Interactive Behaviors of Online Health Community Users in Emergency
Zhe Hu1,2,Xianjin Zha1(),Yalan Yan3
1 School of Information Management, Wuhan University, Wuhan 430072, China 2 Laboratory Center for Library and Information Science, Wuhan University, Wuhan 430072, China 3 Evergrande School of Management, Wuhan University of Science and Technology, Wuhan 430065, China
[Objective] This study explores the interactive behaviors of online health community users in emergency. [Methods] Firstly, we constructed a directed matrix based on the posts and replies and illustrated the structure of this interactive network. Then, we conducted a small-world, and correlation analysis for the centrality index, structural hole index and user interactive behaviors respectively. [Results] The whole network had a small-world effect. The eigenvector centrality had significant positive correlation with the number of posts and the degree centrality had significant positive correlation with the number of replies. Meanwhile, structural holes had significant positive correlations with the number of replies. [Limitations] The data types were not diversified. [Conclusions] This study provides useful references and guidelines for the development of online health communities.
胡哲,查先进,严亚兰. 突发事件情境下在线健康社区用户交互行为研究 *[J]. 数据分析与知识发现, 2019, 3(12): 10-20.
Zhe Hu,Xianjin Zha,Yalan Yan. Interactive Behaviors of Online Health Community Users in Emergency. Data Analysis and Knowledge Discovery, 2019, 3(12): 10-20.
Maloney-Krichmar D, Preece J . A Multilevel Analysis of Sociability, Usability, and Community Dynamics in an Online Health Community[J]. ACM Transactions on Computer-Human Interaction, 2005,12(2):201-232.
( Zhang Jing, Guo Wei, Wang Lei , et al. The Influence of User Interaction on the Cognition and Diffusion of Products Knowledge and Community Incentive Research[J]. Science & Technology Progress and Policy, 2018,35(16):7-15.)
[3]
Khobzi H, Lau R Y K, Cheung T C H . The Outcome of Online Social Interactions on Facebook Pages: A Study of User Engagement Behavior[J]. Internet Research, 2019,29(1):2-23.
[4]
Fang J M, Li J, Prybutok V R . Posting-Related Attributes Driving Differential Engagement Behaviors in Online Travel Communities[J]. Telematics and Informatics, 2018,35(5):1263-1276.
[5]
项惠惠 . 在线社交媒体中用户信息传播行为预测研究[D]. 南京: 南京邮电大学, 2018.
[5]
( Xiang Huihui . Research on the Prediction of Users’ Information Transmission Behavior in Online Social Networks: Taking Micro-blog Users as an Example[D]. Nanjing: Nanjing University of Posts and Telecommunications, 2018.)
[6]
Wang C, Li Q, Wang L , et al. Incorporating Message Embedding into Co-factor Matrix Factorization for Retweeting Prediction [C]//Proceedings of the 2017 International Joint Conference on Neural Networks. IEEE, 2017: 1265-1272.
( Qi Yunfei, Zhang Yue, Zhu Qinghua . Information Interaction Behavior of Users in Social Q&A Community from the Perspective of Information Ecology Chain[J]. Information Studies: Theory & Application, 2018,41(12):1-7, 26.)
( Deng Shengli . Research Model of Network User Information Interaction Behavior[J]. Information Studies: Theory & Application, 2015,38(12):53-56, 87.)
( Wang Xuefen, Zhu Qinghua, Chang Liyan , et al. Characteristics of User Interaction Behaviors in Virtual Job-hunting Communities——Taking Ying Jie Sheng BBS as an Example[J]. Library and Information Service, 2018,62(10):62-69.)
[10]
Bonchi F, Castillo C, Gionis A , et al. Social Network Analysis and Mining for Business Applications[J]. ACM Transactions on Intelligent Systems and Technology, 2011, 2(3): Article No. 22.
[11]
Nepal S, Paris C, Pour P A , et al. Interaction-Based Recommendations for Online Communities[J]. ACM Transactions on Internet Technology, 2015,15(2):14-24.
( Wang Xiwei, Wei Ya’nan, Xing Yunfei , et al. Research on Enterprises and Users Information Interaction Behavior Model and Characteristics in New Media Environment[J]. Library and Information Service, 2018,62(18):6-15.)
( Zhang Jidong, Yang Yang . Measurement Model of Mobile Social Network Users’ Influence Based on Interactive Behavior and Emotional Tendency[J]. Information Studies: Theory & Application, 2019,42(1):112-117, 93.)
( Zhang Fengjuan, Wang Meng, Zhou Gang . Analysis of User Influence in Microblog Based on Activity Network[J]. Computer Technology and Development, 2018,28(9):162-167, 171.)
( Chen Fen, Fu Xi, He Yuan , et al. Identifying Weibo Opinion Leaders with Social Network Analysis and Influence Diffusion Model[J]. Data Analysis and Knowledge Discovery, 2018,2(12):60-67.)
( Wang Zhongyi, Zhang Heming, Huang Jing , et al. Studying Knowledge Dissemination of Online Q&A Community with Social Network Analysis[J]. Data Analysis and Knowledge Discovery, 2018,2(11):80-94. )
[18]
Van Der Eijk M, Faber M J, Aarts J W M , et al. Using Online Health Communities to Deliver Patient-Centered Care to People with Chronic Conditions[J]. Journal of Medical Internet Research, 2013,15(6):190-200.
( Zhang Xing, Chen Xing, Hou Delin . An Analysis of Online Health Information Disclosure Willingness Influencing Factors: An Integrated Model of TPB and Privacy Calculus[J]. Information and Documentation Services, 2016,37(1):48-53.)
( Wang Wentao, Xie Yangqun, Liu Kunfeng . Research on Virtual Health Community Users Willingness Based on Grounded Theory[J]. Information and Documentation Services, 2017,38(3):75-82.)
( Yang Hualong, Ju Xiaofeng . The Effects of Social Support and Individual Goal on Health Condition[J]. Journal of Management Science, 2017,30(1):53-61.)
[24]
吕英杰 . 网络健康社区中的文本挖掘方法研究[D]. 上海: 上海交通大学, 2013.
[24]
( Lv Yingjie . Research on Text Mining in Online Health Community[D]. Shanghai: Shanghai Jiao Tong University, 2013.)
[25]
Oh S . The Characteristics and Motivations of Health Answers for Sharing Information, Knowledge, and Experiences in Online Environments[J]. Journal of the American Society for Information Science and Technology, 2012,63(3):543-557.
( Hou Guisheng, Wang Pengmin, Yang Lei . Research on Evolutionary Game of the Knowledge Conversion and Sharing of Online Health Community Users[J]. Information Science, 2017,35(7):31-38.)
[27]
Chen C J, Hung S W . To Give or to Receive? Factors Influencing Members’ Knowledge Sharing and Community Promotion in Professional Virtual Communities[J]. Information & Management, 2010,47(4):226-236.
( Wu Jiang, Zhou Lusha . The Study of Knowledge Sharing Network and Users’ Knowledge Interaction in Online Health Community[J]. Information Science, 2017,35(3):144-151.)
( Wang Shuyao . Network Characters and Social Support in Network Community for Health Communication[D]. Shanghai: Shanghai Jiao Tong University, 2015.)
[30]
Centola D . The Spread of Behavior in an Online Social Network Experiment[J]. Science, 2010,329(5996):1194-1197.
[31]
Ba S, Wang L . Digital Health Communities: The Effect of Their Motivation Mechanisms[J]. Decision Support Systems, 2013,55(4):941-947.
( Liu Xuan, Wang Linwei, Li Jia , et al. Research on Mechanisms of User Replying Behaviors in Online Health Communities[J]. Journal of Management Science, 2017,30(1):62-72.)
[33]
Wang X, Zhao K . Social Support and User Engagement in Online Health Communities [C]//Proceedings of the 2014 International Conference for Smart Health (ICSH). Springer International Publishing, 2014: 97-110.
( Zhai Yujia, Zhang Xin, Wang Fang . 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.)
( Wang Guohua, Liu Ju, Yang Tengfei , et al. Social Support for AIDS in Cyberspace -Take Baidu Post Bar “HIV Bar” for Example[J]. Journal of Intelligence, 2015,34(11):105-110.)
[36]
Milgram S . The Small World Problem[J]. Psychology Today, 1967,2(1):60-67.
[37]
Watts D J, Strogatz S H . Collective Dynamics of “Small World” Networks[J]. Nature, 1998,393(6684):440-442.
[38]
Newman M E J, Watts D J . Renorm Alization Group Analysis of the Small-world Network Model[J]. Physics Letters A, 1999,263(4):341-346.
( Qu Shaoling, Hu Dehua . A Visual Analysis on the Research of Small World Theory[J]. Library Journal, 2016,35(6):57-65.)
[40]
Capaldo A, Giannoccaro I . Interdependence and Network-level Trust in Supply Chain Networks: A Computational Study[J]. Industrial Marketing Management, 2015,44(1):180-195.
[41]
Wandelt S, Sun X Q, Zanin M , et al. QRE: Quick Robustness Estimation for Large Complex Networks[J]. Future Generation Computer Systems, 2018,83:413-424.
[42]
Centola D . The Social Origins of Networks and Diffusion[J]. American Journal of Sociology, 2015,120(5):1295-1338.
[43]
Pereira J B, Westman E, Stomrud E , et al. Abnormal Structural Brain Connectome in Individuals with Preclinical Alzheimer’s Disease[J]. Cerebral Cortex, 2018,28(10):3638-3649.
[44]
Lee M H, Kim D Y, Chung M K , et al. Topological Properties of the Structural Brain Network in Autism via Epsilon- neighbor Method[J]. IEEE Transactions on Biomedical Engineering, 2018,65(10):2323-2333.
[45]
Lee J, Kim S . Exploring the Role of Social Networks in Affective Organizational Commitment: Network Centrality, Strength of Ties, and Structural Holes[J]. American Review of Public Administration, 2011,41(2):205-223.
[46]
Wang C L, Rodan S, Fruin M , et al. Knowledge Networks, Collaboration Networks, and Exploratory Innovation[J]. Academy of Management Journal, 2014,57(2):484-514.
[47]
Burt R S . Structural Holes: The Social Structure of Competition[M]. Cambridge, MA: Harvard University Press, 1992.
[48]
Burt R S . Structural Holes and Good Ideas[J]. American Journal of Sociology, 2004,110(2):349-399.
[49]
Burt R S . Reinforced Structural Holes[J]. Social Networks, 2015,43:149-161.
[50]
刘军 . 社会网络分析导论[M]. 北京: 社会科学文献出版社, 2004.
[50]
( Liu Jun . An Introduction to Social Network Analysis[M]. Beijing: Social Science Academic Press, 2004.)
[51]
Freeman L C . Centrality in Social Networks: Conceptual Clarification[J]. Social Networks, 1979,1(3):215-239.
[52]
Brandes U, Borgatti S P, Freeman L C . Maintaining the Duality of Closeness and Betweenness Centrality[J]. Social Networks, 2016,44:153-159.
[53]
Bonacich P, Lloyd P . Eigenvector Centrality and Structural Zeroes and Ones: When is a Neighbor Not a Neighbor[J]. Social Networks, 2015,43:86-90.
( Jiang Xin, Tian Zhiwei . An Empirical Study on Information Dissemination in Microblog Community from the Perspective of Small-world Property——A Case Study with Tencent Microblog[J]. Information Science, 2012,30(8):1139-1142.)
( Guan Peng, Wang Yuefen, Cao Jiajun . Research on Framework of Construction and Evolution Analysis of Discipline Knowledge Network Based on Integrating Topic[J]. Information Science, 2018,36(9):3-8.)
[56]
Figueiredo C, Chen W H, Azevedo J . Central Nodes and Surprise in Content Selection in Social Networks[J]. Computers in Human Behavior, 2015,51:382-392.
[57]
Ballinger G A, Cross R, Holtom B C . The Right Friends in the Right Places: Understanding Network Structure as a Predictor of Voluntary Turnover[J]. Journal of Applied Psychology, 2016,101(4):535-548.
[58]
Tortoriello M . The Social Underpinnings of Absorptive Capacity: The Moderating Effects of Structural Holes on Innovation Generation Based on External Knowledge[J]. Strategic Management Journal, 2015,36(4):586-597.
[59]
Liao Y C, Phan P H . Internal Capabilities, External Structural Holes Network Positions, and Knowledge Creation[J]. Journal of Technology Transfer, 2016,41(5):1148-1167.