Abstract
Online Health Communities (OHCs) have become more and more prevalent with the advance of web 2.0 and social media. These platforms provide free, open and wide-sourced places for people to publicly discuss health-related problems, especially some mental health problems, such as depression. This paper aims to characterize the unique structural and dynamic patterns of users’ interactions in depression related OHCs. Through the topological analyses of social networks, we identify the unique highly sticky structure of depression related OHCs as compared with other social communities. Besides, users in these communities spend relatively longer time on closely peer-to-peer messaging. Moreover, the evolutionary trends show that depression related OHCs present distinctive growth patterns in terms of user addition and user activeness, which could be further applied in differentiating the community types and the development stages.
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Acknowledgments
We would like to thank Dr. Ron Chen for his kind advices of dataset selection and suggestions of possible research questions. This research was supported by The National Natural Science Foundation of China (NSFC) Grant No. 71402157, CityU Grants No. 7200399. and No. 7004465, and The Theme-Based Research Scheme Grant of the Research Grants Council (RGC) of Hong Kong SAR No. T32-102/14N.
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Xu, R., Zhang, Q. (2016). Social Dynamics of the Online Health Communities for Mental Health. In: Zheng, X., Zeng, D., Chen, H., Leischow, S. (eds) Smart Health. ICSH 2015. Lecture Notes in Computer Science(), vol 9545. Springer, Cham. https://doi.org/10.1007/978-3-319-29175-8_25
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DOI: https://doi.org/10.1007/978-3-319-29175-8_25
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