[Purpose/Significance] As the cultural treasure of the Chinese nation, cultural heritage plays an important role in highlighting China's cultural background and strengthening national identity. In the process of globalization and digitization, the protection and inheritance of cultural heritage is facing new opportunities and challenges. How to effectively promote the protection and inheritance of cultural heritage and enhance the international influence of Chinese culture is an issue to be considered in the process of building a cultural power. [Method/Process] This paper takes the Chinese tea culture videos on YouTube platform as the research object, constructs the theoretical framework of "Cognitive-Affective-Conative", analyzes users' cognition of Chinese tea culture through LDA topic clustering of video comments, and further explores users' emotional responses. Then, based on the "5W" model, an international communication power measurement model is constructed from three aspects: communication subject, communication audience, and communication content to verify the interaction mechanism among conation, affect and conation. The communication subject factors include influence and credibility. The communication audience factors combine user cognitive themes and user emotions to form user cognitive agreement. The communication content factors are analyzed in terms of video theme, duration, subtitles, and background music. [Results/Conclusions] The video theme of tea sets, the video duration of 4-20 minutes, and the credibility and influence of the communication subject significantly enhance the international communication effect of tea culture videos. While background music and users' cognitive agreement of the tea ceremony negatively affected the communication effect. From the current practice, it can be seen that the application of AI technology in the dissemination of tea culture cannot greatly improve the dissemination effect of videos, which may have much to do with the political nature of video accounts. Based on the above conclusions, this paper further puts forward relevant suggestions for digital intelligence technology to strengthen the protection and inheritance of cultural heritage. The empowerment of digital information technology in the process of cultural heritage protection and inheritance mainly plays a role in the digital storage, data management, digital presentation, and popular dissemination of cultural heritage resources. Looking to the future, with advances in science and technology, new technologies will not only help protect and inherit cultural heritage, but also promote the creative transformation and innovative development of cultural heritage, and maintain its vitality and value.

[Purpose/Significance] AI literacy is becoming increasingly important, not only to adapt to the future development of higher education and the needs of future society, but also to cultivate innovative thinking and problem-solving skills, to enhance decision-making abilities and, most importantly, to emphasize ethical education to avoid the abuse and misuse of AI technology. Existing research emphasizes the importance of AI literacy, with a focus on discussing AI literacy frameworks and pathways. Although some scholars have classified and discussed the AI literacy for teachers and students, there has not been a comprehensive analysis of the skill requirements for different roles in the context of "AI + higher education". [Method/Process] AI literacy education is a multidimensional and multi-level systematic problem. Based on 18 application cases, this study analyzes the specific application scenarios of AI in the educational process, summarizes the development characteristics of "AI+higher education", and analyzes its AI literacy requirements for university teachers, students, managers, and teaching assistants. Therefore, four-role framework for AI literacy is constructed to provide a theoretical reference for future AI literacy education in higher education. [Results/Conclusions] In the context of "AI + Higher Education," future higher education will continue to develop towards ubiquitous teaching, personalized learning, diversified evaluation, and scientific management, ultimately achieving the complete intellectualization of higher education. For teachers, the skills required are innovative teaching and technological integration; for students, active learning and diversified skills; for administrators, forward-thinking leadership and data-driven decision-making; and for educational support staff, intelligent integration of services and resources. The core elements of AI literacy can be summarized as four key components: thinking, knowledge, skills, and attitudes. In specific educational scenarios, the AI skills of teachers, students, administrators, and educational support staff have similarities but also exhibit differences. Due to space limitations, this study did not construct an AI literacy education pathway. In future research, we will continue to deepen the connotation of AI literacy and propose targeted AI literacy education pathways based on the skill requirements of different roles.

[Purpose/Significance] In the open science environment, the mode of collaborative knowledge production is widely used, and the types of scientific outputs are becoming increasingly diverse. Therefore, effective identification and recognition of various contribution contents made by different contributors in open research is crucial to improve transparent disclosure and effective use of research output's contribution data. [Method/Process] Based on the systematic study of domestic and foreign scholarly contribution theories and practices, this study proposes a scholarly contribution analysis system for open science. From the perspective of the creation process of scientific research outputs, research on the attribution of scientific contributions is carried out, focusing on three aspects: the identification of contributors and contribution elements, the calculation of the degree of contribution, and the representation of contribution data. In addition, a paper from the open access platform PLoS One is selected as an empirical case to demonstrate the validity of the process and method of attributing scholarly contributions. It was found that the contribution score is inversely proportional to the number of contributors, i.e., the more the number of contributors, the less likely it is to have a high contribution score. The more contribution elements contributors participate in, the higher the contribution score they receive. If contributors participate in the same contribution elements, and their contribution scores may also be the same. For the same contribution factor, the higher the number of contributors, the lower the contribution degree of each contributor. This paper summarizes the application scenarios of academic contributions from three aspects: clearly distinguishing author and non-author contributors, establishing correlation between contribution data and other LOD ontologies, establishing attribution and responsibility mechanism for academic contributions, and improving the index system of scientific research evaluation. [Results/Conclusions] Academic contribution is an important part of the open science system. It is an inevitable trend to improve the openness and transparency of academic contributions to various scientific research results. However, existing methods for attributing contributions are scattered, lack systematicity, and mainly apply to a certain type of achievement, which has certain limitations in terms of disciplines and achievements. In the future, the applicability of the contribution attribution method can be improved by expanding the application objects of contributions to include research papers, scientific data, scientific software, preprints, scientific notes, and more, establishing a common contribution element system for all types of research outputs, and optimizing the method of calculating the contribution rate. Finally, it is necessary to continuously enrich and expand the application scope and application scenarios of scientific research output's contribution data.

[Purpose/Significance] To explore in depth the acceptance and usage habits of AIGC tools by graduate students in the process of academic research, and to promote the positive attention and application of emerging technologies by graduate students is one of the goals of library knowledge service and information literacy education. This paper aims to reveal the influence mechanism of internal and external factors on the use of AIGC tools by graduate students at the user level, clarify the behavioral motivation of graduate students to use AIGC tools to support learning and research, help libraries to design and promote AIGC services according to the actual situation, and promote the implementation of AIGC technology in knowledge services. [Method/Process] Based on the UTAUT2 model, considering related theories such as perceived value and the characteristics of AIGC tool and graduate student group, this study constructed the influencing factor model of graduate students' AIGC tool use behavior, and provided empirical evidence through questionnaire survey and structural equation model analysis. The survey respondents are graduate students in universities or research institutes. In this study, questionnaires were distributed to graduate students through social media platforms, enterprise Wechat contacts, email, etc., and the survey period was from July to August 2024. After the data collection, statistical software such as SPSS and SmartPLS was used to analyze all the valid data obtained, including descriptive statistics, reliability and validity test and structural equation model analysis. [Results/ [Conclusions] Functional value, use value and emotional value in the tool aspect, individual innovation in individual aspect and social influence in environmental aspect have significant positive effects on graduate students' willingness to use AIGC tools, and indirectly affect their use behavior. Facilitating conditions, such as network equipment, as supporting factors, also have a significant positive impact on graduate students' usage. It is suggested that AIGC tool developers and library service designers consider the functional advantages and convenience. On the one hand, it is suggested that they pay attention to the functional value of the tool, that is, the auxiliary role to the graduate study and scientific research; on the other hand, they consider whether the tool is design-friendly, easy to operate, with low technical threshold and easy to use on an ongoing basis. From a graduate education perspective, it is important to promote the deep integration of the tool use with one's own professional learning and research in order to realize the improvement of other qualities through information literacy. Meanwhile, strengthening students' innovative thinking and comprehensive ability training, and guiding AIGC tool application ability and scientific research thinking to promote each other are conducive to new technologies to truly support learning and scientific research, and ultimately achieve the goal of developing high-level innovative talents.

[Purpose/Significance] Virtual communities of interest have rapidly become key sources of information that significantly influence users' decision making. Characterized by resource aggregation, active exchanges, and high interactivity, these communities foster a unique environment that encourages strong user engagement. Understanding the factors that influence information adoption in these settings is essential to meeting user needs and enhancing community management and services. Unlike traditional information contexts, virtual communities emphasize user trust, emotional support, and community identity, which are critical in shaping how users perceive and adopt information. This study aims to deepen the theoretical understanding of information adoption in virtual communities of interest by incorporating information ecology theory and applying both structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA). This dual-method approach enables in-depth analysis of individual factors and reveals complex configurations that influence adoption behaviors, providing insights that go beyond what SEM alone can provide. [Method/Process] The research model is based on information ecology theory, which provides a holistic framework that captures the dynamic interplay between factors such as information quality, user support systems, community structures, and platform features. This theory is particularly suited to the study of virtual communities, where multiple interdependent factors create a unique decision-making environment. SEM is used to assess linear relationships between variables, evaluating the influence of information quality, emotional support, community identity, opinion leader participation, content interaction, source credibility, and platform usability on users' information adoption intentions. As a complement to SEM, fsQCA is used to explore configurations of multiple factors, identify pathways through which these factors collectively shape adoption intentions, and capture complex causal relationships that SEM does not address. [Results/Conclusions] The SEM analysis shows that information quality, emotional support, community identity, active participation of opinion leaders, and content interaction significantly increase users' adoption intentions, while information source credibility and platform usability do not. These findings suggest that community-driven aspects may be more important to users in this context than traditional credibility indicators. The fsQCA results further identify two primary modes that drive adoption intentions: a trust-driven mode, where adoption is supported by trust-related factors, and an experience-promoting mode, which focuses on user engagement within the community. Together, these modes comprise six distinct configurations, suggesting that users' adoption intentions are influenced by combinations of factors rather than isolated variables. This study thus highlights the unique value of fsQCA in uncovering the complex interplay of factors in virtual communities and providing detailed insights into user behavior. Future research could explore cultural differences in adoption behaviors and additional factors influencing user engagement in different types of virtual communities.

[Purpose/Significance] In the digital age, government digital avatars represent a significant innovative application of the integration of generative artificial intelligence and digital government. These digital avatars aim to enhance the efficiency, accessibility, and responsiveness of public services. This study aims to explore the factors and pathways that influence public acceptance of government digital avatars, providing a theoretical basis and practical insights for improving these services and enhancing the user experience. Unlike previous studies that have focused primarily on technological and functional aspects, this research emphasizes users' perceptions and expectations, filling the gap in existing research on user experience. This innovation of this paper lies in the integration of the Expectation Confirmation Theory (ECT) and the Technology Acceptance Model (TAM) and the extension of other user perception factors to systematically analyze how these factors together influence public acceptance. [Method/Process] The study adopts a comprehensive approach, integrating the Expectation Confirmation Theory (ECT) and the Technology Acceptance Model (TAM), and extends the framework to include additional user perception factors such as perceived information quality, perceived intelligence, perceived convenience, perceived attractiveness, perceived usefulness, and AI trust. Structured questionnaires were used to collect data from a diverse sample, measuring constructs such as expectation confirmation, satisfaction, and various user perception factors. The data were analyzed using structural equation modeling (SEM), which provides robust statistical insights into the relationships between these constructs. In addition, mediation effect models were used to examine indirect effects, providing a comprehensive understanding of how these factors influence public acceptance. Data were collected from a diverse group of respondents to ensure the findings are broadly applicable and representative. [Results/Conclusions] The results suggest that expectation confirmation significantly increases public satisfaction with government digital avatars, which in turn positively affects their acceptance. Perceived information quality, perceived intelligence, perceived convenience, perceived attractiveness, perceived usefulness, and AI trust serve as critical mediators in this relationship. In particular, high levels of perceived quality and intelligence significantly increase satisfaction and acceptance, while convenience and attractiveness also play an important role. AI trust emerges as a critical factor, mediating the impact of user perceptions on acceptance. However, the study does have some limitations. First, the lack of understanding of the professional backgrounds of the research population may lead to differences in acceptance between different professional groups. Future research should look more closely at different occupational groups to gain a fuller understanding. Second, the sample consisted mainly of respondents from younger demographic groups, which may affect the generalizability of the conclusions. Future research should broaden the geographical and demographic coverage of the sample to increase diversity and representativeness. In addition, the lack of qualitative research limits the depth of understanding of users' deep-seated views and needs about government digital avatars. Future research should include qualitative components, such as in-depth interviews and focus group discussions, to explore the actual experiences and specific needs of users and to complement the quantitative findings. This study provides practical recommendations for improving user satisfaction and acceptance, and for supporting the development of effective digital governance solutions. By specifically optimizing government digital avatar services, public satisfaction and trust in digital government services can be increased, further promoting the application and development of digital avatar technology in digital government.

[Purpose/Significance] Farmers' digital literacy is the prerequisite and foundation for the construction and development of digital rural areas. How to quantitatively assess farmers' digital literacy, accurately identify the influencing factors, and then purposefully improve farmers' digital literacy level, and stimulate farmers' vitality in digital village construction has become an urgent task for the current construction of digital villages in China. [Method/Process] Based on the definition of the relevant concepts of farmers' digital literacy, this article constructs an evaluation index system for farmers' digital literacy in Beijing based on theoretical and practical bases, and combines 236 pre-survey data to comprehensively use exploratory factor analysis and confirmatory factor analysis to test the rationality of the evaluation index system. Based on 1500 questionnaire survey data from 13 agricultural areas in Beijing, the current level of digital literacy among farmers in Beijing was evaluated and analyzed. A regression model was constructed to analyze and explore the influencing factors of digital literacy among farmers in Beijing from three dimensions: personal factors, resource supply factors, and environmental factors. [Results/Conclusions] Based on the KAP theoretical model and the practical development needs of Beijing's digital countryside and smart city construction, the article constructs an evaluation system for Beijing farmers' digital literacy indicators, which includes six primary indicators: digital concept awareness, digital general literacy, digital technology literacy, digital innovation literacy, digital social literacy, and digital security awareness, as well as 26 secondary indicators. According to the calculation, the overall digital literacy level of Beijing farmers is 68.15, and there are significant differences between different regions, dimensions, and groups. From a regional perspective, the digital literacy level of farmers in Fengtai District is relatively high, while that in Daxing District is relatively low. In terms of indicators, farmers have the highest level of digital security literacy, while their levels of digital innovation literacy and digital technology literacy are relatively low. In terms of group characteristics, small farmers and older people aged 60 and over have the lowest levels of digital literacy. Farmers' digital literacy is negatively influenced by age, but positively influenced by education level, income level, digital training, digital services, popularization of digital science, digital living atmosphere, and digital network. It is suggested to effectively enhance farmers' digital literacy and promote their participation in digital rural areas by strengthening top-level design, creating a good atmosphere, building a lifelong learning system, and establishing a guarantee mechanism.

[Purpose/Significance] The research paradigm is gradually shifting towards a data-intensive model, where research data has become the cornerstone in the realm of academic endeavors. Effective research data management can enhance the research efficiency of scientific researchers, reduce redundant data collection, and reduce costs. As a central repository for the storage of scholarly research outputs, it is essential that university institutional repositories fulfill their role in research data management. [Method/Process] To gain a full understanding of the evolving landscape, we embarked on a meticulous network-based research investigation. We specifically selected the institutional repositories of 24 prestigious American universities as our research subjects, with the aim of exploring the diverse range of services they provide at different stages of the research lifecycle. Our research was firmly grounded in the data lifecycle framework, which enabled us to systematically examine a wide range of research data management (RDM) services. This included critical aspects such as developing comprehensive research data management plans, establishing robust data organization services and standardized protocols, providing reliable long-term data storage solutions to ensure continued accessibility, enhancing data sharing policies to foster collaboration, strengthening research data quality control measures to maintain integrity, and developing comprehensive research data management training programs to empower researchers. Furthermore, we conducted an in-depth analysis to summarize the characteristics and valuable experiences of American universities in building and maintaining the basic infrastructure of their institutional repositories. [Results/Conclusions] Given the unique circumstances of China's modernization process, this paper distills effective insights and strategies from the institutional repositories of domestic university libraries in the field of research data management services. Our findings highlight the importance of building a localized research data management platform tailored to the specific needs and contexts of Chinese academia. Enhancing the quality of research data management is critical to building a trusted institutional knowledge base and fostering an environment of credibility and reliability. By applying the FAIR (Findable, Accessible, Interoperable, Reusable) and TRUST (Transparent, Responsible, Usable, Sustainable, and Trustworthy) principles, we can facilitate the open and seamless sharing of research data, breaking down barriers to collaboration and innovation. Finally, building a professional scientific research data management team is essential to provide the human capital necessary to navigate the complexities of data management and to promote the development and adoption of best practices in scientific research data sharing. Taken together, these findings help to improve the abiity of the scientific community to harness the full potential of research data to drive the creation and dissemination of knowledge.

[Purpose/Significance] In the rapidly evolving digital landscape, generative artificial intelligence (GenAI) has emerged as a transformative force in information literacy (IL) education, presenting unprecedented opportunities and challenges for library-based learning environments. This scoping review comprehensively examines the integration of GenAI within IL education, moving beyond theoretical frameworks to provide a nuanced analysis of practical applications and strategic implementations. In contrast to existing research that primarily emphasizes technological capabilities, this study explores the profound implications of GenAI on educational paradigms and provides critical insights into the systematic transformation of library IL services in the AI era. [Methods/Process] Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, 51 key literature sources selected from the SSCI, A\&HCI, and CSSCI databases were systematically analyzed. The comprehensive analytical framework encompassed four key dimensions: technology acceptance, educational framework construction, AI literacy cultivation, and the integration of artificial intelligence with IL education. This methodological approach enabled a thorough exploration of current practices while identifying critical gaps in existing research. [Results/Conclusions] The results show that GenAI significantly enhances IL education through personalized learning experiences and improved digital teaching effectiveness. Tools such as ChatGPT have significant potential to promote adaptive learning environments and improve student engagement. The research identifies four primary areas of impact: 1) creating dynamically adaptive learning environments tailored to individual needs, 2) enhancing critical thinking through interactive scenarios, 3) facilitating cross-disciplinary knowledge integration, and 4) generating innovative educational content and resources. However, the study also identifies several critical challenges, including concerns about data accuracy concerns, inherent algorithmic biases, risks to academic integrity, and the potential weakening of independent thinking skills due to over-reliance on AI systems. To address these challenges, the research proposes a comprehensive framework that includes: 1) robust ethical guidelines for the implementation of GenAI, 2) systematic assessment mechanisms to monitor learning outcomes, 3) critical thinking training programs, and 4) strategies to maintain academic integrity and intellectual autonomy. The study emphasizes that the integration of GenAI is more than a technological change - it represents a fundamental shift towards AI literacy education. This evolution will require learners to develop skills beyond traditional IL skills, including understanding AI ethics, legal frameworks, and using AI technologies to solve problems. Future research directions should focus on conducting empirical studies in different educational contexts, developing adaptive teaching frameworks that balance technological innovation with traditional educational values, and investigating the long-term impact of GenAI integration on learning outcomes. By systematically examining the opportunities, challenges, and development trajectories of generative AI, this study provides valuable insights for libraries and educational institutions seeking to optimize their IL programs in the AI era. The findings not only contribute to the theoretical understanding of the role of GenAI in education, but also provdie practical guidance for integrating advanced technologies into traditional educational frameworks, ultimately fostering a more adaptive, intelligent, and personalized learning ecosystem.

[Purpose/Significance] The study aims to construct an early warning model of public opinion risks based on government-citizen interaction data, guided by evidence-based decision-making theory. We seek to uncover the governance value embedded in such interaction data, providing new insights and methods for identifying and managing potential public opinion risks. Traditional methods of monitoring public opinion often rely on subjective judgment, leading to potential bias and inefficiency. In contrast, this study uses objective, data-driven techniques to improve the accuracy and reliability of risk predictions. By integrating evidence-based decision making with public opinion analysis, the study not only advances the theoretical framework but also provides practical tools for government use. This innovation is significant as it addresses the gaps in the current literature regarding the objective assessment of public opinion risks and their impact on governance, thereby contributing to the field of public administration and social governance. [Method/Process] The research methodology involves a multi-step process, starting with the identification of key indicators of public opinion risks. These indicators include appeal purpose, text length, sensitivity, emotional tendency, and degree of aggregation. The analytical hierarchy process (AHP) and the criteria importance through intercriteria correlation (CRITIC) method were employed to calculate the weight of each indicator. AHP, a subjective weighting method, uses expert judgement to construct a judgement matrix and determine indicator weights. However, to reduce subjective bias, the CRITIC method is integrated, which objectively determines weights based on the variability and conflict in the data. The model's workflow began with problem identification, which captures the issues that government officials want to address through public opinion monitoring. Data were then collected from various channels, such as the "12345" government service hotline, government Weibo accounts, and official email inboxes. The risk identification phase involves the construction of a public opinion risk identification index system to identify potential risks in the data collected. This is followed by a risk assessment, where the weight of each indicator is calculated, and the risks are classified into different levels. Finally, decision recommendations were provided based on the risks identified and their urgency. The model was validated using government-citizen interaction data from Suzhou as a case study. The results of the analysis were closely aligned with the future priorities of the Suzhou municipal government, fully demonstrating the model's effectiveness and reliability of the model for early risk warning. [Results/Conclusions] The study concludes with the validation of a feasible and practical early warning model for public opinion risks. The model was tested using interaction data from the Suzhou municipal government's official website, demonstrating its effectiveness in identifying and predicting public opinion risks. The results show that the model can accurately assess the severity of risks and provide timely warnings, helping government decision-makers to manage risks proactively.

[Purpose/Significance] The "15th Five-Year Plan" defines the development direction and strategic choice for Chinese libraries in the next five years. It is based on China's national conditions and serves the characteristic development of Chinese libraries. Against the backdrop of the Chinese-style modernization, this paper explores how libraries can achieve high-quality development under the changing internal and external environment, with the aim of grasping the development direction of Chinese libraries and offering a construction path for the scientific formulation of the "15th Five-Year Plan". [Method/Process] A library strategy is an action plan based on a comprehensive and in-depth analysis of the Chinese libraries' internal and external environment. Environmental scanning is a fundamental part of strategic library planning. It implies that the libraries adapts to environmental changes by seeking and using external information. The formulation of the library strategy must start from the current situation, identfiy external environmental changes such as those in the political, economic, social, cultural and technological spheres, and track responses and developments. Using the research method of environmental scanning, this paper traces the dynamics of the social environment at the macro level, the business environment at the medium level, and the system environment at the micro level, and analyzes the practical demands of the society at the macro level, the medium industry at the medium level, and the library readers at the micro level. [Results/Conclusions] Chinese-style modernization embodies both conceptual and discursive innovation. As an ideological discourse, it has four layers of meaning: socialist modernization, independent modernization, modernization for the comprehensive rejuvenation of the Chinese nation, and modernization that creates a new form of human civilization. This article is guided by the theory of China's modernization and has set the main goal for the construction of China's modern libraries. It emphasizes the leading role of the concepts of "people-oriented" and "efficiency", and focuses on the three major development priorities of "professional and stable development", "intelligent transformation", and "building a national library service network". Finally, it proposes the four modern systems of "the cooperative governance system for libraries of all kinds", "the next-generation knowledge sharing and service system", "the cultural dissemination and social service system", and "the library security and guarantee system". The goal of the Chinese-style modern library is to build a national library service network that is both deeply professional and highly intelligent, organically integrating specialization and intelligence. First, to ensure the specialization of library services, then realize the wisdom to broaden the service boundary, and finally build a national library service network. A cultural communication and social service system should be built in accordance with the macroscopic social needs. A collaborative governance system should be established based on the needs of library development. A new generation of knowledge sharing and service system should be established according to individual needs. The establishment of the support system ensures the successful development of the "15th Five-Year Plan". We should consistently integrate the above three key priorities throughout the four modern systems.

[Purpose/Significance] In the era of digital intelligence, robots technology is playing an increasingly important role in the field of education. The applying of AI chatbots in library scenarios is an important lever for the future construction of learning ecosystems in universities. This study aims to explain the influencing factors of users' willingness to continue using library AI chatbots, and provide a new perspective beyond the IT perspective to understand the impact of the basic characteristics of AI chatbots on human behavioral intentions, in order to better understand the sustainability thinking of interpreters and provide some inspiration for the further development of library AI chatbots in the future learning ecosystem. [Method/Process] Based on U&G theory and the SOR framework, we developed a conceptual model of library AI chatbot users's willingness to continue using the chatbot. Data were collected using a questionnaire survey method, with teachers and students as the main respondents. The variables of the AI chatbot user's continuous usage intention model were set to 8, each consisting of 3-6 options, and then measured using a 7-point Likert scale. Finally, the variables and hypotheses in the model were validated using a mixed research method of PLS-SEM and fsQCA. [Results/ [Conclusions] The research results indicate that three types of satisfaction, hedonic (entertainment and avoidance), social (social presence), and utilitarian (convenience and information consultation), have a significant positive impact on emotional experience (awe experience and emotional participation), with avoidance having the greatest impact on awe experience and social presence having the greatest impact on emotional participation. Emotional experience has a significant positive impact on the intention to continue using, with awe experience having the greatest impact on the intention to continue using. Emotional experience, as a mechanism of action, affects user satisfaction and willingness to use. Based on the data analysis, four suggestions are proposed from the perspective of future learning ecology design and user psychology. When designing library AI chatbots, the usage scenarios should be enriched, and the healing function, immersive experiences and immersive experiences should be emphasized. The limitation of this study is that the use of first-hand cross-sectional data cannot prove whether the influencing mechanism changes over time. In the future, a combination of first-hand and second-hand data can be used to improve the explanatory power. In addition, although this study ensures the validity and reliability of cross-sectional data, there may be geographic and cultural differences in users' behavioral intentions. In the future, a comparative study of the intention to continue using library AI chatbots in different regions and levels can be considered.

[Purpose/Significance] With the proliferation of artificial intelligence (AI) technology, knowledge workers' basic understanding of AI and their ability to evaluate its application, known as AI literacy, is particularly important. This study addresses the current state of the AI literacy gap among knowledge workers and explores how AI technology itself can be used to bridge this gap, with the goal of shortening the AI literacy gap. The article analyzes the reasons for the existence of the AI gap in multiple dimensions and the need to bridge the AI gap. In today's era of proliferating AI tools, mastering the use of AI tools and improving AI literacy is the best assistant for knowledge workers. Learning to use AI tools can significantly improve the efficiency of information collection, processing, and storage, and greatly facilitate the building of information resources. [Method/Process] From the dimensions of cognition, practice, and assessment, the study explores how AI technology can assist in enhancing AI literacy. At the cognitive level, the research examines how AI agents can provide personalized knowledge services and help users build a systematic body of knowledge in a particular domain; at the practical level, it analyzes how AI tools can simplify professional tasks such as data analysis, and suggests how to improve knowledge workers' own ways and means of using AI tools through human-computer interaction and mastering effective AI problem-solving aids; at the assessment level, the application of AI tools in verifying the authenticity of information and the importance of the "human-in-the-loop" model in AI applications are discussed, emphasizing the need for human oversight. The article comprehensively draws on the excellent literature on AI, library intelligence, and learning literacy at home and abroad, and combines its own practical situation of using AI tools to achieve AI literacy, which helps knowledge workers establish basic cognition, practical operation ability, and evaluation of answer results. [Results/Conclusions] AI technology has significant advantages in closing the AI literacy gap. AI agents can provide customized knowledge explanation based on user needs, and AI tools can automate the execution of professional tasks and provide factual evidence. These applications not only compensate for the shortcomings of traditional educational methods but also offer new directions for innovation in the field of education. In presenting the arguments, the number of AI tools chosen is small, but fundamentally representative of the problem. Subsequent research will focus on improving AI literacy from other perspectives, and on ways and means to make knowledge workers more comfortable with AI tools. With the continuous development of AI technology, its role in enhancing AI literacy will become more pronounced, contributing to the construction of a more intelligent and efficient information environment.

[Purpose/Significance] The rapid development of generative artificial intelligence (GenAI) has led to a growing demand for AI literacy in various fields. However, current AI literacy courses often fail to adequately address the diverse needs of students with different academic backgrounds, expertise, and learning levels. This research aims to design an AI literacy curriculum that balances knowledge dissemination with skill development, ensuring that students can not only understand basic concepts but also apply them in practice. [Method/Process] This study is based on the design of Nanjing University's "Exploration of Frontier Applications of Generative Artificial Intelligence" course, which adopts the "knowledge-skills" navigation framework. The course is divided into four progressively advanced levels: foundational cognition, core understanding, tool application, and innovative development. The foundational cognition level systematically organizes the four key knowledge modules involved in generative artificial intelligence: Machine Learning, Neural Networks, Deep Learning, and Natural Language Processing, helping students to build an initial cognitive framework for GenAI. The core understanding level explores advanced topics in GenAI, covering four main modules: basic model pre-training, downstream task adaptation, human-AI value alignment, and AI agents. This aims to enhance students' comprehensive understanding of the technical principles, application methods, and ethical considerations, providing the necessary technical support and conceptual tools for real-world applications. The tool application level consists of three modules: classification of intelligent tools, tool acquisition and use, and derived applications. It gradually guides students from analyzing the characteristics of tools and their use to exploring state-of-the-art applications in multi-modal, multi-scenario, and integrated contexts. Finally, the innovative development level is the final practical stage of the GenAI learning system and includes environment configuration, basic processes, and frontier development. This includes configuration of hardware and software environments, basic steps for development tasks, and advanced practices for complex functions, forming a complete chain from basic support to high-end applications. Following the "knowledge-skills" navigation, the course will also include teaching designs such as concept cognition modules, multi-modal generation and application skill modules, advanced generative AI knowledge and skill modules, and generative AI governance modules, along with the development of corresponding online open courses, open educational resources, and experimental equipment resources. [Results/Conclusions] The "knowledge-skills" navigation framework effectively enhances students' AI literacy by successfully bridging the gap between theoretical knowledge and practical application. The modular structure of the course, combined with multi-modal learning and hands-on practice, effectively meets the diverse learning needs of students. The course allows students to gradually build a knowledge system from basic concepts to advanced skills, fostering a comprehensive understanding of AI technologies.

[Purpose/Significance] Previous studies or reviews of digital twins have focused either on conceptual analysis and theoretical models, or on the current state of the art and implementation, with only a few studies analyzing human-digital twin interaction and collaboration. This paper explores the collaboration between human and digital twin systems, and offers recommendations on how digital twins can catalyze the progress of societal digitization. It envisions a future where the interaction and collaboration between humans and digital twins is not only deepened but also transcended, moving closer to the harmonious integration of man and machine. The proposed strategies aim to unlock the full potential of digital twins in promoting a more connected and intelligent world. [Method/Process] This paper is a systematic literature review focusing on the partnership between human and digital twin systems, emphasizing the role of artificial intelligence. We analyze the value positioning, key technologies and practical applications through 45 papers from home and abroad. Then, we explore the construction path of digital twin technology-enabled information resource management. [Results/Conclusions] The study shows that human and digital twin systems have different unique values in the whole ecology, the irreplaceable wisdom of the human brain is reflected in innovation and decision-making, and the core function of the digital twin system is to support and enhance the communication between man and machine. AI technology plays the role of the pedestal in the interaction. There are common enabling technologies for human intelligence collaboration in the digital twin ecosystem, and the types of key technologies supporting human intelligence collaboration in different twin modules are not identical but synergistic with each other. The supporting technologies in digital twin environment mainly involve data acquisition and data transmission, model twin mainly lies in data fusion and management, image recognition and processing, and process twin mainly involves human-computer interfaces, immersive perception and other key technologies. In terms of application areas, human-intelligent information system cooperation at home and abroad has rich applications in industry, healthcare, smart cities and public cultural services, especially in public cultural services, where cooperation has accelerated the intelligentization process of public cultural service institutions. Finally, the study categorizes the human-intelligent information system collaboration methods in the digital twin ecology into three types: pre-determined, collaborative, and autonomous, proposes a holistic framework for the twin co-intelligence system of intelligent connections, and summarizes the current obstacles and development strategies from a realistic perspective. There are some limitations due to the limited samples, which can be increased in the future to deepen the mining and analysis to optimize the form of human-intelligent information system collaboration in the digital twin ecosystem.

[Purpose/Significance] The development of artificial intelligence (AI) technology has brought huge changes and opportunities to library knowledge services. With the improvement of the multimodal capabilities of large language models, the ability of generative artificial intelligence to generate cultural images, cultural audio, and cultural video will also improve, which will effectively promote the intelligent transformation of library knowledge services and support the innovation of library knowledge services. General AI has stronger generalization ability, which can achieve functions such as complex task understanding, multimodal data learning, zero-sample reasoning, and continuous dialogue, completing the transformation from data-driven AI to natural mechanism-driven AI. By studying the theoretical foundation, system framework and application perspective of knowledge services based on artificial general intelligence, we can get new research ideas and practical references for knowledge services. [Method/Process] Based on the classification of the development history of AI, this article examines the state of research in AI for library knowledge services from the dynamic perspective of the evolution from generative AI to artificial general intelligence. This article analyzes the system framework of library knowledge services constructed with generative artificial intelligence and artificial general intelligence as technical bases, and explores the future development trend of library knowledge services based on artificial general intelligence from the aspects of space, content, mechanism and talent. [Results/Conclusions] With the continuous development and optimization of large language model technologies, the gradual implementation and widespread application of artificial general intelligence technology is an inevitable trend in the future. With the promotion of artificial general intelligence, library knowledge services will also undergo significant changes, and the traditional knowledge service model based on existing resources will gradually transform into a digital intelligence service model. Although artificial general intelligence has shown great potential in knowledge understanding and content generation, artificial general intelligence is still at an early stage of development, and its prospects for application in library knowledge services are not yet clear. In order to explore the impact of artificial general intelligence on the library knowledge service model, this article summarizes the different stages of AI technology integration in knowledge services, namely the evolution from automation to cognition and then to autonomy, and proposes an AI agent-driven library knowledge service framework. It is believed that artificial general intelligence technology will open up new development space for library knowledge services, promote academic research and practical applications in knowledge services and enter a new era of rapid development.

[Purpose/Significance] Improving artificial intelligence (AI) literacy has emerged as a critical focus in global education, reflecting the growing significance of AI in today's society. This study aims to explore and interpret the core elements and key competencies articulated in the UNESCO AI Competency Framework for teachers and students, and to provide practical guidance for educators and policymakers, offering insights that can facilitate the systematic integration of AI literacy education. A comprehensive approach to AI education is needed to equip both students and teachers with the skills and knowledge necessary to navigate and thrive in an increasingly intelligent era. The results of this study are intended to support the formulation of effective pedagogical strategies, thereby contributing to the enhancement of AI literacy among educational stakeholders. [Method/Process] The study analyzes the preliminary policy foundations and background that led to the creation of the UNESCO AI Competency Framework. It analyzes the content of both the AI CFS and the AI CFT, focusing on key principles and framework structure to systematically interpret the framework's content. In particular, this study explores the policy context in which these frameworks were developed and examines how global educational goals and technological advances have influenced the articulation of AI competencies. By understanding the development and rationale behind the UNESCO AI Competency Framework, this study aims to provide a comprehensive overview that can support the development of effective AI literacy initiatives. It also highlights the connections between the intentions of the frameworks and the practical competencies required of educators and students, thereby contributing to a deeper understanding of how AI literacy can be meaningfully integrated into educational practice. [ [Results/Conclusions] Based on the experience provided by the competency framework and considering the current state of AI literacy education, this study offers insights and recommendations for developing AI literacy education in China from four perspectives: core values, policy refinement, practical application, and future implementation. Specifically, this study emphasizes that all educational stakeholders should work together to improve AI educational content and methods, and move toward a teacher-student-AI interaction model that empowers teachers, fosters student creativity, and integrates AI as a facilitator of personalized, flexible, and multidirectional learning. In terms of policy refinement, this study advocates for the creation of a supportive policy environment that addresses the unique challenges faced by educators and learners in the Chinese context. For practical application, the study provides actionable recommendations for integrating AI literacy into curricula, emphasizing project-based learning, hands-on experiences, and interdisciplinary approaches that foster a comprehensive understanding of AI concepts. Finally, in terms of future implementation, this study highlights the need for ongoing professional development for educators, such as the establishment of assessment mechanisms to monitor and evaluate the effectiveness of AI literacy programs over time.

[Purpose/Significance] AI technology has brought unprecedented challenges and opportunities to the knowledge service industry, requiring innovation and reform of knowledge services in various dimensions, including technology, organizational mechanisms, and service models, to adapt to the development of emerging knowledge productivity. AI technology has not only changed the way knowledge is produc ed and disseminated, it has also significantly influenced the processes by which users acquire knowledge and the systems through which they produce knowledge. Simply promoting the empowerment of knowledge services through AI from a technical point of view is not enough to achieve the transformation and upgrading of knowledge service institutions. [Method/Process] This article begins with the multi-level transformative impact of AI technology on emerging knowledge productivity, proposing that generative AI has rapidly become a powerful new force in knowledge production, and that AI agents are gradually becoming revolutionary tools for the flexible design and innovation of complex processes. We argue that the rapid development of AI has deepened the connotations and forms of AI empowerment. The article further explores the barriers in production relations in the development of new quality productive knowledge services and examines the challenges of aligning traditional knowledge services with user knowledge processes and user production systems in the AI environment. We propose to promote the development of the knowledge service industry through multi-level AI empowerment and innovation of the traditional organizational mechanisms of knowledge services. The article emphasizes placing the construction of new production relations at the key point of AI empowerment, developing new user-oriented, user-process-driven knowledge service organizational models, and developing new docking logic and service embedding architectures between knowledge services and user production systems, as well as building user-oriented, service-driven internal organizational models. Specifically, we present possible new directions for knowledge service production relations, such as the Library-Inside model, the Inside-Out+Outside-In model, new docking architectures between knowledge services and user production systems, and reforms in internal organizational models of institutions. [Results/Conclusions] By exploring the multi-level transformative effects of AI technology and analyzing the barriers in the production relations of new quality productive knowledge services, this article proposes to reform and innovate the production relations of knowledge services. In order to promote the development of new quality productive knowledge services, we summarize the construction ideas of new-type knowledge service production relations, aiming to sustainably promote the development of new quality producitve knowledge services in the process of improving users' knowledge productivity and promoting the high-quality development of users' production systems.

[Purpose/Significance] The spread of misinformation on social media has caused serious harm and attracted attention from various disciplines. This study aims to systematically examine the factors associated with the propagation of misinformation. It contributes to the existing literature by providing an integrated model of the factors influencing misinformation propagation, which is crucial for understanding and mitigating the spread of misinformation. [Method/Process] The search strategy, developed with the help of librarians, was searched in six Chinese and foreign databases. Four researchers coded the information back-to-back to ensure the accuracy of the analysis. Our literature screening criteria were rigorous to ensure that only high quality and relevant research was included. A total of 108 empirical studies related to misinformation propagation were included. The factors were summarized and sorted from multiple perspectives such as disciplinary field, theoretical foundation, research methods and different roles. [Results/Conclusions] Research on this topic has grown rapidly in recent years. Scholars from a variety of disciplines have used survey and experimental methods to study misinformation in the areas of politics and health. Pedictors of misinformation propagation are mainly studed from the perspective of users and information, including objective characteristics of information, perceptual characteristics of information, as well as individual characteristics, cognitive characteristics, and perceptual characteristics of users. The results show that individual characteristics play a critical role in shaping users' intention and behavior to propagate misinformation. Individual characteristics are the most frequently studied factors, while information and situational characteristics have received less attention. Psychological and behavioral variables, including users' cognitive, emotional, and behavioral responses play key mediating roles in this process. In addition, the types of information, individual attributes, cognitive characteristics, social interactions, personal knowledge, behavior and emotions play moderating roles. This study constructs an integrated model of the influencing factors for misinformation propagation, which can provide direction for targeted interventions and algorithm design to mitigate the spread of misinformation. The study also identified some limitations of current studies, including an excessive focus on the political and health issues, a lack of attention to how information characteristics, intervention factors, and platform characteristics play a role, and the relative simplicity of the research methods. Future studies should focus on misinformation propagation in other scenarios, explore more information characteristics suitable for algorithmic intervention, examine the differences in misinformation propagation on different platforms, and use mixed research methods to reach more credible conclusions. This study provides directions and goals for multi-agent collaborative misinformation management.

[Purpose/Significance] As China enters the threshold of an aging society, the health problem of the elderly group has become the focus of attention from all walks of life. The demand for health information among this group has increased dramatically, not only because of the physiological changes associated with aging, but also because they have high expectations of how health information can improve their quality of life. As a unique branch in the field of information behavior, the research on the health information behavior of the elderly presents specific complexity in its object, phenomenon and mechanism. The acquisition, processing and application of health information has a profound impact on the health behavior of older people, particularly the potential for inappropriate drug use and overuse of drugs, which is often closely linked to their health information behavior. Therefore, in-depth research in this area is urgent and important. [Methods/Process] Based on the topic differentiation perspective, this paper conducted a comprehensive and in-depth literature review on the occurrence mechanism, internal influencing factors (such as cognition, emotion, social support, etc.) and external environment (such as family, community, and medical system) of health information behavior of older people. This review aims to identify the status quo, hot spots and shortcomings of current research, and to provide a valuable reference frame of reference and inspirational direction for future research. [Results/Conclusions] The study found that there were significant differences between the concerns of the elderly and the young and middle-aged in health information behavior, mainly reflected in the preferences for types of health information and factors influencing health information behavior. There are also large differences between urban and rural areas, social backgrounds at different stages of development, different social characteristics (such as educational background, economic status), individual characteristics (such as age, gender, health status) and health information behaviors in different scenarios. In terms of study objects, future studies can design experiments with control groups to explore more precisely the specific differences in health information behaviors of older people at different stages of development and with different characteristics. In terms of research content, we should broaden our horizons and introduce a variety of theoretical models in combination with the trend of social development, so that the research field not only covers a wider area, but also improves the depth of research. In terms of research methods, future research should actively explore new perspectives, adopt innovative research methods, such as the survey experiment method, and try to combine modern technical means, such as big data analysis and artificial intelligence to obtain more comprehensive and accurate data resources, while exploring and developing new research methods and analysis tools to promote the continuous in-depth development of research in this field.

[Purpose/Significance] In recent years, China has been committed to building a strong educational country. As key academic institutions within universities, university libraries play a vital role in disseminating knowledge, nurturing talent, and supporting scholary research. Their development is of great significance in promoting the high-quality development of higher education and realizing the goal of building a strong educational country. This study focuses on the "15th Five-Year Plan" of university libraries. It analyzes the development characteristics of university libraries during the "14th Five-Year Plan" period, explores the opportunities and challenges they face in the new era, and puts forward key points and suggestions for the "15th Five-Year Plan" to promote the transformation and upgrading of university libraries and better support the building of a strong education country. The innovation of this article is that it comprehensively considers various factors and national strategic requirements, and puts forward a relatively systematic and forward-looking development plan for university libraries, which provides a new perspective and practical guidance for the research and practice of university libraries in the new era. It contributes to the improvement of the theoretical research system of library science and promotes the deep integration of library services with teaching, scientific research, and cultural heritage in the digital age. [Method/Process] This study mainly adopts the methods of literature review, data analysis, and case study. By collecting and analyzing a large body of literature on library development policies, strategic plans, and related research findings from home and abroad, it examines the development context and trends of university libraries. At the same time, it analyzes the statistical data of library funds, resource construction, and service development during the "14th Five-Year Plan" period to objectively understand the current situation and problems. In addition, it also studies the development cases and practices of some excellent university libraries at home and abroad to draw on successful experiences. The theoretical basis of this study is drawn from the theory of library science, information science, and the relevant theories of education and cultural development. The empirical basis is mainly based on the actual situation and data of the university libraries in China in the past few years. [Results/Conclusions] During the "14th Five-Year Plan" period, university libraries have not only made certain achievements in smart library construction, digital transformation, and information literacy education, but they also face challenges such as reduced funding and polarized academic evaluation services. In the "15th Five-Year Plan" period, university libraries should seize the opportunities provided by national strategies such as national cultural digitization and educational strength, and focus on eight aspects, including to modernize the management system, strengthen the construction of data infrastructure, promote the construction of digital special collections, support digital intelligence teaching, explore the management and operation of future learning centers, build intelligent service systems supported by artificial intelligence, provide full-cycle support for scientific research, and enhance the reader's experience in the virtual environment. At the same time, it is necessary to pay attention to the evaluation of development results, summarize experience and lessons learned, and continuously optimize the development path. Future research can further explore the specific implementation strategies and detailed operation methods of each plan point, strengthen the cooperation and integration between libraries and other departments in the school, and conduct in-depth research on the application and impact of emerging technologies in libraries.

[Purpose/Significance] In the process of providing and receiving public cultural goods empowered by digital technology, digital inequality caused by the digital divide tramples on digital justice. Digitization has shaped the space of digital ecological justice, and digital justice is naturally consistent with "fairness". The value attribute of "justice" is its rightful meaning. The connotation of digital empowerment is "efficiency", which is not only the application of technology and data, but also the methodology of promoting economic and social development through digital means. Exploring the positive significance of digital empowerment is a great driving force for the innovative development of public cultural construction in the new era. [Method/Process] By analyzing the relevant literature, we started from the public attribute of public cultural goods, by sorting out basic concepts such as "digital justice", "digital empowerment", and "digital divide", and explored the logical essence of achieving "social justice" under the unity of efficiency and fairness. This article is a return to traditional justice theory and has been promoted and expanded under the value orientation of digital justice in the new era. In order to achieve a natural state where free individuals are not coerced, value analysis methods should be used to address the conflict between the human-centered justice value orientation and instrumental rationality in the context of digital empowerment, as well as the mismatch between traditional social rights protection mechanisms and digital social operating models. We use the contradiction analysis method to explore reality dilemmas and value conflicts, and provide suggestions for resolving conflicts. [Results/Conclusions] The supply and acquisition of public cultural goods should follow the requirements of digital justice in the digital field and space, and embody the value attribute of "justice", which is its rightful meaning. Suggestions for dealing with the difficulties include returning to the humanistic value theory, clarifying the relationship between ends and means, establishing a standardized new ecosystem for digital empowerment, reaching a rational consensus on addressing digital inequality, and affirming that we are guided by the dynamic and genuine cultural needs of citizens. This article provides a "should-be" approach to further optimize the supply and acquisition of digitally enabled public cultural goods and services. The focus of this article is on value attribute analysis, comparative and practical research on micro-level policies and specific cases of digital empowerment of public cultural goods supply and acquisition. It is also necessary to fully investigate the reality in China and gather information and data. In the future, we will focus on finding viable solutions to real-world problems in order to increase the positive impact of "digital empowerment".

[Purpose/Significance] Universities are important bases for cultivating national innovative talent. In the context of China's implementation of the strategy of strengthening the country through talent and innovation, intellectual property literacy (IPL) has become an essential quality for college students to adapt to the society. In order to explore the ways and methods of IPL education in the training of innovative talent in university libraries, this paper aims to discuss the practical experience of IPL education based on innovative talent cultivation among college students. [Method/Process] Taking Yangzhou University Library as an example, we are undertaking the work of IPL education for undergraduates, graduates, and innovation and entrepreneurship students in non-law majors at universities. The IPL education in the cultivation of innovative talent of college students are divided into different stages, including innovation and entrepreneurship cognition stage to cultivate the intellectual property innovation awareness for innovative talent, comprehensive literacy education stage to inspire the intellectual property innovative ways of thinking for innovative talents, innovation ability training stage to improve the intellectual property practical skills for innovative talent, and professional knowledge development stage to improve the quality of intellectual property creation for innovative talented people. Under the guidance of the characteristics of demand for IPL in different educational stages, the content and the objectives of IPL education are formulated, the purpose is to comprehensively enhance students' awareness and ability of intellectual property innovation, which will lay a solid foundation for future technological innovation activities and intellectual property protection. [Results/Conclusions] The IPL of innovative talent plays a crucial role in the country's innovation-driven development. IPL education in the training of innovative talent in universities is a systematic project that requires constant practice and reform in university libraries, only then can we build an IPL education system that is compatible with the concepts of cultivating innovative talent and innovation and entrepreneurship education. We also made some suggestions on IPL education in the cultivation of innovative talent,including strengthening the construction of talent team in IPL education, emphasizing the demand of personalized talent on IPL education, focusing on the practical education of IPL for innovative talents and strengthening the cooperation between university libraries and innovation and entrepreneurship departments. In addition, we should inject more effective vitality into the training of innovative talent in colleges and universities.

[Purpose/Significance] This study aims to analyze the mechanism of collaborative knowledge management capability on the innovation of new think tank smart services, clarify the internal driving force and main methods of providing innovative new think tank smart services, and uncover the internal role "black box" of innovation in new think tank smart services from the perspective of collaborative knowledge management, in order to enhance the innovative new think tank smart services. The contribution of the article lies in the construction of a model for understanding the role of collaborative knowledge management capability in providing the innovative new think tank smart services. The impact of collaborative knowledge management capability on the innovation of new think tank smart services is a complex dynamic process that requires continuous investment of multiple forces and energy. Through system dynamics simulation, it is possible to observe which key factors should be emphasized in long-term development, providing reference basis for organizational development. [Method/Process] This article takes knowledge ecology as the theoretical support, analyzes the composition of collaborative knowledge management capability and its mechanism of action on innovative smart services in new think tanks, and uses system dynamics methods to construct a model of the effect of collaborative knowledge management capability on innovative smart services in new think tanks. It simulates and analyzes the dynamic changes in the impact of each capability on innovative smart services, providing reference for the development of innovative smart services in new think tanks, simultaneously expanding the research perspective of new think tank smart services. [Results/Conclusions] The results show that collaborative knowledge ability, collaborative supporting ability and collaborative management ability have different effects on the smart service innovation of new think tanks, and collaborative knowledge ability is the key factor affecting the smart service innovation level of new think tanks. This article cannot cover all collaborative knowledge management capabilities in the classification of collaborative knowledge management capabilities. In the future research, it is necessary to explore their impact on the innovation of new think tank smart services from a more comprehensive and representative perspective.

[Purpose/Significance] With the rapid advancement of information technology, library services are undergoing transformative changes. The emergence of generative artificial intelligence (Generative AI) presents unprecedented opportunities and challenges for innovation in smart library services. By enhancing service efficiency and user experience, generative AI supports core library functions, such as personalized recommendations, intelligent question answering, and automatic summarization. This research explores the implications of applying generative AI technology to library services, with the goal of understanding its transformative impact on the field and addressing its potential risks. Unlike traditional studies that focus primarily on functionality, this study emphasizes the ethical, technical, and management risks associated with the use of generative AI in libraries. The study occupies an important place in the advancement of knowledge in this area and contributes to the development of sustainable, user-centered library services capable of addressing significant contemporary challenges related to information accessibility and data security. [Method/Process] This study uses a systematic literature review and case analysis to examine the current state of generative AI applications in smart libraries. A comprehensive approach is taken to understand how generative AI can enhance library services in areas such as personalized recommendation systems, intelligent Q&A, and automated summarization. The study draws on both theoretical and empirical sources, utilizing qualitative analysis to examine trends in the use of generative AI in different types of library services. This review also includes a thorough examination of the potential risks associated with implementing these technologies. Technical risks include data security vulnerabilities and model bias, while ethical risks focus on the issues surrounding user privacy, misinformation, and intellectual property rights. Management risks are also discussed, including the challenges of maintaining system stability and ensuring regulatory compliance. The multi-dimensional risk framework developed in this study provides a robust structure for analyzing these complex challenges and serves as a foundation for future empirical research in smart library applications. [Results/Conclusions] The research reveals that while generative AI can significantly improve the quality of library services and user satisfaction, it also poses significant risks. These include challenges related to data security, model bias, ethical standards, and management complexity. To address these, the study proposes a number of risk mitigation strategies. Key recommendations include strengthening data security through advanced encryption and access controls, increasing model transparency to build user confidence, and ensuring system stability through rigorous testing and monitoring. In addition, the study advocates for the establishment of ethical guidelines that prioritize user privacy, transparency, and content accuracy. It also underscores the need for ongoing regulatory adjustments to keep pace with technological advances. The study concludes by identifying limitations, such as the lack of quantitative data and real-time experiments, and suggests areas for future research. Future studies should focus on empirically validating the proposed framework, exploring the long-term impact of generative AI on library services, and developing best practices for balancing innovation with ethical responsibility. The continued evolution of generative AI is likely to deepen its integration with smart libraries, enabling innovative service models that meet the diverse and dynamic needs of users while safeguarding against potential risks. This research provides a foundational reference for library managers and policymakers seeking to implement generative AI responsibly and sustainably, and to promote the progressive transformation of library services in the information age.

[Purpose/Significance] Rich Internet data provide a multi-dimensional perspective for understanding emergencies, and multimodal emergency classification methods have emerged. However, the existing multimodal datasets of emergencies are not only scarce, but also lacking in diversity in categories, which is not enough to support related research, and greatly affects the progress of subsequent research. Compared with previous public datasets, the dataset constructed in this paper has richer categories and more improved modalities. This dataset solves the key gaps in the availability and diversity of multimodal datasets of emergencies. It not only expands the category range, but also provides more detailed classification in the natural disaster category, which is crucial for developing robust and accurate multimodal classification models. [Method/Process] An emergency event dataset (MEED) based on multimodal information was constructed, which contains data from five categories: accident disasters, public health, social security, natural disasters, and non-emergency events. The natural disaster data are divided into seven subcategories: geological disasters, biological disasters, drought disasters, marine disasters, meteorological disasters, earthquake disasters, and forest and grassland fires. [Results/Conclusions] The existing emergency classification methods were analyzed and validated on the emergency public dataset and MEED. The results showed that MEED helped improve the performance of multimodal models by more than 10% compared with the currently available emergency datasets. The results show that the improvement in model performance highlights the value of MEED in promoting emergency management and response research and applications. The dataset enables researchers and practitioners to better understand the complexity of emergencies and develop more effective prevention, mitigation, and response strategies. The improvement in model performance also shows that multimodal methods are a promising direction for analyzing emergency events because it leverages the advantages of different types of data to achieve higher accuracy and reliability in classification tasks. The creation of MEED is a major advancement in the field of emergency management, providing researchers with a valuable resource and potentially leading to the development of more sophisticated tools for responding to emergencies. However, the dataset still has certain limitations. Over time, the number of emergencies on the Internet continues to grow, which requires us to continuously update the dataset to adapt to new situations. The size of the dataset largely determines the performance of the classification model. The class imbalance problem of the emergency dataset constructed in this paper needs to be solved. In future research, we will continue to update and maintain the dataset in a timely manner to address these issues.

[Purpose/Significance] The generative natural language processing model represented by ChatGPT is beginning to show great application potential in libraries, and its technical advantages coincide with the development needs of knowledge services, greatly improving the quality and efficiency of user services. [Method/Process] Starting with the introduction of ChatGPT's development history, technical advantages and theoretical and practical research achievements of Chinese and foreign academic circles, this paper explains its technical advantages in cross-modal information organization, text generation, and in-depth mining of user behavior. The most direct use of ChatGPT for a library is to connect the library's collection resources to ChatGPTAPI. Using machine transformer, human feedback reinforcement learning and other technologies to create its own open source chat machine model with intelligent interactive question and answer, text and image multi-mode generation, semantic search and discrimination and other functions, the application scenario covers a range of areas from basic library information services to intelligent knowledge services. During the consultation, users can use natural language to communicate directly with the model, and ChatGPT uses semantic analysis and pre-training models to fine-tune the language environment to provide a more accurate question and answer service in different contexts. During a search, the multi-modal technology of ChatGPT can fully realize the multi-source heterogeneous data input of information resources inside and outside the library, so as to effectively solve the problem of multi-dimensional, multi-level and multi-source cross-mode "heterogeneous aggregation" in information retrieval, and help search engines find more comprehensive search results. In addition, ChatGPT automatically generates subject resources such as abstracts or reviews that are highly relevant to the knowledge content of the user's ongoing conversation. By accurately capturing and analyzing the profile characteristics of users' interests and hobbies, ChatGPT can recommend personalized subject guidance services to them based on knowledge graphs, and quickly realize effective collection, refinement and analysis of knowledge related to required subject areas. At the same time, the application focuses on the risks and challenges posed by technical limitations, intellectual property rights, user privacy, harmful information, data sources, academic integrity and other aspects. [Results/Conclusions] In the future, ChatGPT will be embedded in knowledge services with a new quality of productivity, but it is necessary to recognize the limitations and security risks of this technology. At this stage, libraries should take a series of measures in advance to integrate business platforms and resources, strengthen internal system security prevention, improve the risk supervision mechanism and enhance the professional quality of librarians to fully cope with the crisis. It also provides a new research focus for libraries to actively build their own language interaction model in the future. Given the limited practical experience of ChatGPT in the library knowledge service, this paper only provides a risk analysis and prediction in the application, and the specific implementation path and rules in the future need further study.

[Purpose/Significance] With the advancement of communication technology and the popularization of smart mobile devices, social media platforms have developed rapidly. The increased exchange of information via social media platforms has increased the complexity and the spread of public opinion. Understanding the topological structure of information dissemination networks across platforms and the mechanisms of public opinion dissemination on them is of great significant guiding importance for predicting trends in online public opinion and formulating guiding strategies. [Methods/Processes] Based on the SEIR model of infectious diseases, a model of the spread of public opinion on cross-social platform coupled networks was constructed. Using the Monte Carlo simulation method, the experiment explored the effect of the degree of coupling between users and the type of coupling between platforms on the speed and extent of the spread of public opinion, revealing the laws of the spread of public opinion in cross-social platform coupled networks. [ [Results/Conclusions] The simulation results indicate that, compared to single-layer networks, the inter-layer edges formed by users across platforms significantly promote the spread of public opinion. As the degree of inter-layer coupling in the network increases, the speed of public opinion diffusion accelerates and the extent of diffusion increases. For inter-layer coupling modes, homophily links are more conducive to the spread of public opinion information than heterophily links. The results of this study provide valuable guidance for public opinion management. In a networked environment, government departments should disseminate accurate and authoritative information promptly through a variety of channels to gain the upper hand in public opinion. Given the positive correlation between inter-layer coupling and the speed at which public opinion spreads, it is crucial to closely monitor other platforms with a high degree of user overlap with the current one, and to accurately understand key data such as user overlap, activity levels, and differentiation between platforms. This will help to identify key users with high influence and activity, and enable more targeted, personalized guidance strategies. For platforms with a high degree of user assortative connectivity, the emergency response to public opinion should be enhanced. Conversely, platforms with a high degree of user disassortative connectivity should implement more stringent information filtering and response measures. The model constructed in this paper can simulate the basic structure of real coupled social networks and the process of spreading public opinion to some extent, but there are still shortcomings. Future research can introduce more factors, such as user behavior characteristics and content attributes, to construct a more refined public opinion diffusion model, thereby enhancing the model's capability to describe the real-world mechanisms of public opinion information diffusion.

[Purpose/Significance] In recent years, the development momentum of the artificial intelligence (AI) technology industry has been strong. From the perspective of policy instruments, in-depth discussion on the high-quality development path of China's AI technology industry is of great significance to the selection of high-quality development path of China's provincial AI technology industry and the formulation and optimization of government policies in the AI industry. [Method/Process] The mechanism of the high-quality development path of the AI technology industry is relatively complex. The article is based on the theory of policy instruments, selecting supply-oriented, environment-oriented, and demand-oriented policy instruments as the analytical framework. The platforms such as Peking University Treasure, Law Star, and various provincial administrative region government portals were used to review policy texts. A total of 42 policy texts were selected as the objects of analysis, and NVivo software was used to encode the text content and assign conditional variables. The evaluation index of regional competitiveness of AI technology industry in 31 provincial administrative regions was selected as the result variable of QCA analysis, and the fuzzy set qualitative comparative analysis method was used to explore the diversified combination driving path of policy instrument elements. [Results/Conclusions] Research has shown that the high-quality development of the AI technology industry is influenced by multiple policy instruments, including demonstration and promotion, infrastructure, technical support, cooperation and exchange, and target planning. There are three combined paths, namely the supply-oriented path, the supply-demand synergy path, and the supply-demand-environment synergy path. The government should promote the high-quality and sustainable development of China's AI technology industry by improving the basic support system, continuously promoting infrastructure construction, improving the environmental impact mechanism, creating a sound and favorable policy environment, optimizing the structure of policy instruments, and strengthening demand-oriented public services. This study has several limitations. On the one hand, the selection of conditional variables needs to be further optimized; on the other hand, the article has not further verified the key combination path that affects the high-quality development of China's AI technology industry. In subsequent research, we will continue to improve the variable selection of policy instrument elements, draw on and explore more scientific variable assignment standards and methods, and conduct in-depth analysis of the specific combination path obtained in the article to verify the feasibility and scientificity of the key combination path for the high-quality development of the AI technology industry. This will further enrich the theoretical achievements of AI policy research and provide strong theoretical support for the formulation of AI technology industry policies.

[Purpose/Significance] Artificial intelligence is empowering scientific research and has become a major driver of scientific discovery. High-quality data resources for thematic scenarios are the key to training high-performance AI models. Given the complexity of scientific and technological (S&T) literature data and the limitations of its direct use for large-scale model training, there is a urgent need to build a systematic data construction technology framework to process, refine and curate S&T literature resources, and ultimately build a high-quality training corpus for AI applications. Some experts have conducted a number of studies, but there is still a lack of research on S&T literature AI data system for thematic scenarios. [Method/Process] This article proposes a "3+5 technical framework" plan for the construction of an AI data system for themed scenarios. Focusing on the whole process of AI data system construction, it refined and designed three levels of data content and five stages of data governance. The three-level data structure inclueds the multi-type basic database, the multi-model deconstruction database and fine-grained semantic mining knowledge base. The five-level construction stages are multi-channel data source scanning, multi-type basic data construction, multi-modal deconstruction data construction, fine-grained semantic mining knowledge construction and multi-scenario data application. Taking big data technology and intelligent mining technology as the key elements of data governance, the system architecture and functions of the data governance tool chain are described in detail. The core components of the tool chain are multi-source data aggregation tool, multi-format data parsing tool, data cleaning tool, associated file identification and acquisition tool, data fusion tool, multi-modal deconstruction and reorganization tool, and fine-grained knowledge identification tool. Working together, these tools ensure the efficiency and integrity of the design process from raw data to the AI data system. [Results/Conclusions] To verify the effectiveness of the proposed technical framework, this study has built a knowledge base in the field of rice breeding. The AI data system for thematic scenario of rice intelligent breeding includes a multi-type basic knowledge layer, a multi-modal deconstruction and recombination knowledge layer and a fine-grained semantic mining knowledge layer. The basic knowledge layer includes general scientific papers and patent data; the multi-modal knowledge layer includes the multi-modal data deconstruction of the paper content; the domain semantic mining knowledge layer focuses on the professional knowledge in rice intelligent breeding, such as rice variety validation data, phenotypic characteristics data, and rice lineage network. The results showed that the framework can effectively process S&T literature data and build a high-quality domain knowledge base, providing data support for the application of AI models in rice breeding research, verifying the effectiveness and practicality of the framework.

[Purpose/Significance] Against the backdrop of the increasing popularity of artificial intelligence technology, particularly large language models, this paper aims to explore their applications in the field of digital humanities, with a particular focus on the retrieval of ancient documents. Through the practice and exploration of the ancient document retrieval platform at Peking University Library, this study not only introduces new perspectives and methods to the field of digital humanities, but also promotes academic research and cultural heritage. It also provides practical references for other university libraries, which is an important guide. [Method/Process] The article begins with an overview of the origins and development of the digital humanities, emphasizing its central role in humanities research. The paper then examines the current state of the arts in large language models and analyzes their potential and advantages for identifying and classifying ancient documents, semantic understanding and parsing, and information extraction and association. Through the analysis of practical case studies, this paper constructs a fundamental semantic retrieval model, the core architecture of which consists of two critical components. First, the construction phase of the retrieval engine involves meticulous pre-processing of the ancient document information to generate basic metadata. Using large-scale models, these metadata are subjected to in-depth processing and enhancement to create auxiliary search fields and enriched text. In addition, the text processed by the model and the original text are transformed into semantic vectors, which are then stored in an efficient vector engine for rapid retrieval. Second, the search and sort component is another core part of the model. This part accurately processes the user's search terms through large models to generate extended content and, in conjunction with the search terms, creates accurate semantic vectors. Utilizing the previously constructed vector engine, the model can efficiently retrieve relevant documents and intelligently sort the search results based on specific algorithms, ensuring that users can quickly obtain the most relevant and valuable information. Taking the ancient document system collection data of Peking University Library as the research object, the paper processes over 250,000 records, primarily consisting of ancient books and rubbings, as well as over 10 million metadata items. Using the gradio framework on a server equipped with two NVIDIA RTX 4090 24G graphics cards, a semantic retrieval platform was created to effectively manage and retrieve these vast amounts of data. [Results/Conclusions] The main strengths and contributions of the study lie in the standardized metadata organization, the metadata extension supported by large models, the support for natural language search terms, the fault-tolerant search mechanisms, and the efficient retrieval capabilities of the vector engine. However, there are shortcomings, such as the accuracy of results generated by large models and insufficient comprehensive analysis of user search data. Future efforts will be devoted to improving these issues to increase the effectiveness of the research.

[Purpose/Significance] American university libraries have accumulated rich experience in strategic planning with their advanced concepts and practices. This article analyzes the content and development trends of strategic planning in American university libraries from two dimensions, and provides an in-depth understanding of the key elements and future directions of strategic planning in university libraries. In the relevant knowledge system, it provides a new reference perspective for Chinese university libraries. Compared with previous studies, this study provides a more systematic analysis of the content and development trends of strategic planning in American university libraries. It helps to promote in-depth research on strategic planning in the field of library science. By addressing important major practical issues, specific ideas and methods can be provided for the strategic planning of university libraries in China. [Method/Process] This article uses online surveys and content analysis methods. The online survey method can widely collect information related to the strategic planning of American university libraries, which is efficient and convenient; the content analysis method can deeply analyze the main content and development trends, which is relatively systematic and objective. This article is based on the relevant theories of library strategic planning and academic research achievements in libraries. Through online surveys, it obtains strategic planning texts and other materials published by major libraries, and analyzes the actual strategic plans of prominent university libraries in the United States as an basis for research and analysis. [Results/Conclusions] The research suggests that the key elements of strategic planning for prominent university libraries in the United States can be summarized as strengthening collaboration and sharing, promoting world-class collections and services, understanding internal and external environmental factors, improving management levels, and enhancing technical service support. The main trends of its strategic planning development are the trends of service development, collection development, organizational development, and cooperative development. Finally, considerations for the strategic planning of university libraries in China are proposed. Suggestions are put forward for Chinese university libraries to strengthen cooperation, optimize collections, and improve service levels. The limitation of this study lies in its limited scope and lack of in-depth case studies. In the future, the scope of the research can be extended to more countries, in-depth case studies can be conducted, dynamic changes in the implementation of strategic planning can be tracked, and the future direction of university libraries in combination with the development of new technologies can be explored.

[Purpose/Significance] In the context of digital rural development, farmers' digital literacy is greatly influenced by both intrinsic motivations and external influences. Cultivating digital literacy is of great significance in accelerating farmers' integration into the digital process, promoting the construction of digital villages, and facilitating the revitalization of rural talent. As an innovative mechanism for farmer education, the synergistic cultivation of farmers' digital literacy is poised to emerge as a critical research focus in the revitalization of rural talent. [Method/Process] Drawing from activity theory, the static components of this synergistic cultivation - consisting of the interrelated elements of goals, core aspects, and mediating factors - offer a nuanced perspective on the intricacies involved in enhancing farmers' digital literacy. The framework includes production, communication, sharing, and collaboration subsystems that together form a dynamic structure for cultivating farmers' digital literacy. By examining both static activity elements and dynamic operational systems, we conducted an in-depth analysis of the challenges encountered within each subsystem during collaborative cultivation efforts. [Results/Conclusions] We recommend the optimization strategies such as refining the use of tools, improving the regulatory framework, maximizing the potential for collaboration, and establishing sustainable mechanisms. The farmers' digital literacy collaborative cultivation activity model constructed in this paper is based on the background of digital rural construction and high-quality farmer cultivation. With the agricultural broadcasting school (center) as the core subject, it interacts and cooperates with other communities, and through the online digital platform and offline regular practice tools, it realizes the embedding of tool use, the improvement of the rule system, the long-term cooperation of activities, and the close participation and co-construction through the interaction and coordination of the four subsystems of production, sharing, communication and cooperation. It is closer to the digital scene requirements of farmers' cultivation. Moreover, few studies have applied activity theory to the cultivation activities of farmers' digital literacy, and analyzed the interaction and coordination process among elements from a dynamic and holistic perspective. The proposed framework for synergistically cultivating farmers' digital literacy not only provides detailed insights into educational practices, but also offers theoretical foundations for improving practical pathways in this area. The limitation of this article lies in the fact that the collaborative mechanisms and existing problems among the subsystems in the collaborative cultivation model of farmers' digital literacy have not been systematically sorted out. In response to the above limitations, continuous research based on the integration of different perspectives and methods will be conducted on the hot topic of cultivating farmers' digital literacy, which is "always in progress".

[Purpose/Significance] With the advancement of open science, the signing of transformative open access agreements will have a profound and long-term impact on the acquisition of library information resources. How libraries respond to this trend, how to evaluate open access conversion agreements, whether to sign reasonable open access conversion agreements, and actively adopt them suitable for China's domestic conditions, and scientific and effective collection acquisition and transformation strategies in an open publishing environment, how to ensure reasonable investment of institutional publishing funds, and how to play a role in promoting positive academic exchanges in an open scientific environment are all important issues that deserve industry attention and exploration. [Method/Process] We first reviewed the research progress on open access transformation at home and abroad. Second, based on the data statistics and analysis of DOAJ and related research reports and institutions, the relatiave concepts were elaborated, the impact on stakeholders was examined, and the trend of practical development was understood. Through the analysis and induction of practical cases in domestic and foreign university libraries, especially through the case analysis of the library of Shanghai Jiao Tong University, we elaborated on the issues that Chinese university libraries need to pay more attention to in the process of open access transformation, and proposes related strategies. [Results/Conclusions] To cope with the open access movement, on the one hand, we need to be vigilant against the emergence of new knowledge "barriers" and "paywalls" due to profit-driven, high APC, and transformative costs, as well as the lack of regulatory norms for author payments and the existence of financial risks and loopholes such as taxation. On the other hand, all parties adhere to the original intention of promoting the dissemination of academic knowledge, forming a transparent and reasonable APC price ecological market, establishing a hierarchical, reliable, and sustainable open publishing funding support, transformation, and regulation mechanism, and creating an economic and healthy academic information exchange environment. In this process, it is necessary for university libraries to comprehensively coordinate subscription fees and publishing fees, and fully guarantee and restructure knowledge exchange and information dissemination. This paper summarizes the three issues that need to be considered in the process of open access transformation, including the impact of open access on stakeholders, the phenomena that need to be monitored, and the key to ensuring sustainability. We proposed implementation strategies based on practical cases, including research and data preparation, analysis and evaluation, focusing on specific implementation points such as controlling elements of contract terms. The OA transformation is still in the transition period, and in order to avoid the loss of funds due to double payments, some overall management and guidance systems are needed during this period. For some publishers that prioritize commercial profit, it is necessary to send strong signals and strengthen supervision of APC pricing rationality through alliances and other levels. In addtion, we must strengthen China's leadership and discourse power in open science, and carry out the construction of related supporting systems.

[Purpose/Significance] Rural public digital cultural service is a new module of public cultural service, and the current relevant research mainly starts from two independent perspectives, namely external institutional structure and internal subjective action, and constructs the research paradigm of "system-behavior". However, this framework still has room for improvement in order to reveal the phenomenon of "technical alienation" in practice. "Technological alienation" is essentially a deviation from the value level, and the original framework is difficult to effectively reveal the influence of value on the impact of digital technology on rural public cultural services, so this study introduces the value factor to provide new theoretical perspectives and analytical frameworks for the existing research, in order to comprehensively reveal the underlying logic of "technological alienation" and to find the path of digital technology-enabled rural public cultural services. [Method/Process] Starting from the current situation of rural public digital cultural services, this study constructs a three-dimensional analysis framework of "value-institution-behavior" and applies the extended case study method to the case of Y Township in Zhejiang Province to explore the phenomenon of "technological alienation" of rural public digital cultural services, such as the de-domainization of public cultural service content, information risk aggregation, and "digital authoritarian" production, which is caused by the fragmented value, institutional imbalance, and unruly action. This "technological alienation" has seriously affected the effectiveness of public digital cultural services. [Results/Conclusions] According to the specific elements of the three-dimensional analysis framework of "values-institutions-behavior" alignment, combined with the extended case study method focusing on the study of macro-micro interactions, it is proposed that the people-centered value concept guides the goal of building rural public digital cultural services, a more complete institutional system protects the process of building rural public digital cultural services, and a more standardized subjective behavior shares the results of building rural public digital cultural services. Based on the above paths, the "technical alienation" of rural public digital cultural services will be abandoned. This study still has shortcomings in the use of research methods in this field, while the framework of "value-institution-behavior" has some explanatory power, but still differs from the complex reality of the society due to the lack of empirical material. In the future, we plan to increase the empirical research on rural public digital cultural services to verify the conclusions of this study and to further refine the measurement of the level of rural public digital cultural services.

[Purpose/Significance] Every transformation and development in scientific and technological (S&T) documentation and information services has revolved around the application of advanced information technologies. Currently, cutting-edge AI technologies such as large-scale models and agents are driving a new wave of paradigm shifts in scientific research. Information institutions should consider how the paradigm of S&T documentation and information services should evolve to lay a strategic foundation for the development of the "15th Five-Year Plan" development. [Method/Process] This study uses objective induction and theoretical reasoning methods. It starts with the three driving modes of AI empowering scientific research and combines them with the essence of information work. The study concludes and summarizes that AI empowers S&T documentation and information services in two main areas: information infrastructure (data production, information organization, and knowledge representation) and information generation (intelligence computation). Agents integrated with large-scale modelling technologies demonstrate exceptional, even scientist-level, data understanding capabilities, suggesting that they are already capable of enabling information generation. [Results/Conclusions] Building and deploying DIS agents is an inevitable choice for information institutions as they prepare for the "15th Five-Year Plan". Driven by DIS agents, S&T documentation and information services will achieve higher levels of automation and intelligence, freeing information professionals from tedious basic data processing tasks and allowing them to focus on generating high-value information and supporting decision making. In the ecosystem of S&T documentation and information services driven by DIS agents, clusters of agents form the core and work together both internally and externally: Internally, DIS agents achieve a high level of automation in four core functions: data production, information organization, knowledge representation, and intelligence computation through the integration of planning tools, basic data and infrastructure resources. Externally, through interactions between agents, information experts, and specific intelligence scenarios, a new working paradigm emerges: "human and multi-agent collaboration". In the future, when planning and designing the implementation of DIS agents, it is essential to focus on both the technical adaptability at the current R&D stage and the potential security risks in future application stages. This ensures the efficient and secure use of DIS agents in S&T documentation and information services.

[Purpose/Significance] A thorough understanding of algorithm aversion among social media users, encompassing its manifestations and underlying causes, is crucial in the algorithmic era. This understanding serves as the cornerstone for accurately capturing users' information needs and preferences, which are constantly evolving due to technological advances and changes in societal behaviors. By studying how users perceive, interact with, and respond to algorithmic recommendations and personalizations, researchers can gain insight into the effectiveness and limitations of current algorithmic technologies. These insights are invaluable for improving and optimizing algorithms to ensure that they not only meet user expectations, but also enhance their overall experience and satisfaction. Moreover, understanding algorithm aversion can help design more ethical and transparent algorithms, foster trust between users and technology, and ultimately promote the sustainable development of the digital economy. In addition, this research has broader implications for the fields of human-computer interaction, artificial intelligence, and social media studies. By exploring the psychological, social, and cultural factors that influence users' attitudes and behaviors towards algorithms, researchers can contribute to the development of more user-centered and socially responsible technologies. This, in turn, can lead to more inclusive and equitable digital environments, where everyone can benefit from the advances of technology. [Method/Process] This study employed a qualitative research approach, which is well suited for exploring complex and nuanced phenomena such as algorithm aversion among social media users. Qualitative research allows for the collection of rich, detailed, and contextually embedded data, enabling a deeper understanding of the subject matter. To accomplish this, the study included in-depth interviews with 26 respondents, who were selected for their active use of social media and their diverse experiences and perspectives on algorithmic recommendations and personalizations. The interviews were conducted using a semi-structured format that allowed for flexibility in the conversation while still addressing key research questions and themes. This approach allowed the researchers to gain detailed insights into the participants' attitudes, beliefs, and experiences with algorithms, as well as their perceptions of the consequences of algorithm aversion. A rigorous coding process was used to analyze the collected data. This involved breaking down the textual data into smaller, manageable units, or codes, which were then categorized and grouped based on common themes and patterns. The coding analysis focused on three main areas: the expression of algorithm aversion, the formation mechanisms of algorithm aversion, and the consequences of algorithm aversion for social media users. Drawing on qualitative research paradigms, the analysis resulted in the construction of a theoretical model analysis framework specifically tailored to algorithm aversion among social media users. This framework provides a structured way to understand the complex interplay between users' attitudes, beliefs, and behaviors towards algorithms, and the factors that influence these attitudes and behaviors. The framework also highlights key consequences of algorithm aversion, such as reduced trust in social media platforms, decreased engagement with algorithmic recommendations, and potential negative impacts on user experience and satisfaction. [Results/Conclusions] The results reveal three distinct forms of algorithm aversion among social media users: algorithmic interruption, algorithmic complaint, and algorithmic evasion. These forms have significant implications for individuals, organizations, and society. Additionally, the study identifies personal factors, algorithmic technology factors, and social environment factors as key drivers of algorithm aversion. A comprehensive framework for analyzing the formation mechanism of algorithm aversion, based on the concept of "individual-algorithm-social environment," is extracted. Based on this framework, the study proposes research paths and coping strategies from three perspectives: theoretical research, technical research, and humanistic research. These recommendations aim to effectively address and mitigate algorithm aversion among social media users.

[Purpose/Significance] In promoting red resources, libraries face problems such as "low reading rate of resources", "low public participation" and "low level of innovation in service". To some extent, these problems stem from the neglect of embodied cognition. The essence of embodied cognition is that cognitive process is not only the activity of the brain, but is inseparable from the perception and interaction of the body. Applying the theory of embodied cognition to reading can enhance the sense of immersion and participation in reading, thus optimizing the reading effect of red resources. This study explores the application and optimization path of VR technology in reading red resources from the perspective of embodied cognition. By enhancing users' immersive experience, it promotes their deep cognition and emotional resonance of red resources in order to promote the innovative utilization and efficient dissemination of red resources. [Method/Process] Taking the grounded theory as the research method, we first carry out data collection and sample selection, then analyze the text materials through the three-level coding method of open coding, axial coding and selective coding, and finally randomly select one third of the samples from the materials to carry out the saturation test of the theoretical model, summarize the three main categories of reading guarantee mechanism, reading ecology and reading experience optimization, and construct the optimization of the VR red resource reading path model, and elaborate the model in detail. [Results/Conclusions] It is found that reading guarantee mechanism, reading ecology and reading experience optimization have a positive effect on promoting the continuous optimization in reading VR red resources. Among them, reading guarantee mechanism plays a fundamental role, providing basic support for the whole VR red resource reading system. Reading ecology plays the role of a bridge, transforming the support of reading guarantee mechanism into the actual experience of users. The optimization of reading experience plays a goal-oriented role, and its realization depends on the results of the reading ecology practice, and through the feedback mechanism to promote the progress of the whole system. The interaction of these three main categories forms a dynamic feedback loop, ensuring that the VR red resource reading system can be continuously optimized with the development of technology and changes in user needs, and promoting the continuous innovation and optimization of VR red resource reading methods. This study relies mainly on secondary data and case studies, and lacks the actual feedback from users in real-life scenarios, especially the individual differences in user experience have not been fully explored. In future research, in-depth interviews will be introduced as a complementary means to further explore the individual experience of users in reading VR red resources, especially the specific application scenarios of embodied cognition theory.

[Purpose/Significance] As China's population ages, the health status and information accessibility of rural elderly groups have become the focus of public attention. This study aims to explore the factors influencing the online health information access behavior of the elderly in rural areas of western China, with the aim of improving the current situation of this group's access to information, increasing the efficiency of their access to health information, narrowing the digital divide, and providing references for promoting the "Healthy China 2030" strategy. [Method/Process] Thirteen rural villages in the Guanzhong region of Shaanxi province were selected as the research sites to collect primary data through face-to-face in-depth interview. Based on the grounded theory and three-level coding with the help of qualitative analysis software NVIVO, we constructed a model of factors influencing the access to health information among the rural elderly in western China by taking into account the three behavioral modes of health information search, health information encounter, and health information substitution search. [Results/ [Conclusions] The health information seeking behaviors of western rural elderly groups were influenced by information, personal factor, social factor and media. Among them, the cultural level, media literacy, and subjective perception of personal factors directly affect the demand for and access to health information by the elderly; medical concepts are more influenced by social factors. Social factors, such as family support, social networks, and the availability of local healthcare resources significantly influence how older adults access health information and its effectiveness. Content specificity and quality reliability of information factors are key factors that drive or hinder older adults' willingness to access online health information. The media, as an external context, plays a mediating role in older adults' active or passive access to health information, with short video platforms and social media in particular becoming important channels. In addition, the study found that the roles of health information acquisition among the rural elderly could be categorized into passive recipients, limited participants and active searchers of health information, and based on this, a three-dimensional "R-P-S" model was constructed to describe the online health information acquisition status of the rural elderly. This model represents the developmental trajectory of this group's online health information access status, and as health information literacy improves, individuals may move from one stage to another more mature stage. Finally, interventions for different roles in health information access are proposed to better meet the health information needs of the rural elderly population.

[Purpose/Significance] Sentiment analysis technology is an important part of the natural language process and plays a key role in modern smart systems. As smart libraries continue to develop, traditional service models focused only on functionality are no longer enough to meet users' diverse and personalized needs. In the digital transformation era, smart libraries need new technologies to improve service quality, and adding sentiment awareness has become a key way to move beyond traditional approaches. This study uses ChatGPT(Chat Generative Pre-trained Transformer) to apply sentiment analysis in smart library services. This goal is to create a new service model based on emotions, helping smart libraries shift from basic information management to services that focus on emotional care and better user experiences. This approach not only helps smart libraries handle the challenges of digital transformation but also offers a fresh way to meet users' emotional needs. [Method/Process] This study reviews relevant literature from both domestic and international sources, systematically analyzing the mainstream research methods and technological trends in the field of smart libraries. It also explores the adaptability and feasibility of sentiment analysis technology in smart libraries, based on current practical scenarios. The research uses ChatGPT's sentiment analysis as the technological foundation, combined with the theory of smart library service models, leveraging the advantages of the ChatGPT to create an analysis framework that integrates theory and practice. At the same time, the study draws on successful cases and practical experiences from domestic and international smart libraries, such as intelligent recommendation systems and contextual knowledge services, extracting effective application paths for sentiment perception technology. This approach provides strong theoretical and practical support for the applicability of the research methods, ensuring the scientific, logical, and innovative nature of the study, and effectively contributing to the optimization of smart library services. [Results/Conclusions] ChatGPT's sentiment analysis capabilities have the potential to significantly enhance both the service quality and user experience in smart libraries. Personalized recommendations and context-aware services can effectively meet the diverse needs of library users. However, the application and research in this area are still in their infancy in China, and there are ongoing challenges in technology adaptation and practical implementation. Particularly, the difficulties in promoting the technology, user adaptability, and issues related to funding have hindered the implementation and widespread adoption of smart library services. To promote the further development of smart libraries, greater efforts should be made to deepen the integration of ChatGPT technology and explore its potential to meet the evolving demands for library services in the digital era. Additionally, the research proposes strategies to address these challenges, such as enhancing technology adaption and user education, exploring diversified funding support options, and continuously innovating application pathways. Through these explorations, smart libraries will better adapt to the needs of the new era and provide more personalized, context-aware services.