[Purpose/Significance] Reading promotion has been a basic and normalized activity in libraries, and has been carried out for many years. Although it has achieved remarkable results in promoting the dissemination of knowledge and culture, it has reached a developmental bottleneck that urgently requires innovative breakthroughs. The introduction and application of artificial intelligence generated content (AIGC) technology can innovate the content and form of the library work, and promote the connotative development of library services. Currently, there is limited research on the application of AIGC in library reading promotion, with most studies focusing on theoretical discussions of work scenarios rather than practical applications. The aim of this article is to explore new technology applications in new scenarios to help solve common problems in the field. [Method/Process] Through literature research and case analysis, based on the characteristics of AIGC content, we look forward to AIGC empowering library reading promotion scenarios, including inspiring activity creativity, and enriching work forms; creating reading IP, and forming work brands; promoting in-depth and professional reading, and optimizing work content; strengthening service management, and promoting the construction of work evaluation standards. Taking the "New Book Recommendation" activity as an example, we analyze work application elements such as planning, promotion, organization, and evaluation, and construct a work model suitable for the scenario. [Results/Conclusions] Although AIGC has great potential and broad prospects for application in library reading promotion, it faces many application challenges, such as the need for a change in librarians' work mindset, issues of data privacy and ethics, and the quality and accuracy of generated content. This paper discusses the application paths of AIGC in library reading promotion, including strengthening skills training to comprehensively enhance librarians' new literacy in the AI era; exploiting the role of "AI prompter" to deepen reading services; building a rich database of event data corpora to ensure digital content generation; and improving rules for content review and quality control. Compared to other information resource management tasks, such as reference consulting and academic services, the impact of AIGC is relatively mild. AIGC is applied as a tool for reading promotion, with librarians remaining the primary actors, and the implementation of work elements is still carried out within the existing work framework. The discussion of AIGC applications in library reading promotion practice in this paper offers methodological insights for library reading promotion, with scenario elaboration, model construction, and path generation facilitating the realization and broad application of these related services. The limitation of this study, however, is the lack of concrete data on the effectiveness of the work discussed, which requires further research.

[Purpose/Significance] Research on the governance system and policy of data elements circulation is an important issue to be solved in the field of data governance in China at present, and research on the policy formulation and governance system of its circulation plays an important role in grasping the security of data circulation in China and promoting the market-oriented allocation of data elements. [Method/Process] First, this study is based on the reality of China's data factor market security and trustworthy, autonomous and controllable requirements. Based on the analysis of the security risk of data circulation, we put forward the data factor market risk governance countermeasures of the "security-fairness-efficiency" triangular structure. Then, based on the three-level system and five-dimensional standards of data factor market governance, we put forward the method of docking the security governance with the trusted ecosystem and the international data governance rule system for cross-border data flow, and constructed a governance system with Chinese characteristics for the national unified data factor market. [Results/Conclusions] Facing the security risks in data sovereignty, data market and data circulation, we should identify and monitor data sovereignty disputes and the operation situation of the circulation market, and establish a multi-party cooperative and joint governance model led by the government, operated by the platform owner, the main body of the enterprise and the participation of users. When assessing the market for data elements, a mixed assessment approach should be adopted, combining qualitative and quantitative aspects, combining expert opinion with objective data, and comparing objectives with results. For different types of data, the control boundaries and scope of use should be clarified in a hierarchical manner, and data ownership, use and income should be clarified; at the same time, a confirmation platform of data rights should be established to audit and register and certify the data service subject, data circulation process, and data circulation rules so as to ensure that the normative nature of data circulation is maintained.

[Purpose/Significance] Generative artificial intelligence (AI) technology has been widely used in many fields, and the application of this technology has become popular among researchers. However, there are few studies on the willingness of researchers willingness to accept generative AI. This leads to an insufficient understanding of the psychological mechanism, cognitive process and behavioral pattern of users' acceptance of generative AI, which limits the ability of theoretical innovation and practical exploration in user information behavior. This study focuses on researchers acceptance of generative AI. By studying the evaluation process of ChatGPT by college students, it explores the acceptance behavior of generative AI. At the same time, it verifies the applicability of the AIDUA model in the new context, and introduces the new variable of school identity, which further extends the AIDUA model. [Method/Process] Based on the cognitive assessment theory and the AI acceptance framework (AIDUA), this paper constructs a theoretical model of the intention to use generative artificial intelligence, and develops and empirically tests the theoretical model of the intention to use generative AI. Taking college students as the main research object, based on the maturity scale in authoritative literature at home and abroad, 8 variables and 29 observation variables such as social influence, hedonic motivation and anthropomorphism were designed. College students with experience in using generative AI were invited to participate in the questionnaire survey. SPSS26.0 was used to analyze the data from 294 valid questionnaires collected. SmartPLS 3.2.9 was used to construct a structural equation model to test the hypothesis, and the JN method was used to detect the regulatory effect. [Results/Conclusions] The study found that users went through three stages of decision making before using generative AI. The PLS-SEM results show that: 1) Social influence, hedonic motivation and anthropomorphism significantly affect performance expectancy and effort expectancy, and anthropomorphism is the strongest variable affecting performance expectancy and effort expectancy. 2) Performance expectancy and effort expectancy are significantly negatively correlated with negative emotions, while hedonic motivation has no significant effect on negative emotions. 3) Negative emotions are significantly negatively correlated with users' intension to use. 4) School identity moderates the relationship between effort expectancy and negative emotions. This study combines anthropomorphic research on college students' acceptance of generative AI, and provides a framework for the acceptance of generative AI. Researchers can use this framework to better study the acceptance of AI. This study has some limitations. In the future, we will focus on the following three aspects: 1) to evaluate the users' acceptance of generative AI in different usage scenarios. 2) to use samples of other groups to test the applicability of the model, such as civil servants, librarians, researchers and other groups. 3) to incorporate variables from other technology acceptance models into the model, such as ease of use and practicality.

[Purpose/Significance] In recent years, the rapid development of artificial intelligence (AI) technology has become an international research hotspot. Embedding ChatGPT-like AI system in libraries will lead to a new direction for the development of their intelligent services, which is a necessary choice to improve the library service level, optimize service efficiency and promote service model innovation. It is also an important measure to adapt to the development trend of the information age, which brings new opportunities and challenges to the information and digital construction of libraries. This article aims to explore the realization path of ChatGPT to help libraries provide intelligent services, provide theoretical reference and practical basis for the intelligent service by libraries, and promote the construction of library intelligent service system. [Method/Process] By reviewing the relevant literature at home and abroad, on the basis of summarizing the core technology of ChatGPT, and studying the practical application cases of some domestic libraries, this article analyzes the application scenarios and directions in which ChatGPT can support library services, explains the current limitations of this technology and the threats and challenges it poses to libraries and librarians, and thus proposes corresponding strategies. [Results/Conclusions] ChatGPT technology will further optimize the knowledge service system of libraries and improve the intelligent service capability of libraries. It brings vitality to the libraries, but also brings threats and challenges. Librarians should grasp the integration capabilities of humans and AI in time, and make full use of their unique advantages. Libraries should strengthen the capacity building of their smart services oriented to ChatGPT, innovate the mode and mechanism of their smart services, and rely on ChatGPT to build a smart service platform, provide smart service resources, build a sound service system, build a service team, and improve the level of their smart services. Continuous efforts should be made to promote the in-depth development of smart library services, so as to meet the diversified and personalized information needs of library readers. To this end, this paper makes a preliminary exploration on the opportunities, challenges and development strategies of enabling smart services in libraries through ChatGPT. Due to the limited conditions, only some practices of domestic libraries are explored, and no cases of international libraries are introduced, which has certain limitations and needs to be improved in future studies.

[Purpose/Significance] The advent and emergence of social robots represent a closer development trend in human-computer interaction. However, the study of the information behavior of social robots faces many challenges that arise from the need to simulate human social behavior. This challenge includes technical hurdles such as a multi-level understanding of human emotions, extraction of multi-modal information features, situational awareness, as well as the establishment of long-term user profiling, data privacy, and ethical considerations in personalized interaction. However, existing research tends to focus narrowly on specific applications and lacks a holistic review. This paper attempts to provide a thorough review of both domestic and international studies of social robots in the area of information behavior. It aims to elucidate the theoretical evolution and technological foundations of social robots, thereby enriching our understanding of their role in the landscape of information behavior research. [Method/Process] Using a rigorous literature review methodology, we meticulously analyze the current state and prospective trajectory of research on the information behavior of social robots. First, we extract and scrutinize the theoretical foundations and salient research topics within the field. We then delineate the core tasks of social robots, which include data acquisition, language processing, emotion analysis, information retrieval, and intelligent communication. Furthermore, we synthesize research on the information behavior of social robots in various application domains such as education, healthcare, and service sectors. We delve into the intricacies of human-computer interaction in these contexts and provide comprehensive insights. Finally, we explore future directions in the field. [Results/Conclusions] Our examination of the information behavior of social robots reveals both promising potential and notable challenges. This paper provides a fundamental elucidation of the social robot concept, identifies current research foci, and addresses prevailing challenges. Regarding the construction of data resource and related technologies, we systematically delineate the task architecture of social robots, and highlight their wide-ranging applications in various domains. Furthermore, we provide an in-depth examination of human-computer interaction scenarios in critical domains such as education, healthcare, and service delivery, offering prescient guidance for future research efforts in social robotics. Nonetheless, our findings underscore the nascent stage of development of social robotics, which requires a concerted focus on advancing interaction quality assessment, enhancing social cognitive capabilities, managing user information disclosure, and refining emotional intelligence. By prioritizing these avenues, we aim to improve the quality of human-robot interaction and provide users with enriched and personalized service experiences, thereby catalyzing the continued evolution and broader integration of social robotics technology.

[Purpose/Significance] New quality productive forces is the latest pattern of productivity development under the background of data-driven intelligence. To explore the mechanism and practical way of bidirectional empowerment of knowledge service and new quality productive forces has important theoretical and practical significance for giving full play to the effectiveness of new quality of data elements, new power of digital intelligence technology and new application of intelligent service, so as to promote the cultivation of new quality productive forces and improve knowledge service. [Method/Process] Based on the summary of the development process of knowledge service and the new interpretation from the perspective of new quality productive forces, this study analyzes the internal relationship and external manifestations of the bidirectional empowerment of knowledge services and new quality productive forces, constructs the bidirectional empowerment mechanism of knowledge services and new quality productive forces, and proposes the bidirectional empowerment path. [Results/Conclusions] "Factor reorganization, scientific and technological innovation, and quality service" has become the internal relationship between knowledge service and new quality productive forces. Data factor as the core production factor, digital intelligence technology as the key production technology, and intelligence-driven new business forms and new models as the common carrier, which is an important basis for intelligent knowledge service and new quality productive forces bidirectional empowerment mechanism. Intelligent knowledge service cultivates the new quality productive forces through three important ways: accelerating scientific and technological innovation, opening up new ways and creating new business forms. New quality productive forces drives the development of intelligent knowledge service and improves the service by solving the resource dilemma, technology dilemma and talent dilemma, and creating new competitive advantages. This is an important manifestation of the bidirectional empowerment mechanism of new quality productive forces and intelligent knowledge service. After clarifying the empowerment basis and the performance of the bidirectional empowerment mechanism, this study proposes that the two kinds of empowerment should be realized from the following four aspects: a) Taking the market demand as the guide by mining new value and responding to new demand, and grasping the new quality growth engine; b) Taking data elements as the center, the compacting intelligent driving base is realized by building the data element empowerment system and improving the standardization of element utilization; c) Taking technological innovation as the key way by releasing the potential of key elements and creating fusion application scenarios to consolidate the foundation of fusion application; d) Starting from the application scenario as the starting point, the bidirectional empowerment mechanism is put into practice in various fields.

[Purpose/Significance] The development of the Internet has led to the rapid development of social networks, providing users with a convenient channel for the release, dissemination and acceptance of information. However, its low-threshold characteristics have also given rise to a group of the "Internet water army"--online social spammers, who are paid to post online comments with particular content and spread false information on purpose. They have become a major problem for the Internet ecology. It is of great significance to detect the Internet water army, prevent their malicious attacks, and combat and eliminate their negative effects on the security of the online public opinion. [Method/Process] First, we analyzed the development process and characteristics of the online social spammers, summarized the algorithms used in previous studies and the characteristics mentioned, and sorted out three research starting points: text features, interaction features and graph structure features. Then, an online social spammer detection method based on deep learning was proposed. Combined with the three aspects of user basic information, historical remarks and interaction behavior, six types of features were extracted from the basic information, recent remarks, social intimacy, interaction behavior, microblog number and membership level. Through feature depth extraction and vector splicing and fusion, the user feature vectors were formed with the same length. Finally, a convolutional neural network was used as a classifier to build an automatic, high-precision and high-efficiency spammer detection model. Two Chinese online spammer datasets collected from the Sina Weibo platform were selected for the experiment. The features of the datasets were spliced and aligned to form the Weibo Spammer 2023 dataset as the model training dataset, which prevented the data features of a single dataset from being too discrete and reducing modle generalization. Considering the overfitting problem in the model training process, we solved the problem by adding abandoned layers. [Results/Conclusions] The online spammer detection model constructed in this experiment has significantly improved in terms of metrics such as precision and accuracy. At the same time, the ablation experiment shows that the six features extracted in this experiment have a positive effect on the detection process. Through empirical analysis, the model constructed in this paper has a high detection accuracy and detection efficiency, which can provide certain technical support and theoretical guidance for online spammer identification. By using machine learning methods to actively identify online social spammer accounts, real-time monitoring and prevention of key spammer accounts can prevent the occurrence of malicious network events more timely and effectively and reduce the risk of illegal forces damaging the public opinion ecology.

[Purpose/Significance] This article is aimed to explore the impact of artificial intelligence generation technologies such as large language models (LLMs) on users' information retrieval behavior and to suggest ideas for information retrieval systems and information resource construction. In this way, it provides insights into and references for the future establishment of the artificial intelligence generated content (AIGC) information platform with Chinese characteristics as well as the information literacy education system. [Method/Process] In the field of library intelligence, with the wide application of AI technology in information service work, LLMs represented by ChatGPT have also become a hot topic of discussion. Taking the booming development of LLMs such as ChatGPT as background, we analyzed the impact of the increasing popularity of this technology on information retrieval systems and user retrieval behavior from the perspective of user information behavior by combining the technical features of LLMs with the characteristics of existing products. Literature survey and empirical analysis were used. [Results/Conclusions] The use of LLMs as information retrieval systems has unparalleled advantages over traditional products. These advantages include the ability to understand and process natural language queries, generate relevant and context-specific responses, and interact with users in a more human-like way. The application of LLMs in information retrieval systems has the potential to transform the way users search for information, influence the underlying logic, action priorities, and retrieval expectations of user information retrieval behavior. However, the existing shortcomings of LLMs in terms of reliability and accuracy still make it difficult for them to replace traditional information retrieval methods immediately. Language models may not always provide accurate and reliable answers, especially when dealing with complex or domain-specific queries. Additionally, LLMs may struggle to understand and process contextual information effectively, leading to limitations in their ability to extract relevant and context-aware insights. It is recommended to pay attention to this technology in the construction of information retrieval systems and information resources, and to explore the combination of LLMs and information services in order to cope with the changes in future user information needs and to further make full use of the value of existing information resources. Limited by the lack of expertise in the field of AI and the fact that LLMs are not yet widely used in practice in China, the research findings are only a reflection and exploration of the impact of LLMs on users' information behavior.

[Purpose/Significance] In recent years, the national leadership has attached great importance to the inheritance and innovation of China's excellent traditional culture, and the concepts of creative transformation and innovative development are constantly evolving. The Ministry of Science and Technology of China, among six departments, jointly formulated the "Guidelines for Promoting the Deep Integration of Culture and Technology", proposing to form a "cultural and technological integration innovation system covering key areas and critical links, to achieve the goal of in-depth integration of culture and technology". Intangible cultural heritage (ICH), as an essential part of China's excellent traditional culture, plays a crucial role in consolidating the sense of the Chinese national community and enhancing cultural self-confidence. This paper discusses the research paths for the creative transformation and innovative development of ICH in the context of culture and technology integration, emphasizing the significant role of modern technology in promoting the transformation and development of ICH. [Method/Process] The paper first interprets the connotation of "creative transformation and innovative development" in ICH, and clarifies the theoretical foundation and guiding principles of "creative transformation and innovative development" in ICH. It then analyzes the significant contributions of "creative transformation and innovative development" in ICH to society, economy, and cultural diversity, as well as the categorized scenarios of technology empowerment in "creative transformation and innovative development" of ICH. It discusses six types of common key technologies that enable technology-driven "creative transformation and innovative development" in ICH, including digital technology, virtual and augmented reality, big data analysis, artificial intelligence, cloud computing, and the Internet of Things. It summarizes a three-tier framework system for technology-driven "creative transformation and innovative development" in ICH, namely the method layer, technology layer, and object layer, forming a progressive relationship from theory to technology and then to specific practices. Finally, by integrating the specific example of the traditional craft of Wuhu iron painting, it demonstrates the facilitating role of modern technology in the "creative transformation and innovative development" of ICH and its impact on the protection, inheritance, and innovative development of ICH. [Results/Conclusions] The findings suggest that technological means can effectively protect and inherit ICH, facilitating its creative transformation and innovative development. However, it also requires careful consideration and precautions against the potential risks and challenges that modern technology poses to ICH projects in terms of intellectual property rights, the digital divide, and the indirect nature of experiences. Looking to the future, with the emergence of more innovative technologies, modern technology will not only help to protect and pass on traditional culture but also give new connotations and expressions to traditional culture, ensuring that its unique value and charm continue to play out in an ever-changing world.

The scientific connotation, strategic considerations and practical ways of "new quality productive forces" have received wide attention from the political, academic and industrial circles. Cultivating and developing new quality productive forces means fundamentally changing the mode of production. It is necessary to grasp the practical direction of new quality productive forces from their scientific connotation and internal logic, and explore the scientific way of cultivating and developing the new quality productive forces from China's national conditions. As an important engine of economic development in the new era, its connotation characteristics, development path, opportunities and challenges are worthy of further discussion. For this reason, seven experts were invited to share their perspectives. 1) The deep logic and realization path of the construction of new quality productive forces and high-quality data resources. This paper discusses in depth the background and connotation characteristics of the high-quality data resources, and analyzes the internal logic of the mutual promotion between high-quality data resources and the development of new quality productivity. It is proposed that the construction of high-quality data resources must implement the concepts of innovation, coordination, openness, credibility and sustainability, and follow the construction strategies of concept innovation, model innovation, structural innovation and technological innovation. 2) The theoretical logic and practical path of data elements empowering new quality productive forces. In the new era of green and intelligent development, there is a profound dialectical relationship between data elements and new quality productive forces, and a new situation of economic and social development is accelerated in the spiral ascent of complementarity. We should comprehensively build a data space governance model with clear data ownership, smooth data path, guaranteed data quality and orderly and standardized algorithm computing power, expand new quality production capacity and production factors with the goal of human-machine cooperation and promote sustainable economic and social development. 3) Accelerating the promotion of data rights. Data can act on new quality productive forces from the technical, factor and industrial dimensions, and accelerate the formation of new quality productive forces. The multiplier effect of data elements on new quality productive forces will involve many dimensions, levels and stages, the most important and fundamental of which is how to determine the ownership of data. The measures for speeding up the promotion of new quality productive forces are discussed, such as constructing the theory of property rights in accordance with the characteristics of data and the law of development of new quality productive forces, speeding up the clarification of the types and scope of data confirmation, and improving the supporting system of data confirmation. 4) Promoting China's modernization path with Chinese-style digitization. Accelerating the promotion of Chinese-style digitization is not only the only way to realize Chinese-style modernization, but also the core to fully release new quality productive forces and build China's asymmetric competitive advantage under the new situation. It is suggested that in the process of digitalization and informatization in China, the information resource management industry plays a vital role and bears the important responsibility of digital transformation. 5) Interpreting the mission of public libraries from the perspective of new quality productive forces. Since its establishment, public libraries have been based on the concept of enlightenment. Faced with the profound digital transformation of society, today's public libraries need to further develop the potential of empowering the people in the field of digital economy and make them play an active role in the development of new quality productive forces. Public libraries need to further develop their potential to empower people in the field of digital economy, so that they can play an active role in the development of new quality productive forces. They should actively participate in data commercialization, promote the effective use of data elements and the efficiency of resource allocation, and enable more people to obtain and use data elements equally through open access and digital services. 6) The intelligent transformation of university libraries from the perspective of new quality productive forces. In the process of developing new quality productive forces, we should fully understand the profound meaning of new productive forces, based on the core tasks of providing a strong guarantee for the development of new quality productive forces in higher education, grasp the development opportunities, and realize the high-quality development of the industry. This paper explains the understanding of university libraries on the three key words of new quality productive forces, and proposes that the re-understanding and realization of library intelligence is an important starting point for the development of new productive forces. 7) To support information resource management discipline to accelerate the development of new quality productive forces. From the perspective of information resource management discipline, this paper analyzes several aspects of "doing something" under the rise of new quality productivity concept, including theoretical system, information resource guarantee, information analysis and consultation, scenario building, knowledge popularization and civic literacy cultivation. The content of academic evaluation, information policy, intellectual property rights, digital consumption behavior and other directions related to new quality productivity are also important directions that the discipline needs to pay attention to.

[Purpose/Significance] With the development of artificial intelligence (AI) technology, the teaching innovation in higher education driven by digital intelligence technology has gradually gained attention. ChatGPT has brought new opportunities and challenges to the development of higher education and the reconstruction of educational ecology. The purpose of this study is to apply ChatGPT tools to the process of information literacy (IL) education in colleges, so as to create a human-machine collaborative teaching paradigm of IL education in colleges based on ChatGPT applications, promote the innovative reform and improve the teaching efficiency of IL education in colleges and provide reference for the application research of AI tools in the field of higher education in the era of digital intelligence and the development of high-quality IL ducation in colleges. [Method/Process] By combing the relevant literature, on the basis of summarizing the global educational application situation of ChatGPT and revealing the educational theory of ChatGPT, combined with the current teaching problems of IL education in colleges, this paper comprehensively analyzes the application scenarios of ChatGPT in the process of IL education in colleges from the perspective of teachers' teaching and students' learning. At the same time, the study carries out practical teaching comparison, and examines the satisfaction of teachers and students by means of "interview + questionnaire", so as to test the application effect of ChatGPT, summarize the problems in teaching and put forward improvement strategies for teaching. [Results/Conclusions] ChatGPT can effectively promote the innovation of IL education in colleges and improve the teaching efficiency of courses. Teachers and students also give good feedback on the educational application of ChatGPT. The application of ChatGPT can effectively improve teaching efficiency, innovate teaching content, optimize teaching process, improve teaching management, and provide students with more learning options, enhance learning initiative, promote higher-order thinking and scientific research innovation. At the same time, the educational use of ChatGPT will also lead to many problems, such as tool abuse, knowledge misleading, information security, and intellectual property rights. Therefore, we should look at the teaching use of ChatGPT dialectically. On the one hand, we should actively promote and apply ChatGPT; on the other hand, we should also pay attention to the different risks that ChatGPT may cause, and formulate forward-looking instructional management policies and guidelines to standardize the use of ChatGPT, so as to give full play to the educational function of ChatGPT and further promote the reform of IL education and teaching in colleges.

[Purpose/Significance] Identifying key core technologies helps to clarify the direction of future efforts, optimize the allocation of innovation resources, accelerate the breakthrough of key core technologies, and promote the development of new quality productive forces by cultivating new types of workers, updating new types of means of labor, and expanding new types of subjects of labor. [Method/Process] Given the importance of key core technology identification in empowering the development of new quality productive forces, the research clarifies the connotation and extension of the key core technologies, and investigates the qualitative and quantitative identification methods of key core technologies at home and abroad. Quantitative methods are divided into three categories: indicator evaluation, social network analysis, and text mining. A comparative analysis of the advantages and disadvantages of each method are reviewed, and the overall shortcomings and problems of existing identification methods are summarized. Based on the analysis of the practical requirements and significance of breakthroughs in key core technologies, this study delves into the inherent logic of identifying key core technologies, which enables the development of new quality productive forces. The method of identifying key core technologies can cultivate new types of workers by improving talent management mechanisms and strengthening skills training for workers, New types of means of labor are updated through promoting technological integration and innovation and engaging in industry-academia-research cooperation and expanding new types of objects of labor by developing new production fields and analyzing market demand. In view of the challenges faced in the process of empowering new quality productive forces through the identification of key core technologies, this study proposes a practical way for empowering the development of new quality productive forces through the identification of key core technologies. [Results/Conclusions] Current research on identifying key core technologies is in its early stages and still faces several challenges, including outdated identification methods, inconsistent standards, the complexity of integrating technologies across disciplines, the need for improving accuracy of identification results, the lack of mining and using of multi-source data, and uncertainties in forecasting market demand. These obstacles hinder the process of using key core technology identification to cultivate new types of workers, update new types of means of labor, and expand new types of objects of labor, thus hindering the accelerated development of new quaity productive forces. Therefore, we need to focus on removing the obstacles that hinder the acceleration of new quality productive forces through the identification of key core technologies. A dynamic identification indicator system can be established to support the training of new types of workers, industry-academia-research cooperation can be strengthened to facilitate the updating of new production materials, and industrial development funds can be established to support the expansion of new types of objects of labor.

[Purpose/Significance] Talent data have become the most important production factor and strategic resource. Building a scientific and technological (S&T) talent database has become an inevitable way to narrow the digital divide and accelerate the digital and intelligent transformation of talent work. Therefore, this study builds an S&T talent database to promote scientific decision-making for talent development, precision in attracting new quality technical talent, reform in evaluating S&T talents, and building talent system for new quality productive forces. [Method/Process] By analyzing the practical requirements and significance of building an S&T talent database, this study first explores and analyzes the intrinsic logic of promoting the development of new quality productive forces through an S&T talent database. It then summarizes the challenges facing the current construction of a S&T talent database, including the scattering and concealment of S&T talent data, the lack of policies and standardized systems for S&T talent data, the inadequate exploration of value-added S&T talent data, the need to expand the application of digital technology in talent work, and the security risks of S&T talent data. In response to these challenges, this paper finally proposes the idea of building an S&T talents database, and introduces the research exploration and application practice on it, including the construction of big data database for S&T talent aimed at the development of new quality productive forces, the development of AI-powered talent data computing engine, research into the system for profiling new quality technical talent, the analysis of talent growth paths for the training of new quality technical talent, the identification method of new quality talented professionals based on big data, the development of an efficient digital platform for talent management, and the development of a strategic analysis platform for technical talent. [Results/Conclusions] The construction of S&T talent database is an objective requirement for the development of the digital era and an inevitable requirement for the formation of new quality productive forces. Building big data for S&T talent, empowering talent workflow with big data and artificial intelligence technology can help empower talent workflow, release the enormous energy contained in digitalization, effectively activate the internal momentum of talented professionals, institutions, society, and government, and then continuously improve the efficiency of talent resource allocation, the operational efficiency of talent work, the overall effectiveness of talent development governance, and promote the development of new quality productive forces.

[Purpose/Significance] With the rapid development of communication technology, the number of Internet users has increased rapidly, and the public opinion on the Internet has also developed according to the requirements of the times. Aiming at the online public opinion of public emergencies under the influence of emotional factors and the government's response strategies, a tripartite game model of netizens, online media and the government is constructed, and its development trend and the influence of emotional factors are simulated and analyzed. [Method/Process] This paper introduces the theory of hierarchical expected utility (RDEU), establishes a tripartite game model of netizens, online media and the government by using the replication dynamic equation, analyzes the influence of emotional factors on the behavioral decision-making of the main body and the development trend of public opinion of the three parties under the influence of different emotional states. Finally, through Matlab software simulation, the influence of emotional state on decision-making is analyzed, and the strategies and suggestions are proposed from the perspective of the government. Hierarchical expected utility theory (RDEU) is introduced to establish a tripartite evolutionary game model, the influence of emotional factors on the agent's behavior decision-making and the development trend of public opinion under the influence of different emotional states are analyzed, and the influence of emotional states on the agent's decision-making is also analyzed. [Results/Conclusions] Under the influence of emotional factors, different combinations of emotional states of each subject produce different results, and all three parties adopt different strategies according to the actual benefits, and the government's own emotions have the most obvious impact on the results of the evolutionary game. When the government has no mood or is in an optimistic mood, the online environment is relatively unstable, and it is necessary to strengthen the management of public opinion; when the government is in a pessimistic mood, the government needs to actively supervise and control public opinion so that public opinion will be well managed, and the network environment will be more harmonious. By analyzing the behavioral strategies of the tripartite game under the influence of emotional factors, the following suggestions are made on the management of public opinion from the government's perspective: 1) The government must always pay attention to the emotions of netizens, try to reduce the participation rate of netizens in online public opinion, strengthen education and improve the quality of netizens. 2) The government should reduce the dissemination of public opinion events by online media, encourage online media to report comprehensively and objectively, and avoid false information that causes negative emotions of the online public opinion.

[Purpose/Significance] Data empowerment for collaborative transformation of the entire industrial chain has become a national strategy. In the context of multi-source and heterogeneous big data, we face higher demands on the diversity and real-time of recommendation services, as well as the standardization and comprehensiveness of user and item information management, in order to turn data into resources, support the diversification of smart recommendation services, and enhance the user interaction experience. To this end, we should systematically sort out and analyze the research results of user interest modeling and item information management technologies in China's big data empowerment, elaborate the technical system for standardized management of user and item information in intelligent recommendation. [Method/Process] The article summarizes the content of 507 documents using literature review methods, and summarizes and analyzes the domestic big data empowerment resource management technology for smart recommendation from two aspects: user interest modeling and item information management. User interest modeling technology includes model representation, model initialization and model evolution, the item information management technology shows the goals, implementation methods, implementation techniques, and methods of item information management, including data collection, data mining, data storage, data updating, and data interpretation. [Results/Conclusions] First, the user interest modeling technology of big data empowerment mainly studies the following issues. 1) The method of model representation is to accurately formalize the user's needs. 2) The model is initialized to collect user information in an implicit or explicit way and select tools and technologies according to data types to pre-process user data according to a fixed process, and select measurement methods to quantify user interest. 3) Model evolution aims to apply methods and technologies to evolve user interest models offline and online. Second, the item information management technology of big data empowerment mainly studies the following issues. 1) The online technology and offline equipment are used to synchronously collect item data across the whole domain, integrate domain knowledge, and use algorithm libraries and data analysis methods to mine item data. 2) The distributed storage is used such as databases and file systems to store item data. 3) Data collection, mining, and storage technologies are the main techniques, item data are updated through offline and online methods, and visualization technology is used to intuitively interpret ietm data. Finally, existing research needs to strengthen the design and practical research of user-driven and data-driven smart recommendation solutions, as well as strengthen research on data security.

[Purpose/Significance] With the rapid development of new media technology, social media platform has become the main carrier of information dissemination. Social network analysis (SNA) is used to study the information dissemination structure and mode of emergencies in microblog, which provides theoretical support for the government to effectively deal with emergencies and crises. [Methods/Process] Taking "Tangshan barbecue restaurant beating incident" as an example, Weibo data were collected to build an information dissemination network with strength relationship between nodes. Social network analysis has been used to analyze the user attributes, node attributes, network attributes and dissemination attributes of the information dissemination network, in order to explore the role of the strength relationship between nodes in emergency information transmission. [Results/Conclusions] 1) The factors of user gender, activity, and region affect their dissemination power. In particular, female users, users with high activity or influence and those in developed provinces have a stronger power of information transmission. 2) The core nodes that plays the role of "bridge" in the dissemination chain is particularly critical. Nodes with strong relationships generally occupy central positions in the information dissemination network and may mainly consist of opinion leaders and mainstream media with greater influence. The pathways of weak and authority relationships are mainly concentrated around a few core nodes, while the pathways of strong relationships are dispersed. 3) Emergency information transmission network has high efficiency and sparse characteristics. 4) The whole process of information transmission is still dominated by weak relationships. Authority relations play an important role in all stages of information transmission, while the role of strong relationships is mainly concentrated in the initial stage. The results of this paper help to deepen the understanding of the patterns and rules of emergency information dissemination, and provide some insights for more effective management and guidance of emergency information dissemination in a particular field such as agriculture. However, our research still has shortcomings, such as insufficient crawling of user attributes and insufficient research methods. In the future study, we will obtain more abundant characteristics of users involved in the dissemination such as age, occupation and education level through interviews or questionnaires, and introduce new methods such as machine learning and graph neural network to predict and analyze the transmission path and node relationship of emergency information, so as to cover these shortcomings, improve the comprehensiveness and effectiveness of the study and deeply explore the information dissemination rules of emergencies.

[Purpose/Significance] With the development of the Internet and the popularization of smart devices, the scale of social media users around the world is increasing, and social media has become the center of people's communication, but it also produces a series of negative problems. Digital stress refers to the painful subjective experience of users caused by different stressors in the process of heavy use of social media. At present, most studies on social media focus on users' social media behaviors. In recent years, digital stress has gradually attracted the attention of researchers. However, most studies discuss the impact of single variables on results from the perspective of linear regression, and few studies focus on the complex mechanism behind digital stress. This study aims to explore the influencing factors and mechanism of social media users' digital stress in order to further understand the path of digital stress and provide reference for relieving users' digital stress. [Method/Process] This paper adopted a mixed research method combining grounded theory and qualitative comparative analysis. First, 21 users were selected as interview objects, interview data were coded, and theoretical models were constructed. Second, a questionnaire was designed according to the theoretical model and 262 questionnaires were collected. The fuzzy set qualitative comparative analysis (fsQCA) method was used to analyze the questionnaire data and explore the formation path of social media users' digital stress. [Results/Conclusions] There were 9 influencing factors of social media users' digital stress: overuse, technology intrusion, information overload, communication load, fear of missing out, approval anxiety, social expectation, digital coping skills and self-control. They were classified into four dimensions: technology, social, environment and personal characteristics. There are six paths that trigger digital stress, among which overuse and fear of missing out are the key factors leading to high-level digital stress, technology intrusion and information overload are the important conditions for digital stress, and digital coping skills and self-control have no significant effects. At the same time, this paper has some limitations. First, the end point and result variable of this paper is the digital pressure of social media users, focusing on the factors that affect the generation of digital pressure and how the combination of factors and variables ultimately leads to the generation of results. Less attention is paid to user behavior. Although some attention is paid in the interview, antecedent variables are emphasized in the analysis. Future studies can take users' social media usage behavior into consideration to explore the whole process formation mechanism of influencing factors-digital pressure-user behavior. In addition, most of the research samples are young users of social media, and users of other age groups are less involved. In the future, the research samples should be further expanded to improve the universality of the research conclusions.

[Purpose/Significance] Interdisciplinary research has emerged as a key driver of knowledge innovation, its essence being integration of knowledge from different disciplines. A deep and nuanced understanding of the research content of interdisciplinary knowledge integration is essential to foster innovation beyond traditional academic boundaries. Most of the research reviews on interdisciplinary research summarize theories, concepts and indicators from the macro level, while the content of interdisciplinary knowledge integration at the micro level is scattered, and lacks systematicity and logic. Therefore, this study attempts to classify and summarize the research methods, research content and research ideas involved in order to provide reference for scholars and researchers engaged in interdisciplinary knowledge integration. [Method/Process] Based on Web of Science (WOS) and China National Knowledge Infrastructure (CNKI) database as the primary data sources, we reviewed the relevant literature on interdisciplinary knowledge integration. By clarifying the intrinsic meaning of interdisciplinary knowledge integration, we have systematically reviewed and summarized the existing research findings from three aspects. First, research on the degree of knowledge integration mainly involves measurement methods. Second, research on the content of knowledge integration is based on citations and keywords. Third, research on the process of knowledge integration involves its integration path and process, and the characteristics of the integration stage. On this basis, this paper also summarizes the limitations and challenges of existing research, and provides research perspectives for subsequent research on interdisciplinary knowledge integration. [Results/Conclusions] The existing results have extensively explored the definition, measurement method, content, and process of interdisciplinary knowledge integration, but there are problems such as limited applicability of knowledge integration measurement methods, insufficient semantic disclosure, and the lack of systematic research on the degree of knowledge integration. Future research in this area should pay attention to the following three aspects. First, the applicability of methods for measuring interdisciplinary knowledge integration should be improved in order to better adapt to the development of interdisciplinary knowledge integration. Second, there is also a need to strengthen the study of knowledge integration from the perspective of knowledge increment, examining how new knowledge is created and how it contributes to the advancement of the area. In addition, efforts should be made to explore new theories and methods, grasp the development law of interdisciplinary knowledge integration, and expand the application scope and application value of interdisciplinary knowledge integration.

[Purpose/Significance] In order to better realize the goal of digital transformation of education and digital transformation of university libraries, university libraries should strengthen the team building of high-level and high-quality librarians, so as to improve librarians' digital literacy levels and serve the independent training mode of high-level talented professionals in universities. Most of the existing digital literacy research studies farmers, college students, and teachers, whereas few studies focus on the digital literacy of librarians in teaching assistant positions. With the gradual deepening of the digital transformation of libraries and the application of educational technology, the improvement of librarians' digital literacy is particularly important. Therefore, this study aims to establish the correlation between educational technology and librarians, and explore the ways to improve librarians' digital literacy from the perspective of educational technology application, in order to fill in the gaps of current research. [Method/Process] Based on the literature analysis and research background at home and abroad, this paper comprehensively explored the connotation of digital literacy, and the connotation and characteristics of educational technology; through the combination of "online + field", this paper reviewed the practical application of educational technology at home and abroad in university libraries from two aspects of similarity and difference, and discussed the necessity and correlation of librarians to improve their digital literacy. From the three aspects of media literacy, data literacy and ethical literacy, the pathway for librarians to improve their digital literacy was constructed. [Results/Conclusions] This paper extracts three important qualities needed in the application of educational technology, and constructs the way to improve the quality of librarians, so as to improve the effective utilization rate of educational technology and find out the position of educational technology in the library service. Due to the realistic factors such as time and research object, this study still remains in the theoretical aspect, and we need further verify our method's feasibility and practicality. In the future, we will further study the influencing factors of how to improve the digital literacy of librarians, and then improve our method of improving the digital literacy of librarians from the aspects of digital literacy education object, education content, education method, education mode and education evaluation, so as to realize the feasibility of our method.

[Purpose/Significance] The new quality productivity advancing AI technology, especially exemplified by large language models (LLMs), is rapidly updating and attracting wide attention. In order to accelerate the implementation of AI technologies, it is urgent for advanced AI technologies to acquire support from knowledge resources in scientific and technological (S & T) information and libraries. Meanwhile, S & T information provides significant potential service scenarios for the application of AI technologies such as LLMs. This study aims to explore and design the method and path for constructing AI-ready data resources in the field of S & T information, and proposes a comprehensive and operable construction model that adapts to the new technical environment of AI, thereby facilitating comprehensive readiness in the field of intelligence. [Method/Process] This study first focuses on the concept and development status of AI-ready construction, and examines the development of AI-ready construction at home and abroad from three aspects: governments, enterprises and research institutions. The survey shows that the application of artificial intelligence has been highly valued by various fields of scientific research and production. However, the groundwork and preparation for AI applications are still relatively lagging behind, and AI tools cannot be fully implemented in key application scenarios due to the lack of high-quality and refined data resources. Based on the research results, the study made a preliminary definition of AI-ready construction, that is, we defined AI-ready construction as: the various development and improvement actions to adapt the object to the AI technical environment and promote the long-term benefits. The research then focuses on the field of S & T information, and systematically discusses and designs the AI-ready construction mode in the field of S & T information from six aspects: connotation category, construction angle, construction object, construction principle, control dimension and types of construction mode. [Results/Conclusions] The construction of AI-ready S & T information resources is a comprehensive and multi-angle transformation and upgrading process, which is located between the knowledge resource end and the intelligence application end. It is carried out in four aspects, including standards, methods, tools and platforms. The main content of the construction includes channels of AI technology, data transformation, data resources, and data management. At the same time, the construction is comprehensively controlled by six principles and four control dimensions. Besides, this study proposes the way of the practical construction of AI-ready S & T data resources, including the construction of intelligent data systems, and the construction of integrated platforms for the whole life cycle of S&T information data. The path reflects the process of the variation of knowledge resources from diversification to organization and then to integration, which not only serves the scientific information field itself, but also provides more intelligent, convenient, rich and powerful S&T information support for various fields. In the future, it is hoped that further research can delve into more micro and practical aspects, review the specific characteristics of different AI technologies, and provide more detailed suggestions for specific application scenarios at the operational level, providing a solid guarantee for scientific research institutions to achieve the leading strategic position in research and development.

[Purpose/Significance] The report of the 20th National Congress of the Communist Party of China pointed out that the in-depth integrated development of culture and tourism should follow the principle of shaping tourism with culture and highlighting culture with tourism. As an integral part of the public cultural service system, university libraries and social organizations cooperate with each other to form a common force that contributes to promoting the inheritance and innovation of excellent culture, enhancing cultural confidence, and promoting the high-quality development of culture and tourism integration. [Method/Process] This study elaborates on the necessity of jointly building and empowering the development of cultural and tourism integration between university libraries and social organizations. At the same time, it introduces a new model of cooperation between university libraries and social organizations based on the theory of full life-cycle project management, and systematically analyzes the characteristics and management mechanisms of project management under this model. Based on this, it takes the practice of strengthening culture and tourism integration through cooperation between Hainan Normal University Library and social organizations as an example, and summarizes the effectiveness and characteristics of their cooperation. [Results/Conclusions] Based on the characteristic literature resources, university libraries cooperate with social organizations to jointly promote the innovation practice of local cultural construction, which has strengthened the inheritance and innovation of local characteristic culture to a certain extent. However, due to the different cooperation projects, the specific practice process and effectiveness are also very different. It is necessary to standardize the management process and further refine the cooperation strategies for the characteristics of different social organizations. Therefore, in connection with the actual cooperation between the Shanghai Normal University Library and social organizations, starting from the project cooperation process, university libraries should pay attention to the following issues: clarifying service positioning, strengthening the selection of cooperation organizations; integrating advantageous resources and improving service project management; ensuring service effectiveness and optimizing the connotation of cooperation projects; innovating service forms and deepening the promotion of cooperation achievements..

[Purpose/Significance] The advent of the Internet and the subsequent evolution of new technologies and applications, such as big data and artificial intelligence, have spurred the exponential growth of a new generation of technologies. China has entered the era of data-driven digital intelligence, with social network data privacy protection playing a crucial role in the country's comprehensive security strategy. By studying the evolution of this field, we gain insights into how to protect personal information, foster the healthy development of social platforms, and facilitate the responsible circulation of data elements. Compared to previous studies, this paper offers a broader range of perspectives, exploring the main directions and roles of each element of privacy protection with the information ecology theory, and more comprehensive research content, and combining causes, technologies, management and metrics.We propose an ecological framework for social network data privacy protection, based on a thorough overview of the subject matter. This framework serves as a reference point for the evolving landscape of privacy protection practices. [Method/Process] This study uses two different approaches: literature review and content analysis. The former is utilized to identify and categorize literature related to CNKI and WOS, while the latter is employed to visually analyze and interpret this corpus using Citespace. This study provides a systematic review of data privacy protection in social networks in four dimensions: privacy protection triggers, privacy leakage, privacy protection technology, and privacy protection management. The review is based on the visualization and analysis of both Chinese and international literature. Furthermore, we present our perspective on information ecology, integrating analyses of research themes and limitations for each information topic. We also explore strategies to promote the sustainable and healthy development of behaviors related to data privacy protection in social networks. [Results/Conclusions] Interdisciplinary exchange on data privacy protection in social networks is essential to advance the digital intelligence era. Relying solely on isolated methods of privacy protection is insufficient in the face of an increasingly complex application environment and the trends towards digitalization and intelligence. It is therefore necessary to establish a comprehensive privacy protection system that integrates technical optimization, legal improvements, platform regulations, and user engagement. Specifically, from a technical perspective, it is essential to leverage a variety of technologies to develop solutions for privacy protection. From a legal perspective, there is a need to refine the content, standardize the adjudication process, and strengthen supervision and sanctions. At the platform level, optimizing the content of privacy policies and ensuring their effectiveness are crucial. Finally, at the user level, it is essential to raise awareness of privacy protection and to enhance privacy protection capabilities. Moreover, it is crutial to examine the inherent relationship between each entity and the methods of protection. A key limitation of this paper is the lack of an in-depth analysis of the interaction mechanisms between stakeholders within the ecological framework of social network data privacy protection. Future iterations will address this by incorporating a background on the complex information environment and conducting a more in-depth analysis of the interaction mechanisms.

[Purpose/Significance] Accelerating the construction of digital rural areas is a strategic direction for comprehensively promoting rural revitalization, which plays an important role in promoting the modern basic living conditions in rural areas, improving the quality and efficiency of farmers' production and living, and achieving the development of urban-rural integration. In recent years, the construction of digital rural areas has been actively promoted in various regions, and a number of typical models are being explored and practised which has brought more digital dividends to rural residents. However, the regular characteristics of various practices have not been summarized in related research, resulting in poor promotion of best experience models and a lack of directional indicators for digital rural construction in different regions. This paper has summarized the regular characteristics and application mechanisms of diversified digital rural construction practices in China. The relevant conclusions would provide theoretical reference for promoting the construction of digital rural areas in different regions through classification. [Method/Process] Based on the perspective of structural elements and dynamic effects, this paper investigated four typical county-level digital rural construction models as research objects, namely Deqing County, Pukou District, Cao County, and Dianjiang County, in the national or provincial-level digital rural pilot county. Then, it used a multi-case analysis method to explore the regulatory characteristics of different types of digital rural construction models. [Results/Conclusions] The construction of digital rural areas in China mainly involves the integration of urban and rural areas, the integration of industry and city, the integration of point, line, and area, and the promotion of construction throughout the county. Influenced by factors such as the main functions of the construction, the requirements of the construction content, and the resource endowment, location, and transportation of the construction area, the internal and external thrust mechanisms of different construction models also exhibit different characteristics. In promoting the construction of digital rural areas in the future, different regions should fully consider the strength of the main functions of the construction, choose different construction mechanisms and content, so that digital rural areas can benefit more farmers, and help promote the comprehensive revitalization of rural areas. However, there are some shortcomings in this paper, such as the lack of in-depth analysis on the role and functional positioning of farmers, different levels of government, and market subject as participants. More wisdom is needed to embed the operation and maintenance mechanism for the later stage of digital rural area construction in future research.

[Purpose/Significance] There is no shortage of discussions in the library industry on how the value of academic libraries can be reflected by affecting students' learning outcome. There are also excellent cases such as the "Value of Academic Libraries' Initiative", which have a great impact on the theoretical and practical research in the field, and have initially formed a research system. Due to the differences in the higher education systems of different countries and the focus of higher education talent cultivation goals in different eras, it is necessary to consider the actual situation and based on the construction background of "double first-class" university construction to explore the paths and countermeasures that are in line with the development strategy of higher education in the new era of Chinese academic libraries. Scientific measurement and evaluation of academic library services from the student-oriented perspective is an important way to clarify the key path of library value enhancement, which is helpful for libraries to optimize their services, improve their development framework and enhance their own value. [Process/Method] In view of the above background and related research deficiencies, this research focuses on how academic libraries can improve their own value in the new era to better serve the strategic development of universities, and become the core of value for various stakeholders to discuss. Meanwhile, the methods used in related research lack the in-depth analysis of the process of library influence. In order to systematically sort out the internal logic of library impact on students' learning outcome, it is essential to explore the role of process factors in it, and it is not enough to use only regression analysis to conduct data statistics. This study analyzed 985 questionnaires by using the structural equation model analysis method, built a student-oriented value impact model of academic libraries with "situation-effect-outcome" as the main line, and explored the key influencing factors. [Results/Conclusions] It is suggested that the academic libraries should enhance their value influence in the following four aspects: to strengthen the policy guidance to improve the service utilization rate of academic libraries, attach importance to the contribution and value of academic libraries in the construction of "double first-class" university service, study and build a service system that meets the needs of users, and strengthen the service support for "double first-class" university construction. In this study, the research area is set in the University of Chinese Academy of Sciences and the interviewees are set at the postgraduate education stage. Although it is representative to a certain extent, the sample scope is still limited. The applicability of the conclusions obtained from the empirical research needs to be further verified to improve the reliability of the conclusions. In the future, it is necessary to investigate the influence of more types of university libraries on students' academic performance and the influence of university libraries on students' academic performance at different stages of education. To verify whether school factors and the training level of students have an impact on the correlation between university libraries and students' academic performance, and whether the causal relationship between the cognition and evaluation of students promoted by university libraries and students' academic performance is applicable to all universities and students.

[Purpose/Significance] With the popularity and development of social media, Weibo has become an important information transmission platform. Understanding the law of emergency information transmission based on the characteristics of Weibo users is of great significance for grasping the development trend of events, evaluating the influence of information, and formulating effective response strategies. [Methods/Process] Selecting typical cases of four types of emergencies (natural disasters, accidents, public health events, and social security events) as the research objects, this paper crawled the user data of the information transmission on the Weibo platform and analyzed the distributions of user gender, user geographical distribution, user attention and fan number and user type of the information transmission for these events, in order to reveal the differences and similarities of the user characteristics and transmission laws for the four types of emergencies. [Results/Conclusions] As for the similarities of the user characteristics and transmission laws, first, the audiences of the four types of emergencies have obvious regional characteristics, and the users in economically developed provinces generally have a higher attention rate. Second, the transmission users of all types of emergencies are generally concentrated on active users and grassroot users with strong and weak propagation power respectively, accompanied by a small number of authoritative users with strong influence. However, there are differences in the broadness and gender distribution of the audiences for different types of emergencies. First, natural disasters have a wider spread of the audiences and relatively higher attentiveness; accidents and public health events tend to be local events with relatively low attentiveness, whose audiences may be more concentrated in and around the affected areas; the audience spread of social security events is scattered depending on the nature of the event, the scope of influence as well as the communication channels. Second, female users pay more attention to natural disasters, public health events and social security events, while male users pay more attention to accidents, which can be attributed to the different emotional orientations and psychological characteristics associated with users of different genders. These results provide insights for the formulation of targeted guidance strategies for information dissemination. In future studies, we will collect data on other social media platforms, obtain more information on user characteristics through different channels, and introduce more in-depth analysis methods and indicators to comprehensively reveal the dynamic mechanisms of emergency information dissemination, thus improving the accuracy and effectiveness of the research.

[Purpose/Significance] Accurately measuring the influence of technical topics is crucial for decision-makers to understand the developmental trends in the technology sector. It is also an important link in identifying emerging, cutting-edge, and disruptive technical topics. Traditional methods of measuring technical topic influence are significantly affected by the latency of patent data approval and citations, lack a forward-looking perspective on the potential influence of technical topics, and suffer from insufficient semantic richness in the extraction of technical topics. This paper presents a method for measuring technical topic influence based on PhraseLDA-SNA and machine learning. It aims to mitigate the impact of delays in patent data approval and citation, while improving the interpretability and accuracy of the results in assessing technical topic influence. [Method/Process] In this study the explicit and implicit determinants of technical topic influence were first analyzed, based on which an index system for measuring technical topic influence was constructed. Then, the PhraseLDA model was used to extract semantically rich technical topics from a large corpus of pre-processed patent texts and to compute the topic-patent association probabilities. PhraseLDA-SNA enhances the semantic richness of technical topic extraction and deepens the analysis of topic content. Machine learning methods leverage their robust data processing and analysis capabilities to predict the high citation potential of patents related to the topics. This research integrates PhraseLDA-SNA and machine learning methods to accurately measure the significance and advanced nature of technical topics in promoting field development, thereby achieving an accurate measurement of the influence of technical topics. Finally, an empirical study was conducted in the field of cellulose biodegradation to compare the high-impact technical topics identified by the proposed method with those identified by the traditional method. Several experts with high academic influence and extensive experience in cellulose biodegradation research were invited to evaluate the high-impact technical topics identified in this study, thus validating the effectiveness of the proposed method. [Results/Conclusions] Compared with the traditional method, the technical topic influence measurement approach based on PhraseLDA-SNA and machine learning reveals more in-depth content. Moreover, this method also analyzes the importance and leading nature of technical topics, which shows superiority in quantitative analysis. Comparing the distribution of high-impact technical topic-related patents identified by the two methods across different years, the topics identified by the proposed method had a higher association ratio in the most recent data, indicating a significant reduction in the impact of patent data approval and citation delays.

[Purpose/Significance] Health is the foundation of survival, and the health of all people is the foundation of a country. However, the aging situation in China's rural areas is serious, and the health information literacy (HIL) of the middle-aged and elderly population is low. Improving the HIL of middle-aged and elderly people in rural areas is of great significance to personal health and the "Healthy China" strategy. In terms of research perspective and content, previous studies either used quantitative methods to measure the health level of rural middle-aged and elderly people, or used qualitative methods to analyze a certain aspect of HIL, but the reasons for the low level of HIL among rural elderly people are not explored from a qualitative perspective. Based on this, the author analyzes the reasons for the low level of HIL of the rural middle-aged and elderly from the perspective of qualitative research and proposes corresponding countermeasures. [Method/Process] Semi-structured interview method and ground theory were used to explore the reasons for low HIL among rural middle-aged and elderly people from five aspects: health information awareness, health information access, health information evaluation, health information utilization and health information service. A theoretical model of the causes of low HIL among rural middle-aged and elderly people was constructed. [Results/Conclusions] It is found that the reasons for the low HIL of the rural middle-aged and elderly people include personal cognitive limitations, objective condition limitations, and service delivery problems. Specifically, the reasons are rejection of digitalization, cognitive misunderstanding, physical condition limitation, digital equipment limitation, low quality of related services, and the lack of related services. Accordingly, from the level of personal cognition, it is proposed that multiple measures should be taken to promote health-related publicity and education to improve the awareness of HIL. For example, offline and online HIL education should be improved and the characteristics of rural social acquaintance should be used to improve publicity and HIL education. From the perspective of objective conditions, it is suggested that the material basis of life should be improved to raise the level of HIL. From the perspective of health information services, health care institutions, village committees, libraries and family members should be involved in the health information service system for the rural middle-aged and elderly people, and the quality of health information services should be improved. The interaction between the various causes can be further explored in the future.

[Purpose/Significance] Aiming at the semantic missing and incomplete problems in the process of image organization and retrieval, a framework for semantic description of images in social media is proposed to enrich the existing theoretical system of image description, improve the efficiency and utilization of image retrieval, and provide a reference for the realization of the automatic semantic annotation of images. [Method/Process] First, we conducted a survey and analysis of research progress related to image description both domestically and internationally, summarizing the existing theories of image description and annotation, metadata specifications, and related technical methods. Second, based on the image metadata standards and the theory of hierarchical and categorical description of image features, we constructed a semantic description framework for social media images, focusing on seven layers: external feature layer, content layer, object layer, relationship layer, scene layer, event layer, and emotional layer. We also elaborated in detail the various semantic layers and their interrelationships. Finally, we verified the feasibility of the image semantic description framework by describing the examples of character images and landscape images. [Results/Conclusions] The results of the descriptive examples of character images and landscape images indicate that the image semantic description framework can eliminate the "semantic gap" in image description through semantic associations between different layers, and achieve a multi-faceted, multi-dimensional, and multi-level structured and semantic description of the external and content features of images. It has strong portability and flexibility. However, there are also certain limitations and areas for improvement in this paper: 1) Based on the image semantic description framework proposed in this paper, a prototype system based on image annotation needs to be developed; 2) The images posted by users on social media are closely related to the situation, and they are more likely to express emotions. In the future, more research on the semantic layer of images can be conducted based on the text information posted by users; 3) Future research can further explore the application of deep learning in image and text fusion to achieve more accurate event and emotion recognition. By constructing a more complex neural network structure, the event and emotion information in the image can be deeply mined and fused; 4) When describing images, the study should pay attention not only to static visual features, but also to consider the dynamic course of events. Future frameworks could attempt to combine static and dynamic information to provide richer, more vivid descriptions of images.

[Purpose/Significance] With the popularization of artificial intelligence technology, the cost of information fog has decreased, and its negative impact on national security is becoming increasingly apparent. Information fog not only creates cognitive barriers for users, but also poses serious challenges to various fields such as politics, economy, and society. This article explores the prevention and control of information fog from the perspective of the overall national security concept, with the aim of addressing the risks and challenges posed by information fog. There is a lack of research in the literature on the prevention and control of information fog from the perspective of overall national security. To fill the gap, this article not only provides a new perspective and strategy for the prevention and control of information fog, enriching the connotation of national security research, but also promotes the cross-integration of information security and national security disciplines, providing new theoretical support for research in related fields. It provides reference and guidance to relevant entities such as the government and online platforms in preventing and controlling information fog. [Method/Process] Based on the concept of overall national security, this article summarizes the academic achievements on information fog at home and abroad, including research on stages, scenario applications, governance strategies, and practical case analysis. We summarize the characteristics of information fog and analyze the methods and strategies for prevention and control. [Results/Conclusions] Information fog has the characteristics of wide dissemination, realistic experience, and difficulty in identification. Based on this feature, the article puts forward the following suggestions to strengthen the improvement of legal policies and clarify the division of responsibilities: 1) to strengthen the evaluation and risk warning of online accounts and utilize technology to update anti-counterfeiting tools and improve information authentication capabilities. Governments should intervene in a timely manner to prevent the information fog from escalating. 2) to improve public awareness of discrimination and the level of prevention. In addition, the article also has some shortcomings. First, it does not present other forms of information fog in the security domain. Second, it does not analyze information fog from an algorithmic perspective. Therefore, in future research, we will closely follow the development of society to analyze the characteristics and presentation methods of information fog in various security fields. At the same time, scholars in the fields of computer science, intelligence science, and national security are also invited to conduct in-depth analysis of information fog from the perspective of computer algorithms, in order to propose practical countermeasures and suggestions for preventing and managing information fog from a technological perspective.

[Purpose/Significance] This study aims to unravel the complex relationship between new quality productivity (NQP) and rural revitalization, and to deepen understanding of the role of media in rural development. NQP, characterized by advanced technologies, innovative practice, and enhanced efficiency, has the potential to transform rural economies and communities. This research provides a multi-dimensional theoretical perspective and scientific foundation to advance comprehensive rural revitalization in China. By offering novel insights compared to the existing literature, this study establishes its significance in the field of scientific knowledge and demonstrates its potential to address significant real-world challenges. Understanding the synergies between NQP and rural revitalization can help policy makers, researchers, and practitioners to develop effective strategies to promote sustainable rural development and address socio-economic disparities. [Method/Process] The study employed a rigorous methodological approach that involved the training of a naive Bayes classifier to categorize the texts of government work reports. This machine learning technique enabled the extraction and analysis of relevant information from a large corpus of textual data, providing a robust basis for further empirical investigation. The study utilized provincial-level data from 2012 to 2022 to construct comprehensive evaluation frameworks for the NQP and rural revitalization. These frameworks included a wide range of indicators reflecting economic, social, and technological dimensions.Statistical analyses included bi-directional fixed effect models and spatial Durbin models, which allowed for a comprehensive exploration of the impact mechanisms and spatio-temporal dynamics of NQP on rural revitalization. The bi-directional fixed effect model helped to control for unobserved heterogeneity and to capture the dynamic interplay between NQP and rural revitalization over time. The spatial Durbin model was particularly useful in identifying spatial spillovers and understanding regional interdependencies. The theoretical underpinnings of this research were grounded in established frameworks in economic development and media studies. Media practice, including information dissemination, community building, and consumption upgrading, were hypothesized to play a crucial role in facilitating the impact of the NQP on rural revitalization. The empirical foundations were derived from robust provincial-level datasets, ensuring the reliability and validity of the findings. These methodological choices ensured a rigorous examination of the complex dynamics between NQP and rural revitalization in different regions over time. [Results/Conclusions] 1) Media factors demonstrated significant complementary relationships with various drivers of rural revitalization. 2) Media practice, centered on information support, community building, and consumption upgrading, has profoundly altered rural production relations and economic bases. 3) Temporally, both NQP levels and rural revitalization showed rapid growth, with annual growth rates increasing. Spatially, the central and western regions showed a stronger impact of NQP on rural revitalization compared to the eastern regions.4) NQP had significant spatial spillover effects on rural revitalization, not only influencing local revitalization efforts but also fostering stronger indirect effects on surrounding areas, thereby promoting regional interlinked development.

[Purpose/Significance] In the context of the digital age, knowledge collaboration platforms such as online Q&A communities, academic forums, and various professional networking platforms have become important venues for knowledge sharing and collective wisdom. These platforms bring together users from different fields, with diverse professional backgrounds and levels of expertise. They actively engage in problem solving, exchange views, and form complex and dynamic social networks. Online knowledge collaboration platforms not only enhance the accessibility of knowledge but also serve as incubators for interdisciplinary communication, problem solving, and innovative thinking by harnessing the collective wisdom and expertise of individuals. This article explores how to optimize the network structure of online knowledge collaboration platforms and balance the internal knowledge and expertise within teams. The goal is to promote cross-domain information flow, prevent the formation of information silos, and promote the creation, dissemination, and application of knowledge through collective knowledge collaboration. [Methods/Process] Due to the diversity of participants' backgrounds, experiences, and viewpoints, effectively managing and coordinating this heterogeneity becomes a critical issue. Additionally, the quality and efficiency of knowledge collaboration is also influenced by the characteristics of the network structure, such as the flow of information paths, the role of key nodes, and the interaction patterns of small groups. This study is based on actual data from Stack Overflow, the world's largest programming Q&A website. It focuses specifically on the following aspects of influence: clustering coefficient, node centrality, edge span, user knowledge heterogeneity, and user experience heterogeneity. By constructing a negative binomial regression model, the study investigates how network structure characteristics and team user heterogeneity affect the quality and efficiency of knowledge collaboration. [Results/Conclusions] The results show that, with respect to network structural characteristics, node centrality significantly improves the quality and efficiency of collaboration, and higher aggregation coefficients and larger span of connecting edges restrict information flow and are detrimental to the efficiency of knowledge collaboration. In terms of user heterogeneity, high heterogeneity in knowledge background and registration duration usually hinders collaboration, heterogeneity in experience heterogeneity in registration duration negatively affects collaboration effectiveness in both cases, heterogeneity in response acceptance rate only negatively affects collaboration quality, while heterogeneity in activity intensity positively affects it. In addition, this study still has shortcomings that deserve further exploration. First, future research could consider expanding the sample to include more questions on different topics and domains to increase the reliability and generalizability of the findings. Second, future research could focus on the dynamic changes of network structure and heterogeneity in order to better understand the impact of network structure on knowledge collaboration and to improve the prediction ability of collaboration effects; it could explore more deeply how different types of heterogeneity affect collaboration dynamics over time.

[Purpose/Significance] Today, the methods of global technology cooperation have become diversified, while the patterns of knowledge and resource flows have become networked. The way knowledge flows between science and technology and promotes innovation is a hot topic in informatics research. Under such circumstances, the transfer and flow of technical knowledge has become increasingly important for the creation of new technologies and the generation of new knowledge. It can provide potential solutions for solving technical problems and generating technological competitive advantages. This study reveals the structural characteristics of the knowledge flow network between science and technology from a micro perspective, and provides new ideas for discovering new knowledge flow and communication channels, understanding the links between science and technology, and exploring innovation breakthroughs. [Method/Process] This paper adopts a multi-perspective approach and exames technical knowledge citation, scientific knowledge citation, and the intersection of scientific knowledge. Specifically, the study focuses on patent-patent citation, patent-paper citation, and paper-discipline co-occurrence, and uses a multi-layer network method to develop a science-technology (S&T) knowledge flow micro-network analysis framework. Through this framework, knowledge flow patterns between science and technology can be comprehensively explored. An empirical study was conducted in the field of genetically modified corn to investigate the knowledge flow patterns between science and technology. Using a multi-layered network model, this study aims to explore the relationship between science and technology from three different perspectives. [Results/Conclusions] The results of the study suggest that technology nodes that absorb multidisciplinary knowledge are more likely to engage in knowledge diffusion or absorption. Additionally, knowledge flow is more likely to occur between the technology nodes corresponding to two interdisciplinary subjects. The analytical framework proposed in our study can reveal the characteristics of knowledge flow from a micro perspective, and can identify two types of knowledge flow structures in the empirical case of genetically modified corn, which extends and enriches existing research on knowledge flow. In the future, the S&T knowledge flow research framework proposed in this study has the potential to be further extended and widely applied by incorporating different types of knowledge subjects, enriching knowledge attribute factors, and expanding knowledge flow paths. For instance, the research framework can be extended to broader fields to explore the relationship between knowledge flow patterns and the characteristics of these fields. It can also be used to explore knowledge flow patterns and potential technological breakthroughs at different flow levels and innovation themes. Such research can serve as a basis for innovation policy and provide theoretical support for the development of strategies and technology research directions.

[Purpose/Significance] With the advent of the algorithmic era, libraries' information delivery channels have shifted from offline physical entities to online digital platforms. This transformation has brought about significant changes in the way users access and utilize scientific data. The frequency of use of scientific data has increased exponentially, as more and more users rely on data to support their research, education, and innovation activities. The huge demand and application of use of data poses challenges to the development of libraries, among which the service guarantee of intellectual property rights (IPR) for scientific data is becoming a key factor affecting the development of digital libraries. IPR is a legal concept that protects the ownership and control of data creators and providers over their data. It also regulates the rights and obligations of data users and re-users. Therefore, this study aims to explore the influencing factors and optimization strategies of libraries' IPR service quality for scientific data. [Method/Process] To achieve this goal, this study used a questionnaire analysis method to collect data from a sample of 252 individuals belonging to a highly knowledgeable group, such as researchers, academics, and students. These individuals are the main users and producers of scientific data, and their perceptions and expectations of the quality of IPR services by libraries are crucial for improving the service. The questionnaire consists of four parts: demographic information, IPR awareness, IPR satisfaction, and IPR improvement suggestions. The reliability of the questionnaire factors is between 0.724 and 0.913, indicating a high level of internal consistency. The validity of the questionnaire is verified by confirmatory factor analysis, which shows a good fit between the data and the model. Based on the data, this study conducts a path analysis to test the hypotheses and obtain the results. [Results/Conclusions] The results show that the following factors have a significant positive impact on the quality of libraries' IPR services for scientific data: the implementation efficiency of policies and regulations (beta=0.326, p<0.001), talent team building (beta=0.274, p<0.001), the data management technology (beta=0.211, p<0.001), the diversification of service models (beta=0.358, p<0.001), and the number of data IPR sharing agreements (beta=0.329, p<0.001). These factors reflect the importance of improving the legal, human, technical, and organizational aspects of libraries' scientific data IPR services. Based on the findings, this study proposes five optimization strategies for libraries in scientific data IPR service: strengthening the implementation of policies and regulations, improving the training and motivation of talent teams, upgrading the data management technology, innovating the service model, and increasing the number of data IPR sharing agreements. These strategies can help libraries to improve the quality of their scientific data IPR services and meet the needs of the users in the algorithmic era.

[Purpose/Significance] This study aims to explore the challenges that artificially intelligent (AI) scientists may bring to scientific epistemology. [Method/Process] Scientific discovery has long been of interest to AI researchers. The next big step in AI is the development of AI scientists. AI scientists should be able to independently motivate, make, understand, and communicate discoveries. Although the current robot scientists are still just a form of AI-driven automated experimental apparatus, and the best AI systems today cannot define their own hypothesis space and experimental design. At best, they can be considered to be a primitive form of AI scientists. Clearly, the specific path of AI-driven scientific research or the transition to AI scientists will inevitably be influenced by the frontier development of AI. Current AI systems must overcome the following major technical challenges: 1) making strategic choices in their research goals; 2) developing the ability to generate exciting and novel hypotheses in areas that push boundaries; 3) designing innovative approaches and experiments to test hypotheses that go beyond the use of prototype experiments; 4) focusing on and describing important discoveries in a way that can be understood by human scientists. The highly autonomous AI scientists can either make discoveries on their own or collaborate with other human and machine scientists to make Nobel-level discoveries. After reviewing the relevant AI applications in scientific research, this study illustrates the main characteristics of AI scientists and the two disruptive changes they bring about at the epistemological level: a leap in AI capabilities and AI for Science as the 5th paradigm of scientific research. [Results/Conclusions] The implications of AI for Science are revolutionary, but recent AI-driven explorations in scientific research increasingly support the possibility of its realization. In this situation, discussions on the epistemological issues of relevant sciences need to go beyond general philosophical debates and instead explore epistemological strategies for the coming scientific revolution in AI. In view of the coming scientific revolution in AI, this study proposes four strategies. First, we should pay more attention to the problems and solutions in the process of developing AI scientists. Second, the key to advancing the scientific revolution in AI is to find ways to eliminate factors that may lead to failure. Then, we use different strategies to achieve the scientific revolution of AI. Finally, we take advantage of metaphorical methods to help us develop AI scientists.

[Purpose/Significance] This paper aims to explore the development and evolution of the library statistical evaluation index system, highlighting its characteristics and changes at different stages of document management, information management, and data management. The research is conducted around three key stages: document level, information level, and data level, analyzing the main content and significance of the library statistical evaluation index system at different development stages. The innovation of this paper lies in the systematic analysis of these transitions, providing a comprehensive perspective that integrates theoretical and methodological advances with practical indicators. [Method/Process] The research methodology includes a systematic analysis of statistical evaluation indicators of libraries in different stages of development. The study uses historical review and theoretical analysis methods, analyzing the development of document organization, information digitization, and data management in libraries. By examining the development of classification, cataloging, and evaluation metrics, the research combines historical documentation with contemporary practices to provide a solid theoretical foundation. The study also draws on existing literature and integrates data from library management systems and user feedback to assess service quality and operational efficiency. This mixed-methods approach ensures a comprehensive understanding of the applicability and effectiveness of the evaluation indicators. [Results/Conclusions] The study shows that the library's statistical evaluation index system has evolved significantly, reflecting the library's adaptation to changing resource types and management needs. The main conclusions can be summarized as follows. The document level in the first stage, focusing on book circulation, including indicators such as book use efficiency, collection development quality, and reader engagement. Key metrics such as cumulative borrowing and utilization rates provide basic service performance data, but lack deep information insights. With the development of information technology, library statistical evaluation indicators have expanded to include service frequency, response time, user satisfaction, and growth rates, enabling libraries to evaluate and improve service strategies based on user feedback and service performance. Currently, the library's statistical evaluation system focuses on research data management and data value assessment. Indicators now include not only resource- and service-related metrics but also operational efficiency, budget utilization, technological updates, scholarly contributions, and social impact. These indicators provide a comprehensive view of the library's performance in resource management, service quality, and social contribution, helping to optimize resource allocation, enhance service quality, and increase impact. The study also acknowledges certain limitations, such as the evolving nature of technology and user needs, which may require continuous updates to the evaluation system. Future research should explore the integration of advanced data analytics and artificial intelligence to further refine evaluation metrics. In addition, ongoing studies are needed to adapt to emerging trends in data management and user behavior to ensure that libraries remain at the forefront of information services in the digital age.

[Purpose/Significance] Breeding 4.0, characterized by "biotechnology + artificial intelligence + big data information technology," has brought new requirements for the digital management and intelligent utilization of germplasm resources. In order to meet the diverse support needs for knowledge service forms under an intelligent background, this article aims to propose an effective method for knowledge organization and deep semantic association. This is essential to address the inconveniences that discrete germplasm resource data bring to researchers when collaborating across regions and institutions. Therefore, the article presents a method that integrates fragmented domain data into a systematic knowledge system, which is particularly important. [Method/Process] By analyzing the domain data descriptions and the current organizational status, the ontology construction was performed using the seven-step method developed by Stanford University Hospital. First, existing ontologies such as the Crop Ontology, Gene Ontology, and Darwin Core were referenced and reused, and then integrated with the knowledge framework from the "Technical Specifications for Crop Germplasm Resources" series and example datasets. Consequently, an ontology model was successfully constructed, which covers five major categories of crops: cereals, cash crops, vegetables, fruit trees, and forage and green manure crops. This model defines 11 core classes including phenotypes and genotypes, as well as identification methods and evaluation standards, along with 10 object properties and 56 data properties. [Results/Conclusions] Based on the ontology model, the article proposes a methodology for constructing a knowledge graph of crop germplasm resources. Using rice as an example, a domain-specific fine-grained knowledge graph is developed to facilitate semantic association and querying across multiple knowledge dimensions. The article also outlines prospective designs for new intelligent knowledge service scenarios driven by the knowledge graph, such as intelligent question and answer and knowledge computation, aiming to meet the knowledge service needs of researchers, breeding companies, and the general public. This is intended to provide more accurate and efficient support for computational breeding efforts. Currently, the research focuses only on rice as an example of a cereal crop, with economic crops, vegetables, and other types of crop germplasm resources not yet included in the study. Future work will expand the scope of the study and add new classes and properties specific to different germplasm resources to better address the diverse and personalized knowledge needs of users in the eraa of big data. This approach aims to promote the contextualization, ubiquity, and intelligence of knowledge services, and to further integrate them into different academic disciplines related to the development of new quality digital productivity.

[Purpose/Significance] This study aims to critically analyze the social philosophical roots of the digital intelligence divide from the perspective of machine functionalism. By uncovering the theoretical origins and generation pathways of the digital intelligence divide, countermeasures can be proposed. The research contributes to understanding the divide's impact on society and provides insights for promoting inclusive development of artificial intelligence (AI) technology. The study fills a gap in the literature by linking machine functionalism to the digital intelligence divide and offers a novel perspective on addressing the unequal use of AI technology. The findings have significant implications for policymakers, technology developers, and researchers in the fields of AI ethics, digital inequality, and social philosophy. [Method/Process] Using the theoretical lens of machine functionalism, this study examines the evolutionary pathways, generation mechanisms, and multiple risks of the digital intelligence divide. It draws on relevant theories, such as the extended mind thesis and the theory of technological determinism, to analyze how machine functionalism influences the design and application of AI technology. The study also draws on empirical evidence from case studies and surveys to illustrate the manifestation of the digital intelligence divide in different contexts. By synthesizing theoretical and empirical insights, the research proposes interventions that address the divide at different levels, from the philosophical underpinnings to the practical implementation of AI technology. [Results/Conclusions] The study shows that machine functionalism, which applies Turing machine principles to explain the mind and views the mind as a physically realized Turing machine. It has become the social philosophical foundation of AI technology. While breaking with the traditional biological essentialist view of the mind, machine functionalism inadvertently creates inequitable uses of AI through three main pathways: the mechanization of the mind, designer bias and algorithmic preference, and technological specialization and barriers to entry. This creates the digital intelligence divide and risks such as the evolution of information access inequality into social inequality and the weakening of information cocoons and public dialogue. The study argues that interventions are needed to mitigate these risks and promote a more equitable distribution of the benefits of AI technology. To bridge the digital intelligence divide, the study suggests a multi-pronged approach. First, future efforts should focus on promoting positive interaction between machines and humans through value-sensitive design, which incorporates ethical considerations into the development and deployment of AI systems. Second, developing ethical algorithms that eliminate designer bias and algorithmic preference is critical to ensuring fair and unbiased AI decision-making. Third, improving the digital intelligence skills of individuals and communities can help break down barriers to entry caused by technological specialization and enable more people to benefit from AI technology. Together, these policies can help break down the barriers of unequal technology use under machine functionalism. The study concludes by emphasizing the importance of a collaborative effort among policymakers, technology developers, researchers, and the public in addressing the digital intelligence divide. It calls for further research on the social implications of machine functionalism and the development of inclusive AI governance frameworks. The findings of this study serve as a foundation for future work to mitigate the risks of the digital intelligence divide and promote the responsible and equitable development of AI technology.

[Purpose/Significance] The birth of the Internet has brought revolutionary impact on bibliometrics, giving rise to a number of online download indicators for academic literature. The most representative basic indicator among them is the download frequency, but it also includes the annual download rate, the total download volume, the download half-life, and the Google Scholar Index. The proposal of these indicators provides a new method and means of measuring scholarly dissemination and impact, which is a significant development of traditional bibliometrics and an important component of alternative metrics. Given the lack of indicators that comprehensively characterize the dissemination, impact, knowledge and information volume of academic journals, this paper proposes the download factor indicator to address this problem. [Method/Process] First, according to the changes of download frequency and citation frequency over the years, based on the citation data of CSSCI journals of library information and bibliology on CNKI, a panel data model was used to establish a prediction model of download frequency and citation frequency, and the optimal lag period for designing the download factor was determined. The indicator of download factor was proposed, that is, the average number of downloads per hundred times of each paper after 2 years of publication. This paper further used ridge regression to analyze the relationship between the download factor and the impact factor, h-index, and the number of articles. [Results/Conclusions] The download frequency with a lag of 1 year and 2 years determines 80% of the citation frequency. This article innovatively adopts a panel data model and comprehensively evaluates the impact of download frequency on citation frequency in both current and lagged periods, thereby greatly improving the prediction accuracy. The download factor can better measure the knowledge information volume, dissemination level, influence and academic quality of the journal. The timeline for downloading factor indicators is synchronized with the influencing factors, both within 2 years after the publication of journal articles, focusing on the evaluation of academic communication level. The download factor has the highest correlation with the main indicator of the impact of journal quality, the h-index, and has a high correlation with the impact factor and publication volume. It has good statistical indicator properties and is a comprehensive indicator for evaluating journals; the download factor index needs to be more inspection of application in disciplines and use of data. This article is based on the conclusions drawn from the research of 19 CSSCI journals in library and information science literature. The relationship between download frequency and citation frequency in other disciplines, as well as the construction of download factors, require further research in conjunction with the latest data.

[Purpose/Significance] In the era of mobile Internet, mobile phones are the most important information access tools. From the perspective of mobile phone use, this paper examines and reveals the information acquisition behavior of farmers, explores the information gap in rural areas, analyzes the characteristics of the information acquisition behavior of key groups, and provide insights into how to improve the information acquisition behavior and narrowing the information gap. The significance of the research is that, with a focus on digital inclusion, we start from the inclusive feature of the Internet and modern information technology, find out the key groups to pay attention to in the information gap, and put forward ideas on how to realize digital inclusion from the perspective of farmers' information acquisition and needs. [Method/Process] Based on the rural sample survey at the national level, principal component analysis and RIF regression analysis were used to measure farmers' information acquisition behavior and identify the role of key influencing factors in improving information acquisition behavior. This study analyzes farmers' information acquisition behavior from the perspective of mobile phone use, describes the micro characteristics of the information gap in rural areas, and makes the conclusion more scientific and generalizable based on the sample survey of farmers at the national level. [Results/Conclusions] The low "long tail" group in the evaluation results of farmers' information acquisition behavior exists in the aged people groups and the groups with the education level below junior middle school, which highlights the phenomenon of information gap in rural areas. Key explanatory variables have a more pronounced marginal effect on groups with low evaluation results of information acquisition behavior (below the median). Improving the impact of mobile phone use among key groups such as the elderly and the undereducated makes an important contribution to narrowing the information gap, which reflects the inevitable requirement of the concept of digital inclusion. Based on the improvement of network facilities, it is also necessary to pay attention to the use of mobile phone functions and information content acquisition of key groups, strengthen the accuracy of information supply, activate the information needs of key groups, and improve the adaptability of such groups in the digital environment. There are still more relatively poor and aging groups in rural areas, which need to be included in the digital inclusion path, improve the situation of vulnerable groups in the digital age, and provide the means to realize people's needs. Future research will pay more attention to promoting the provision of high-quality public service resources through digital tools, realizing the continuous empowerment of digital technology for rural development, and improving the digital literacy of citizens, especially rural residents.

[Purpose/Significance] The vigorous development of information literacy (IL) education has led to the increasingly prominent role of academic librarians as teachers in universities. However, most of the librarians who assume the teaching function lack the special training of pedagogy and teaching competence, so they have negative attitudes such as resistance and refusal to accept the role of teachers. These problems will inevitably affect the favorable and sustainable development of library IL education. Therefore, building the teacher role of librarians is of great significance to the development of IL education. [Method/Process] A content analysis method of the research literatures was used to review the historical development and recent debates about the teacher role of librarians were retrospected. We found that librarians currently play multiple teacher roles, including curriculum designers, teaching partners, teachers, academic research participants, and advocates for IL education. However, librarians face many realistic dilemmas in the process of teacher role development. Based on the in-depth analysis of the realistic dilemmas faced by librarians, this paper puts forward the ways of development for the teacher role of librarians from various aspects and perspectives. [Results/Conclusions] The research suggests that the development of the teacher role of librarians faces many realistic difficulties, such as the influence of professional image, the disconnect between library science education and practice, and the lack of teaching competence of librarians themselves. The ways of development: 1) Librarians: As the implementers of the educational mission, librarians in the new era should establish professional self-confidence and play a good role as a member of the educational and academic circles. In addition, they should actively examine their own lack of professional knowledge and pedagogical knowledge, and actively make up for their lack of knowledge through the training of teaching knowledge for librarians, the MOOCs of universities, and the further study and upgrading of academic degrees. It is also necessary to improve teaching skills through course observation, lecture practice, peer discussion, teaching reflection and other forms. In short, promoting librarians' teaching self-confidence and teaching competence is the key to developing the role of teachers; 2) Library science education: Attention should be paid to the establishment of courses related to IL teaching, such as adapting traditional library science courses to meet the teaching responsibility requirements of university librarians in China, and gradually adding courses related to teaching design, method, theory, assessment, introduction to teaching problems, presentation skills, cooperation and communication skills to improve the teaching ability of pre-service librarians. Embedding more demonstration/simulation teaching in LIS/MLIS teaching courses to help pre-service librarians gradually acquire teaching-related skills and experience, so as to prepare librarians for teaching roles; 3) Library departments: Efforts should be made to establish teacher-librarian positions, reallocate the responsibilities of librarians, and provide policy facilities to enable librarians to grow into library education experts; 4) Library industry associations: The dual professional qualification system of "teachers" and "librarians" should be implemented by library industry associations.