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Dynamic Evolution of Social Network in OHCs Based on Stochastic Actor-Based Model: A Case Study of WeChat Group

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Smart Health (ICSH 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11924))

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Abstract

With the seamless integration of Internet technology and medical industry, the online health community (OHC), transcending the restrictions of time and geo-graphical distances, provides users with rich and customized information services as well as emotional support. By studying user behavior and the social network evolution in the online health community, it can effectively improve the user activity of the online health community and the efficiency of users’ access to information. In this paper, the online health WeChat group is taken as the research object to established a social network based on the @ relationship among users. It explores the influence of individual behaviors on the evolution of network structure through the Stochastic Actor Model. Results show that the user behaviors in the online health WeChat group are of periodicity and turnover. The frequency of speech works differently for the overall and individual network structure changes. It promotes the enrichment of overall network structure while impede the @ relationships among individuals. This paper, exploring the network structure evolution in online health community, carries guiding suggestions concerning the management and maintenance of the online health community.

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Acknowledgments

This research is supported by the National Natural Science Foundation of China (No. 71573197).

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Correspondence to Jiang Wu .

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Wang, C., Cai, J., Gao, J., Wu, J. (2019). Dynamic Evolution of Social Network in OHCs Based on Stochastic Actor-Based Model: A Case Study of WeChat Group. In: Chen, H., Zeng, D., Yan, X., Xing, C. (eds) Smart Health. ICSH 2019. Lecture Notes in Computer Science(), vol 11924. Springer, Cham. https://doi.org/10.1007/978-3-030-34482-5_15

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  • DOI: https://doi.org/10.1007/978-3-030-34482-5_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34481-8

  • Online ISBN: 978-3-030-34482-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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