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Losing Weight Together Online: How People Perceive Social Support in Online Weight Loss Communities

DC Field Value Language
dc.contributor.advisor김은미-
dc.contributor.author서민향-
dc.date.accessioned2017-07-19T12:16:09Z-
dc.date.available2017-07-19T12:16:09Z-
dc.date.issued2013-08-
dc.identifier.other000000013027-
dc.identifier.urihttps://hdl.handle.net/10371/134269-
dc.description학위논문 (석사)-- 서울대학교 대학원 : 언론정보학과, 2013. 8. 김은미.-
dc.description.abstractQuestioning the kind of social support that community members perceive through participation in an online weight loss community, this paper focused on the precedent elements of social support at both individual and community levels. Based on network theory, individualsparticipation and social relations in egocentric networks as well as communities characteristics were discussed as the prerequisites of four types of perceived social support: emotional, appraisal, informational and instrumental supports. As a result of a survey (N=498), it was found that the four types of social support are differentiated in accordance with each of the independent variables. Also individual
participation was found to be the most powerful motivator of perceiving any kind of social support, and the level community activeness is the only predicting factor of emotional support among the four types of perceived social supports. In summary it was revealed that
the effect of variables on social support at the community level is relatively smaller than the effect of variables at the individual level. Nevertheless, communities' structural characteristics are influential to individuals' perception which can be interpreted as the notion that online communities exist with identities as 'a group' in the perception of the community members, and beyond its function as just a platform.
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dc.description.tableofcontentsI. Introduction ……………………………………………...………………… 1
II. Theoretical Backgrounds ………………………………..……………… 4
1. Social Network Theory ………………………………..…………………… 4
III. Literature Reviews ……………...………………………..……………… 7
1. Perceived Social Support ………………………………..…………….…… 7
2. Egocentric Network in Individual Level ……………………...………. 14
2.1. Egocentric Network Size ………………………………..………….… 14
2.2. Egocentric Network Strength ……………………………………… 17
3. Individual Participation ………………………………..…………………. 24
4. Whole Network in Community Level …………………………….…… 30
4.1. Community Size ………………………………………...……….…… 30
4.2. Community Activeness ……………………………………...….…… 34
IV. Method …………………………………………………..…………………. 39
1. Aim of the Study ………………………………………..………………….. 39
2. Samples of the Study …………………………………..………………….. 39
3. Measurement of Variables …..………………………..…………………... 40
iv
V. Result ……………………………………………………..…………………. 47
1. Descriptive Statistics ………………………………….…………………... 47
2. The Effects of the Each Variable on Social Support …...……...……. 52
2.1. The Size of Egocentric Network …………...…….........………… 52
2.2. The Strength of Egocentric Network …………....…....……....… 52
2.3. Individuals participation …..……...………...…......………….…. 53
2.4. Community Size …..……...………...…......……………….....…….. 54
2.5. Community Activeness ...………...…......………..……….…...…... 56
3. Multiple Regression Analysis for the Most Influential
Variable ………………………………………...…...…………………..…......… 56
4. The Indirect Influence of the Characteristics of Online
Communities ………………………………………………………...…….....… 58
V. Discussion ……………………………….…………………………..….…... 61
1. Summary ………………………………….…………………………..……... 61
2. Key Findings and Implications …………………………………….…... 63
3. Limitations and Suggestions for the Future Research …...………... 70
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dc.formatapplication/pdf-
dc.format.extent1179523 bytes-
dc.format.mediumapplication/pdf-
dc.language.isoen-
dc.publisher서울대학교 대학원-
dc.subjectperceived social support-
dc.subjectsocial network theory-
dc.subjectonline weight loss community-
dc.subjectcomputer mediated communication-
dc.subject.ddc070-
dc.titleLosing Weight Together Online: How People Perceive Social Support in Online Weight Loss Communities-
dc.typeThesis-
dc.contributor.AlternativeAuthorMinhyang Suh-
dc.description.degreeMaster-
dc.citation.pagesi,88-
dc.contributor.affiliation사회과학대학 언론정보학과-
dc.date.awarded2013-08-
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