Communicating social support in online self-help groups for anxiety and depression: A qualitative discourse analysis

Jesse Wai Chi Yip*

*Corresponding author for this work

    Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

    1 Citation (Scopus)

    Abstract

    Research showed that the communication ofsocial support in online self-help groups wastherapeutic to participants. However, previousstudies tended to focus on the content sharedand have overlooked the communicativebehaviors of the communication. Drawing uponthe framework of discourse analysis, this studymanifests the communicative patterns of thecommunication of social support in online selfhelp groups for anxiety and depression. It isargued that understanding communicativebehaviors is beneficial for people to gauge thetherapeutic effect of participation in the groupsand to become integrated into the groups.

    Original languageEnglish
    Title of host publicationProceedings of the 32nd Pacific Asia Conference on Language, Information and Computation, PACLIC 2018
    EditorsStephen Politzer-Ahles, Yu-Yin Hsu, Chu-Ren Huang, Yao Yao
    PublisherAssociation for Computational Linguistics (ACL)
    Pages807-813
    Number of pages7
    Publication statusPublished - Dec 2018
    Event32nd Pacific Asia Conference on Language, Information and Computation, PACLIC 2018 - Hong Kong, Hong Kong
    Duration: 1 Dec 20183 Dec 2018
    https://aclanthology.org/volumes/Y18-1/ (Conference Proceedings)

    Publication series

    NameProceedings of the Pacific Asia Conference on Language, Information and Computation, PACLIC

    Conference

    Conference32nd Pacific Asia Conference on Language, Information and Computation, PACLIC 2018
    Country/TerritoryHong Kong
    CityHong Kong
    Period1/12/183/12/18
    Internet address

    Fingerprint

    Dive into the research topics of 'Communicating social support in online self-help groups for anxiety and depression: A qualitative discourse analysis'. Together they form a unique fingerprint.

    Cite this