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.
CITATION STYLE
Xu, R., & Zhang, Q. (2016). Social dynamics of the online health communities for mental health. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9545, pp. 267–277). Springer Verlag. https://doi.org/10.1007/978-3-319-29175-8_25
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