Research on Knowledge Sharing Behaviors of Online Health Community Users

doi:10.12341/jssms22025ZX

Online health community has become an important platform for patients and their families to obtain health knowledge, the information service quality of the community can be enhanced by exploring the knowledge sharing behaviors of different types of users. Article based on the theory of knowledge collaborative construction, the user interaction network and knowledge network are constructed, based on the algorithms of the identification of key users and the discovery of key paths, the rules of knowledge sharing behavior are mined. This paper takes the community of biliary cancer as an example to carry out an empirical study, the results show that the knowledge interaction behavior model across multiple communities is formed under the guidance of key users, and ordinary users tend to interact with other users with the same disease types in the community. The knowledge sharing of key users focuses on preoperative examination and disease symptoms knowledge types, while the knowledge sharing of ordinary users focuses on preoperative examination knowledge types; The key knowledge paths reflect the knowledge needs of users in different stages of disease treatment.

Key words: Online health community, knowledge sharing, collaborative knowledge building, network coupling, knowledge path

CLC Number:

91B50

[1] 中国互联网络信息中心(CNNIC).第47次中国互联网络发展状况统计报告.[2021-02-03].http://www.cnnic.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t2021020371361.htm.(China Internet Network Information Center (CNNIC).The 47th Statistical Report on China's Internet Development.[2021-02-03].http://www.cnnic.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t2021020371361.htm.)
[2] 吴江,周露莎.在线医疗社区中知识共享网络及知识互动行为研究.情报科学, 2017, 35(3):144-151.(Wu J, Zhou L S.Research on knowledge sharing network and knowledge interaction behavior in online medical communities.Intelligence Science, 2017, 35(3):144-151.)
[3] 周涛,王盈颖,邓胜利.在线健康社区用户知识分享行为研究.情报科学, 2019, 37(4):72-78.(Zhou T, Wang Y Y, Deng S L.A study on users'knowledge sharing behavior in online health communities.Intelligence Science, 2019, 37(4):72-78.)
[4] 周涛,何莲子,邓胜利.开放式创新社区用户知识分享的影响因素研究.现代情报, 2020, 40(3):58-64.(Zhou T, He L Z, Deng S L.Research on the influencing factors of user knowledge sharing in open innovation communities.Modern Intelligence, 2020, 40(3):58-64.)
[5] 邓朝华,蒙江.在线医疗健康社区知识共享行为研究.第十五届全国计算机模拟与信息技术学术会议论文集, 2015, 39-48.(Deng C H, Meng J.Research on knowledge sharing behavior of online medical and health communities.Proceedings of the 15th National Conference on Computer Simulation and Information Technology, 2015, 39-48.)
[6] Yan Z, Wang T, Chen Y, et al.Knowledge sharing in online health communities:A social exchange theory perspective.Information&Management, 2016, 53(5):643-653.
[7] 吴江,侯绍新,靳萌萌,等.基于LDA模型特征选择的在线医疗社区文本分类及用户聚类研究.情报学报, 2017, 36(11):1183-1191.(Wu J, Hou S X, Jin M M, et al.Research on text classification and user clustering of online medical communities based on LDA model feature selection.Journal of Intelligence, 2017, 36(11):1183-1191.)
[8] 吴江,施立.基于社会网络分析的在线医疗社区用户交互行为研究.情报科学, 2017, 35(7):120-125.(Wu J, Shi L.Research on user interaction behavior of online medical communities based on social network analysis.Intelligence Science, 2017, 35(7):120-125.)
[9] 赵雪芹,王青青,蔡铨.网络问答社区意见领袖的知识分享行为特征分析——以知乎"旅行"话题为例.情报科学,2021, 39(6):68-74.(Zhao X Q, Wang Q Q, Cai Q.Analysis of knowledge sharing behavior characteristics of opinion leaders in online Q&A community-taking the topic of "travel" in Zhihu as an example.Information Science, 2021, 39(6):68-74.)
[10] 岳丽欣,周晓英,刘自强.科学知识网络扩散中的社区扩张与收敛模式特征分析——以医疗健康信息领域为例.图书情报工作, 2020, 64(14):63-73.(Yue L X, Zhou X Y, Liu Z Q.Characterization of community expansion and convergence patterns in the diffusion of scientific knowledge networks:An example in the field of medical and health information.Library and Information Work, 2020, 64(14):63-73.)
[11] 陆泉,朱安琪,张霁月,等.中文网络健康社区中的用户信息需求挖掘研究——以求医网肿瘤板块数据为例.数据分析与知识发现, 2019, 3(4):22-32.(Lu Q, Zhu A Q, Zhang J Y, et al.A study of user information needs mining in Chinese online health communities:An example of tumor board data on Seeking Medical Care.Data Analysis and Knowledge Discovery, 2019, 3(4):22-32.)
[12] 范昊,张玉晨,吴川徽.网络健康社区中健康信息传播网络及主题特征研究.情报科学, 2021, 39(1):4-12, 34.(Fan H, Zhang Y C, Wu C H.Research on health information dissemination networks and thematic characteristics in online health communities.Intelligence Science, 2021, 39(1):4-12, 34.)
[13] 廖开际,黄琼影,席运江.在线医疗社区问答文本的知识图谱构建研究.情报科学, 2021, 39(3):51-59, 75.(Liao K J, Huang Q Y, Xi Y J.Research on knowledge graph construction of question and answer texts in online medical communities.Intelligence Science, 2021, 39(3):51-59, 75.)
[14] 翟姗姗,胡畔,潘英增,等.融合知识图谱与用户病情画像的在线医疗社区场景化信息推荐研究.情报科学, 2021, 39(5):97-105.(Zhai S S, Hu B, Pan Y Z, et al.Research on scenario-based information recommendation for online medical communities by fusing knowledge graph and user condition portraits.Intelligence Science, 2021, 39(5):97-105.)
[15] Scardamalia M, Bereiter C.Knowledge Building:Theory, Pedagogy, and Technology, 2006.
[16] Stahl G.A model of collaborative knowledge-building.Fourth International Conference of the Learning Sciences, Mahwah, NJ:Erlbaum, 2000, 10:70-77.
[17] 潘旭伟,杨#
[38],王世雄,等.知识协同视角下Wiki知识网络的特性研究——以Wikipedia为例.情报学报, 2013, 32(8):817-827.(Pan X W, Yang Y, Wang S X, et al.A study on the characteristics of Wiki knowledge network from the perspective of knowledge collaboration, taking Wikipedia as an example.Journal of Intelligence, 2013, 32(8):817-827.)
[18] 郗强,唐锡晋.在线辩论网络中的互动行为分析.系统科学与数学, 2019, 2019, 39(9):1361-1377.(Xi Q, Tang X J.Analysis of interaction behavior in online debate networks.Journal of Systems Science and Mathematical Sciences, 2019, 39(9):1361-1377.)
[19] 张军,李新旺,李鹏.多维属性融合视角下的在线健康社区关键用户识别研究.情报科学, 2022, 40(3):82-90.(Zhang J, Li X W, Li P.Research on key user identification of online health communities from the perspective of multidimensional attribute fusion.Intelligence Science, 2022, 40(3):82-90.)
[20] Hsu C C, Lai Y A, Chen W H, et al.Unsupervised ranking using graph structures and node attributes.Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017, 771-779.
[21] 唐磊,刘欢,文益民,等.社会计算:社区发现和社会媒体挖掘.北京:机械工业出版社, 2012.(Tang L, Liu H, Wen Y M, et al.Social Computing:Community Discovery and Social Media Mining.Beijing:Machinery Industry Press, 2012.)
[22] Newman M E J, Girvan M.Finding and evaluating community structure in networks.Physical Review E, 2004, 69(2):026113.

[1]	LU Wencong, QI Huibo, LI Yuanlong. CHINESE WORLD AGRICULTURAL REGIONAL MARKET EQUILIBRIUM MODEL AND ITS APPLICATION [J]. Journal of Systems Science and Mathematical Sciences, 2013, 33(1): 20-35.
[2]	WANG Huifang;JIANG Xuemei;XU Shanying. ANALYSIS OF EXPORT TAX REBATE POLICY OF CHINA BASED ON COMPUTABLE GENERAL EQUILIBRIUM MODEL [J]. Journal of Systems Science and Mathematical Sciences, 2011, 31(3): 354-360.

Viewed

Full text

Abstract