Elderly People's Online Health Information Seeking Behavior Based on Evolutionary Dynamics

Chunling GAO, Liyuan JIANG

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Journal of Library and Information Sciences in Agriculture ›› 2024, Vol. 36 ›› Issue (5) : 65-78. DOI: 10.13998/j.cnki.issn1002-1248.24-0254

Elderly People's Online Health Information Seeking Behavior Based on Evolutionary Dynamics

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Abstract

[Purpose/Significance] It is of great significance to analyze the current situation of elderly people's online health information seeking behavior, grasp its hot topics and development trend, to meet the health information needs and improve the health literacy level of the elderly people, and to promote the high-quality development of health services for the elderly people. [Method/Process] In this study, the DTM model was used to perform dynamic topic mining and analysis of Sina Weibo post content from 2016 to 2023, and the topic evolution, topic semantic evolution and topic information entropy trend were each investigated. In this study, data information related to online health searches of the elderly was obtained from the Sina Weibo platform, and the text content and time in the data information were taken as corpus data. After cleaning the data, different time windows are divided in time order, a DTM model is constructed to identify research topics, and "subject-word matrix" and "document-topic matrix" files are obtained. The topic intensity calculation was carried out successively, and the hot topic identification and analysis of online health searches for the elderly was carried out. The evolutionary trend of topic intensity was visualized and the evolutionary path of topic keywords was analyzed at a fine-grained level, so as to explore the focus and changing trend of online health information searches for the elderly people. [Results/Conclusions] The topics of "senile diseases", "old-age care by science and technology", "diet and health care", "mental health" and "social care" have evolved significantly, and the elderly people pay much attention to health information types such as common old age diseases, physical medical maintenance, social assistance and care for the elderly, and clothing, food, housing and transportation, in order to meet their information needs. The topics of "senile diseases", "old-age care by science and technology", "diet and health care", "mental health" and "social care" have evolved significantly, and the elderly pay much attention to health information types such as common old age diseases, physical medical maintenance, social assistance and care for the elderly, and clothing, food, housing and transportation, in order to meet their information needs. The research popularity of "economic trap", "epidemic control", "medical fraud", "virus transmission", "epidemic travel" and "medical health" as a whole showed a trend of first increasing and then decreasing, and the elderly continued to pay gradual attention to health emergencies and economic property security issues that might arise. The research popularity of "sports health care", "high risk" and "cultural and sports tourism" remain moderately stable from 2016 to 2023 and has not changed significantly. Topics such as "senile disease", "sports health", "high risk" and "medical fraud" are semantically stable. The information entropy of "sports health care", "daily life safety" and "virus transmission" is relatively stable, the information entropy of "medical literacy", "epidemic control", "cultural and sports tourism" and "balanced diet" shows a diffusion trend, and the information entropy of "high risk", "diet and health care", "economic trap" and "medical fraud" shows a convergence trend.

Key words

evolutionary dynamics / the aged / health information search / topic evolution / DTM model / information behavior

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Chunling GAO , Liyuan JIANG. Elderly People's Online Health Information Seeking Behavior Based on Evolutionary Dynamics. Journal of Library and Information Science in Agriculture. 2024, 36(5): 65-78 https://doi.org/10.13998/j.cnki.issn1002-1248.24-0254

References

1
中华人民共和国中央人民政府. 《“十四五”健康老龄化规划》印发——推动老年健康服务高质量发展[EB/OL]. [2024-03-23].
2
中华人民共和国中央人民政府. 高举中国特色社会主义伟大旗帜为全面建设社会主义现代化国家而团结奋斗——在中国共产党第二十次全国代表大会上的报告[EB/OL]. [2024-03-23].
3
中华人民共和国中央人民政府. 中华人民共和国老年人权益保障法[EB/OL]. [2024-03-23].
4
中国互联网络信息中心. 第53 次《中国互联网络发展状况统计报告》[EB/OL]. [2024-03-23].
5
李月琳, 蔡文娟. 国外健康信息搜寻行为研究综述[J]. 图书情报工作, 2012, 56(19): 128-132.
LI Y L, CAI W J. A review of the studies on health information seeking behavior overseas[J]. Library and information service, 2012, 56(19): 128-132.
6
赵栋祥, 马费成, 张奇萍. 老年人健康信息搜寻行为的现象学研究[J]. 情报学报, 2019, 38(12): 1320-1328.
ZHAO D X, MA F C, ZHANG Q P. Exploring the health information seeking behavior of older adults in urban China: A phenomenological study[J]. Journal of the China society for scientific and technical information, 2019, 38(12): 1320-1328.
7
朱庆华, 杨梦晴, 赵宇翔, 等. 健康信息行为研究: 溯源、范畴与展望[J]. 中国图书馆学报, 2022, 48(2): 94-107.
ZHU Q H, YANG M Q, ZHAO Y X, et al. Health information behavior: History, category and prospect[J]. Journal of library science in China, 2022, 48(2): 94-107.
8
宋士杰, 齐云飞, 赵宇翔, 等. 冲突性健康信息对用户健康信息搜寻的影响: 基于不确定性视角的探究[J]. 图书情报工作, 2021, 65(11): 24-32.
SONG S J, QI Y F, ZHAO Y X, et al. The impact of conflicting health information in consumers' health information seeking: An investigation of uncertainty[J]. Library and information service, 2021, 65(11): 24-32.
9
周晓英, 蔡文娟. 大学生网络健康信息搜寻行为模式及影响因素[J]. 情报资料工作, 2014(4): 50-55.
ZHOU X Y, CAI W J. Universities students online health information seeking behavior patterns and influencing factors[J]. Information and documentation services, 2014(4): 50-55.
10
邓胜利, 付少雄, 陈晓宇. 信息传播媒介对用户健康信息搜寻的影响研究——基于健康素养和信息检索能力的双重视角[J]. 情报科学, 2017, 35(4): 126-132.
DENG S L, FU S X, CHEN X Y. The role of information media on user health information seeking - Based on health literacy and information retrieval capability perspectives[J]. Information science, 2017, 35(4): 126-132.
11
THEIS S, SCHÄFER K, SCHÄFER D, et al. The relationship between individual coping and the need to have and seek health information among older adults: Exploratory mixed methods study[J]. JMIR human factors, 2021, 8(1): e15858.
12
赵文军, 孟凯, 马锦辉, 等. 基于DEMATEL-ISM的在线健康信息搜寻行为影响因素研究——来自国内外实证研究的元分析[J]. 信息资源管理学报, 2023, 13(2): 53-66, 80.
ZHAO W J, MENG K, MA J H, et al. Influencing factors of online health information searching behavior based on DEMATEL-ISM: From a meta-analysis of empirical studies at home and abroad[J]. Journal of information resources management, 2023, 13(2): 53-66, 80.
13
朱云琴, 陈渝. 双路径视角下在线健康社区用户健康信息搜寻行为影响因素研究[J]. 图书馆杂志, 2022, 41(10): 83-96.
ZHU Y Q, CHEN Y. Research on influencing factors of users' health information seeking behavior in online health community based on the perspective of dual paths[J]. Library journal, 2022, 41(10): 83-96.
14
刘嫣, 张海涛, 李佳玮, 等. 移动终端视角下的老年用户在线健康信息搜寻行为影响因素研究[J]. 图书情报工作, 2021, 65(11): 46-54.
LIU Y, ZHANG H T, LI J W, et al. Research on influencing factors of online health information search behaviors of elderly users from the perspective of mobile terminals[J]. Library and information service, 2021, 65(11): 46-54.
15
刘嫣, 张海涛, 张鑫蕊, 等. 基于元分析的用户在线健康信息搜寻行为影响因素研究[J]. 情报科学, 2022, 40(2): 169-176.
LIU Y, ZHANG H T, ZHANG X R, et al. Influencing factors of users' online health information seeking behavior based on meta-analysis[J]. Information science, 2022, 40(2): 169-176.
16
相甍甍, 孙畹婷, 王晰巍, 等. 在线健康社区用户复合信息行为的实证研究——信息共享和信息搜寻同步的视角[J]. 情报科学, 2022, 40(7): 111-119, 135.
XIANG M M, SUN W T, WANG X W, et al. Recognition and prediction of emerging topics in interdisciplinary scientific research collaboration based on scits conference text[J]. Information science, 2022, 40(7): 111-119, 135.
17
周培宇, 梁昌勇, 马一鸣. COVID-19背景下基于IMB模型的中老年人在线健康信息搜寻行为影响机制研究[J]. 中国管理科学, 2022, 30(3): 76-84.
ZHOU P Y, LIANG C Y, MA Y M. Research on the influence mechanism of online health information seeking behavior of middle-aged and older adults based on the IMB model in the context of COVID-19[J]. Chinese journal of management science, 2022, 30(3): 76-84.
18
POURRAZAVI S, HASHEMIPARAST M, BAZARGAN-HEJAZI S, et al. Why older people seek health information online: A qualitative study[J]. Advances in gerontology, 2021, 11(3): 290-297.
19
ZHAO Y C, ZHAO M Y, SONG S J. Online health information seeking behaviors among older adults: Systematic scoping review[J]. Journal of medical Internet research, 2022, 24(2): e34790.
20
BACHOFNER Y, SEIFERT A, SEPAHNIYA S, et al. Exploring online health information seeking and sharing among older adults: A mini-review about acceptance, potentials, and barriers[J]. Frontiers in digital health, 2024, 6: 1336430.
21
XU Z X, CHEN L, DAI Y M, et al. A dynamic topic model and matrix factorization-based travel recommendation method exploiting ubiquitous data[J]. IEEE transactions on multimedia, 2017, 19(8): 1933-1945.
22
GAO Q, HUANG X, DONG K, et al. Semantic-enhanced topic evolution analysis: A combination of the dynamic topic model and word2vec[J]. Scientometrics, 2022, 127(3): 1543-1563.
23
吴瑞鹏, 李勇男, 刘帅, 等. 基于DTM的美国人工智能战略热点主题及演化分析[J]. 情报杂志, 2023,42(12): 134-143.
WU R P, LI Y N, LIU S, et al. DTM - based analysis of hot topics and evolution of American artificial intelligence strategy[J]. Journal of intelligence, 2023,42(12): 134-143.
24
吕鲲, 项旻昊, 靖继鹏. 基于LDA2Vec和DTM模型的颠覆性技术主题识别研究——以能源科技领域为例[J]. 图书情报工作, 2023, 67(12): 89-102.
LV K, XIANG M H, JING J P. Identification of disruptive technology topics based on LDA2Vec and DTM models: A case study in the energy technology field[J]. Library and information service, 2023, 67(12): 89-102.
25
邱均平, 胡博, 徐中阳, 等. 基于DTM模型的国内外话语权研究主题挖掘及比较分析[J]. 情报理论与实践, 2023, 46(2): 24-34.
QIU J P, HU B, XU Z Y, et al. Topic mining and comparative analysis of discourse power research in China and overseas based on DTM model[J]. Information studies: Theory & application, 2023, 46(2): 24-34.
26
黄飞虎, 彭舰, 宁黎苗. 基于信息熵的社交网络观点演化模型[J]. 物理学报, 2014, 63(16): 160501.
HUANG F H, PENG J, NING L M. Opinion evolution model of social network based on information entropy[J]. Acta physica sinica, 2014, 63(16): 160501.
27
李根强, 刘莎, 张亚楠, 等. 信息熵理论视角下网络集群行为主体的观点演化研究[J]. 情报科学, 2020, 38(1): 42-47, 86.
LI G Q, LIU S, ZHANG Y N, et al. Research on the opinion evolution in online collective behavior from the perspective of information entropy[J]. Information science, 2020, 38(1): 42-47, 86.
28
许子媛. 基于信息熵的图书馆联盟风险分析评价模型构建[J]. 情报科学, 2016, 34(4): 23-28.
XU Z Y. Building of the analysis and evaluation model of the library consortia risk based on information entropy[J]. Information science, 2016, 34(4): 23-28.
29
郝桂荣. 基于信息熵-AHP组合权重系数的图书馆服务质量多层次模糊综合评判研究[J]. 现代情报, 2010, 30(2): 133-136, 141.
HAO G R. Study on multi-leve fuzzy integrative evaluation based on entropy weigh and AHP's combined weight coefficient on library service quality evaluation[J]. Journal of modern information, 2010, 30(2): 133-136, 141.
30
赵兴旺, 梁吉业. 一种基于信息熵的混合数据属性加权聚类算法[J]. 计算机研究与发展, 2016, 53(5): 1018-1028.
ZHAO X W, LIANG J Y. An Attribute weighted clustering algorithm for mixed data based on information entropy[J]. Journal of computer research and development, 2016, 53(5): 1018-1028.
31
中华人民共和国中央人民政府.关于全面加强老年健康服务工作的通知[EB/OL]. [2024-03-23].
32
中华人民共和国中央人民政府. 关于进一步优化新冠肺炎疫情防控措施 科学精准做好防控工作的通知[EB/OL]. [2024-03-23].
33
国家市场监督管理总局. 且看不法分子坑人的“三十六计”——全国打击整治养老诈骗专项行动典型案例及背后养老诈骗“套路”分析解读[EB/OL]. [2024-03-23].
34
中华人民共和国中央人民政府. 关于开展全民健康素养提升三年行动(2024-2027年)的通知[EB/OL]. [2024-03-23].
35
中华人民共和国中央人民政府. 《关于建立完善老年健康服务体系的指导意见》政策解读[EB/OL]. [2024-03-23].
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