Forming online support groups for internet and behavior related addictions

Chih Ya Shen, Hong Han Shuai, De Nian Yang, Yi Feng Lan, Wang Chien Lee, Philip S. Yu, Ming Syan Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Scopus citations


While online social networks have become a part of many people's daily lives, Internet and social network addictions (ISNAs) have been noted recently. With increased patients in addictive Internet use, clinicians often form support groups to help patients. This has become a trend because groups organized around therapeutic goals can effectively enrich members with insight and guidance while holding everyone accountable along the way. With the emergence of online social network services, there is a trend to form support groups online with the aid of mental health professionals. Nevertheless, it becomes impractical for a psychiatrist to manually select the group members because she faces an enormous number of candidates, while the selection criteria are also complicated since they span both the social and symptom dimensions. To effectively address the need of mental healthcare professionals, this paper makes the first attempt to study a new problem, namely Member Selection for Online Support Group (MSSG). The problem aims to maximize the similarity of the symptoms of all selected members, while ensuring that any two members are unacquainted to each other. We prove that MSSG is NP-Hard and inapproximable within any ratio, and design a 3-approximation algorithm with a guaranteed error bound. We evaluate MSSG via a user study with 11 mental health professionals, and the results manifest that MSSG can effectively find support group members satisfying the member selection criteria. Experimental results on large-scale real datasets also demonstrate that our proposed algorithm outperforms other baselines in terms of solution quality and efficiency.

Original languageEnglish (US)
Title of host publicationCIKM 2015 - Proceedings of the 24th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Number of pages10
ISBN (Electronic)9781450337946
StatePublished - Oct 17 2015
Event24th ACM International Conference on Information and Knowledge Management, CIKM 2015 - Melbourne, Australia
Duration: Oct 19 2015Oct 23 2015

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings


Other24th ACM International Conference on Information and Knowledge Management, CIKM 2015

All Science Journal Classification (ASJC) codes

  • General Decision Sciences
  • General Business, Management and Accounting


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