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dc.contributor.advisorPennebaker, James W.en
dc.creatorChung, Cindy Kyuahen
dc.date.accessioned2009-10-16T17:54:20Zen
dc.date.available2009-10-16T17:54:20Zen
dc.date.issued2009-08en
dc.identifier.urihttp://hdl.handle.net/2152/6541en
dc.descriptiontexten
dc.description.abstractAn increasing number of people are turning to online blogging communities devoted to self-change for smoking, shopping, and other behaviors. To understand processes underlying effective self-change, the current project tracked the language and social dynamics of a dieting blog community using computerized text analysis. Three research questions were asked: What predicts weight loss in blogs? What changes in blogging predict weight loss? Can we predict dropping out or successful weight loss based on the first two entries? A community of blogs devoted to weight loss was examined (n = 2530). Most bloggers were female, and on average, around 30 years old, approximately 200 pounds, with a goal weight of about 140 pounds. A sample of blogs by females that had blogged at least 15 entries within the first 15 weeks of blogging resulted in a total of 186 blogs, representing over 9,200 entries for analysis. Computerized text analysis was used to examine language for rates of self-focus, emotionality, cognitive processing, keeping food diaries, and social support. Rates of blogging were assessed by word counts, number of active weeks, and mean entries per week. Social support was assessed through the use of social words, the size of the social network, along with the positivity and negativity of the comments. The discrepancy between start and goal weight was also assessed. The results suggested that having larger weight loss goals and blogging about personal events was a more effective weight loss strategy than keeping an online food intake diary. The degree to which bloggers were socially integrated with the blog community was found to be a potent predictor of weight loss. Online components of behavioral treatment programs could encourage dieters to browse and comment on other dieters’ progress, and to share personal narratives rather than simply focusing on the benefits of food intake diaries, nutrition, and exercise. The current project points to the power of computerized text analytic tools to address important theoretical and practical social psychological issues that are evolving on the internet. Specifically, language analysis methods can identify which dimensions of blogging communities can help or hinder self-change processes.en
dc.format.mediumelectronicen
dc.language.isoengen
dc.rightsCopyright is held by the author. Presentation of this material on the Libraries' web site by University Libraries, The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works.en
dc.subjectPredicting weight lossen
dc.subjectDieting blogsen
dc.subjectComputerized text analysisen
dc.subjectLanguage analysisen
dc.subjectSelf-change blogsen
dc.subjectDieting blog communitiesen
dc.subjectBlogging communitiesen
dc.titlePredicting weight loss in blogs using computerized text analysisen
dc.description.departmentPsychologyen
thesis.degree.departmentPsychologyen
thesis.degree.disciplinePsychologyen
thesis.degree.grantorThe University of Texas at Austinen
thesis.degree.levelDoctoralen
thesis.degree.nameDoctor of Philosophyen


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