RESEARCH PAPERS

Research on User Participation Patterns in Online Health Communities from a Symbiosis Theory Perspective

  • Bi Chongwu ,
  • Yang Jingjing ,
  • Jin Yan ,
  • Sun Zhuo
Expand
  • 1 School of Information Management, Zhengzhou University, Zhengzhou 450001;
    2 Zhengzhou Data Science Research Center, Zhengzhou 450001;
    3 School of Politics and Public Administration, Zhengzhou University, Zhengzhou 450001
Bi Chongwu, associate professor, master supervisor; Yang Jingjing, master candidate; Jin Yan, professor, doctoral supervisor; Sun Zhuo, associate researcher, corresponding author, E-mail: sunzhuo@zzu.edu.cn.

Received date: 2024-04-17

  Revised date: 2024-08-19

  Online published: 2025-02-26

Supported by

This work is supported by the youth project of National Social Science Fund of China, titled “Research on Common View Governance Model of Online Public Opinion for Emergencies Enabled by Data Portrait” (Grant No. 23CTQ015).

Abstract

[Purpose/Significance] Analyzing the user participation patterns in online health communities from a symbiosis theory perspective can help understand the complex interactive relationships in these communities and provides references for improving their management mechanisms. [Method/Process] Firstly, representative data of user participation in Zhihu’s health communities were selected and coded on the grounded theory to identify the behavioral patterns of user participation. Secondly, based on symbiosis theory, the patterns of user participation in online health communities were constructed, exploring the roles, motivations, paths, and modes of user participation in symbiotic scenarios. Finally, combining different modes of user participation, the symbiotic states and behaviors of users were analyzed from a dynamic perspective. [Result/Conclusion] Under the dual effects of self-organization and hetero-organization, the roles of lurkers, bystanders, creators, and evaluators intersect in online health communities along consumption-driven, creation-driven, and interaction-driven paths, generating singular, diverse, and interactive modes of participation. User symbiotic states initially transition from parasitism and biased parasitism to asymmetrical mutualistic relationships, then to mutualistic relationships, ultimately achieving a balance between conflict and cooperation in online health communities.

Cite this article

Bi Chongwu , Yang Jingjing , Jin Yan , Sun Zhuo . Research on User Participation Patterns in Online Health Communities from a Symbiosis Theory Perspective[J]. Library and Information Service, 2025 , 69(4) : 53 -66 . DOI: 10.13266/j.issn.0252-3116.2025.04.005

References

[1] 赵栋祥. 国内在线健康社区研究现状综述[J]. 图书情报工作, 2018, 62(9): 134-142. (ZHAO D X. Review on domestic research status of online health community [J]. Library and information service, 2018, 62(9): 134-142.)
[2] CALDER B J, STAW B M. Self-perception of intrinsic and extrinsic motivation[J]. Journal of personality and social psychology, 1975, 31(4): 599.
[3] WANG Y C, FESENMAIER D R. Towards understanding members general participation in and active contribution to an online travel community[J]. Tourism management, 2004, 25(6): 709-722.
[4] PAPACHARISSI Z. The self online: the utility of personal home pages[J]. Journal of broadcasting & electronic media, 2002, 46(3): 346-368.
[5] FULLWOOD C, CHADWICK D, KEEP M, et al. Lurking towards empowerment: explaining propensity to engage with online health support groups and its association with positive outcomes [J]. Computers in human behavior, 2019, 90: 131-140.
[6] 张李义, 李慧然. 基于互动视角的在线医疗问答患者用户使用研究[J]. 数据分析与知识发现, 2018, 2(1): 76-87. (ZHANG L Y, LI H R. Studying social interaction of online medical question-answering service[J]. Data analysis and knowledge discovery, 2018, 2(1): 76-87.)
[7] TLJ A, EDVC A, PAMPLIN R B, et al. The mediating role of group dynamics in shaping received social support from active and passive use in online health communities[J]. Elsevier science publishers B. V., 2022, 59(3): 15.
[8] STRAGIER J, ABEELE M V, MECHANT P, et al. Understanding persistence in the use of online fitness communities: comparing novice and experienced users[J]. Computers in human behavior, 2016, 64:34-42.
[9] 翟羽佳, 张鑫, 王芳. 在线健康社区中的用户参与行为——以“百度戒烟吧”为例[J]. 图书情报工作, 2017, 61(7): 75-82. (ZHAN Y J, ZHANG X, WANG F. User engagement in online health communities: taking Baidu quitting smoking post bar as an example[J]. Library and information service, 2017, 61(7): 75-82.)
[10] CONNOLLY R, SANCHEZ O P, COMPEAU D, et al. Understanding engagement in online health communities: a trust-based perspective[J]. Assoc information systems, 2023, 2(24): 345-378.
[11] 董庆兴, 周欣, 毛凤华, 等. 在线健康社区用户持续使用意愿研究基于感知价值理论[J], 现代情报, 2019, 39(3): 3-14, 156. (DONG Q X, ZHOU X, MAO F H, et al. An investigation on the users’ continuance intention in online health community: based on perceived value theory[J]. Journal of modem information, 2019, 39(3): 3-14, 156.)
[12] 袁静, 郭玲玉. 在线健康社区用户非持续使用行为影响因素分析[J]. 现代情报, 2022, 42(2): 81-93. (YUAN J, GUO L Y. Influencing factors analysis of discontinuous use behaviors of users on online health communities[J]. Journal of modem information, 2022, 42(2): 81-93.)
[13] 张薇薇, 蒋雪. 在线健康社区用户持续参与动机的演变机理研究[J]. 管理学报, 2020, 17(8): 1245-1253. (ZHANG W W, JIANG X. Research on motivational evolution mechanism of users’continuous participation in online health communities[J]. Chinese journal of management, 2020, 17(8): 1245-1253.)
[14] 姚志臻, 张斌. 激励机制下在线健康社区用户参与行为演化博弈分析[J]. 情报科学, 2021, 39(8): 149-155, 163. (YAO Z Z, ZHANG B. Evolutionary game analysis of users’ participation behavior in online health community under incentive mechanism[J]. Information science, 2021, 39(8): 149-155, 163.)
[15] 王艳, 邓小昭. 网络用户信息行为基本问题探讨[J]. 图书情报工作, 2009, 53(16): 35-39. (WANG Y, DENG X Z. The discussion about fundamental issues of Internet users’ information behavior[J]. Library and information service, 2009, 53(16): 35-39.)
[16] 张鑫. 在线健康社区用户参与行为的类型及偏好研究[J]. 情报资料工作, 2019, 40(5): 84-91. (ZHANG X. Research on types and preferences of user participation behavior in online community[J]. Information and documentation services, 2019, 40(5): 84-91.)
[17] BROWN L K, VEINOT T. Information behavior and social control: toward an understanding of conflictual information behavior in families managing chronic illness[J]. Journal of the Association for Information Science and Technology, 2020(72): 66-82.
[18] 盛姝, 黄奇, 郑姝雅, 等. 在线健康社区中用户画像及主题特征分布下信息需求研究——以医享网结直肠癌圈数据为例[J]. 情报学报, 2021, 40(3): 308-320. (SHEN Z, HUANG Q, ZHENG Z Y, et al. Study of user information requirements in an online health community based on the distribution of user profile and theme features: taking colorectal cancer data from medicenjoy as an example[J]. Journal of the China Society for Scientific and Technical Information, 2021, 40(3): 308-320.)
[19] 徐孝婷, 赵宇翔, 朱庆华. 在线健康社区老年用户健康信息需求实证研究[J]. 图书情报工作, 2019, 63(10): 87-96. (XU X T, ZHAO Y X, ZHU Q H. An empirical study on health information needs of elderly users in online health communities[J]. Library and information service, 2019, 63(10): 87-96.)
[20] 成全, 郑抒琳. 在线健康社区用户信息需求的层级多标签分类研究[J]. 情报理论与实践, 2023, 46(2): 100-108. (CHENG Q, ZHENG S L. Research on hierarchical multi-label classification of user information demand in online health community[J]. Information studies: theory & application, 2023, 46(2): 100-108.)
[21] SHNEIDERMAN B. Technology-mediated social participation: the next 25 years of HCI challenges[C]//Proceedings of the 14th international conference on human-computer interaction: design and development approaches-Volume Part I. Berlin: Springer, 2011: 3-14.
[22] 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[J]. 情报学报, 2017, 36(11): 1183-1191. (WU J, HOU S X, XIN M M, et al. LDA feature selection based text classification and user clustering in Chinese online health community[J]. Journal of the China Society for Scientific and Technical Information, 2017, 36(11): 1183-1191.)
[23] 周军杰. 用户在线参与的行为类型——基于在线健康社区的质性分析[J]. 管理案例研究与评论, 2016, 9(2): 173-184. (ZHOU J J. Examining the users’ participation behavior types-qualitative analysis based on online health community[J]. Journal of management case studies, 2016, 9(2): 173-184.)
[24] MO P K, COULSON N S. Empowering processes in online support groups among people living with HIV/AIDS: a comparative analysis of ‘lurkers’ and ‘posters’[J]. Computers in human behavior, 2010, 26(5): 1183-1193.
[25] 许云红, 李仕林, 许云丽. 在线健康社区不同级别用户的参与行为研究:基于增长模型视角[J]. 情报杂志, 2020, 39(8): 137-144. (XU Y H, LI S L, XU Y L. Participation behavior of users with different level ranks in online health communities: a growth model perspective[J]. Journal of intelligence, 2020, 39(8): 137-144.)
[26] YAN L, TAN Y. Feeling blue? go online: an empirical study of social support among patients[J]. Information systems research, 2014, 25(4): 690-709.
[27] 周涛, 王盈颖, 邓胜利. 基于社会资本理论的在线健康社区用户参与行为研究[J]. 信息资源管理学报, 2020, 10(2): 59-67, 129. (ZHOU T, WANG Y L, DENG S L. Research on online health community users’ participation based on social capital theory[J]. Journal of information resources management, 2020, 10(2): 59-67, 129.)
[28] 张帅, 王文韬, 谢阳群. 在线健康社区用户持续参与行为的演化规律及动力机制[J]. 现代情报, 2021, 41(5): 59-66. (ZHANG S, WANG W T, XIE Y Q. Evolutionary regularity and dynamic mechanism of online health community users’ continuous participation behavior[J]. Journal of modern information, 2021, 41(5): 59-66.)
[29] CORLISS J O, MARGULIS L. Origin of eukaryotic cells[J]. Transactions of the American Microscopical Society, 1970, 37(3): 59-66.
[30] 袁纯青. 共生理论——兼论小型经济[M]. 北京:经济科学出版社, 1998. (YUAN CH Q. Symbiosis theory: also on small economy[M]. Beijing: Economic Science Press, 1998.)
[31] 左菲菲. 基于共生理论的高校图书馆知识服务模式构建[J]. 图书情报工作, 2012, (S2): 134-136. (ZUO F F. Construction of knowledge service model of university library based on symbiosis theory[J]. Library and information service, 2012, (S2): 134-136.)
[32] 袁静, 李森涛, 高晓宁.图书馆智慧服务共生模式的实现机理研究[J]. 图书与情报, 2023(4): 64-77. (YUAN J, LI S T, GAO X N. Research on the realization mechanism of symbiosis model of library smart services[J]. Library and information, 2023(4): 64-77.)
[33] FRASGUET-DELTORO M. ALARC Ó N-DEL-AMO M, LORENZO-ROMERO C. Antecedents and consequences of virtual customer cocreation behaviors[J]. Internet research, 2018, 29(1): 218-244.
[34] LIAO J, HUANG M, XIAO B. Promoting continual member participation in firm-hosted online brand communities: an organizational socialization approach[J]. Journal of business research, 2017, 71: 92-101.
[35] 谭春辉, 王仪雯, 郭洋. 基于共生理论的虚拟学术社区科研合作稳定性研究[J]. 现代情报, 2021, 41(3): 15-28. (TAN C H, WANG Y W, GUO Y. Research on the stability of scientific research cooperation in virtual academic community based on symbiosis theory[J]. Journal of modern information, 2021, 41(3): 15-28.)
[36] SONG X, JIANG S, YAN X, et al. Collaborative friendship networks in online healthcare communities: an exponential random graph model analysis[C]// Proceedings of the international conference for smart health. Berlin: Springer, 2014, 8549.
[37] 易明, 刘继月, 傅航. 共生视角下的在线健康社区知识共创演化机理研究[J]. 情报理论与实践, 2024, 47(9): 134-146. (YI M, LIU J Y, FU H. Study on the evolutionary mechanism of knowledge co-creation in online health communities from a symbiotic perspective[J]. Information studies: theory& application, 2024, 47(9): 134-146.)
[38] 张薇薇, 王昊, 朱晓东. 互联网用户协同创作与内容共享的活动系统研究[J]. 中国图书馆学报, 2011, 37(4): 27-37. (ZHANG W W, WANG H, ZHU X D, Research on the activity system of collaborative creation and content sharing of Internet users[J]. Journal of library science in China, 2011, 37(4): 27-37.)
[39] 韩正彪.周鹏. 扎根理论质性研究方法在情报学研究中的应用[J]. 情报理论与实践, 2011, 34(5): 19-23. (HAN Z B, ZHOU P. Application of grounded theory qualitative research methods in information science research[J]. Information studies: theory& application, 2011, 34(5): 19-23.)
[40] ZIMMERMAN S, THORPE A, FOX C, et al. Investigating the interplay between searchers’ privacy concerns and their search behavior[C]//Proceedings of the 42nd international ACM SIGIR conference on research and development in information retrieval. New York: ACM, 2019: 953-956.
[41] 霍兰. 涌现—从混沌到有序[M]. 陈禹, 方美琪, 译.上海:上海科技出版社, 2001. (HOLLAND J. Emergence: from chaos to order[M]. CHEN Y, FANG M Q, trans. Shanghai: Shanghai Science and Technology Press, 2001.)
[42] RUPERT M, RATTROUT A, HASSAS S. The web from a complex adaptive systems perspective[J]. Journal of computer and system sciences, 2008, 74(2): 133-145.
[43] NAMBISAN P. Information seeking and social support in online health communities: impact on patients’ perceived empathy[J]. Journal of the American Medical Informatics Association, 2011, 18(3): 298-304.
[44] 刘春茂, 米国伟. 基于Web 2.0的网络用户群“社会性”行为的系统分析[J]. 图书情报工作, 2010, 54(20): 32-35, 85. (LIU C M, MI G W. Systematic analysis on ‘sociality’ behavior of networked group users under Web 2.0 environment[J]. Library and information service, 2010, 54(20): 32-35, 85.)
[45] BAK-COLEMAN J B, ALFANO M, BARFUSS W, et al. Stewardship of global collective behavior[J]. Proceedings of the National Academy of Sciences, 2021, 118(27): e2025764118.
Outlines

/

〈 〉