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Conference Paper: Social dynamics of the online health communities for mental health

TitleSocial dynamics of the online health communities for mental health
Authors
KeywordsMessage exchange
Online health communities
Social dynamics
Social network analysis
Issue Date2016
Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, v. 9545, p. 267-277 How to Cite?
AbstractOnline 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.
Persistent Identifierhttp://hdl.handle.net/10722/330521
ISSN
2023 SCImago Journal Rankings: 0.606
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXu, Ronghua-
dc.contributor.authorZhang, Qingpeng-
dc.date.accessioned2023-09-05T12:11:25Z-
dc.date.available2023-09-05T12:11:25Z-
dc.date.issued2016-
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, v. 9545, p. 267-277-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10722/330521-
dc.description.abstractOnline 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.-
dc.languageeng-
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.subjectMessage exchange-
dc.subjectOnline health communities-
dc.subjectSocial dynamics-
dc.subjectSocial network analysis-
dc.titleSocial dynamics of the online health communities for mental health-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/978-3-319-29175-8_25-
dc.identifier.scopuseid_2-s2.0-84958536808-
dc.identifier.volume9545-
dc.identifier.spage267-
dc.identifier.epage277-
dc.identifier.eissn1611-3349-
dc.identifier.isiWOS:000373444000025-

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