An 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. / text

Blogging is a recent phenomenon with research currently focusing on how it facilitates both personal and organisational knowledge exchange (Aimeur, Brassard & Paquet 2005; Hsu & Lin 2008). Social capital is shown to be a crucial factor facilitating knowledge transfer (Nahapiet and Ghoshal 1998). Blogging is a new social communication technology enabling individuals to collaborate and share knowledge. This research investigates how three dimensions of social capital affect individual knowledge sharing in weblog communities. In particular, it explores how individuals exploit weblogs as a tool for conversational knowledge management in educational institutions. Following Wasko & Faraj's (2005) study, the conceptual model is developed by setting eight independent variables from social capital dimensions and a dependent variable is set from individual behaviour in online knowledge sharing. Eight hypotheses are developed to test the relationship between these variables. A quantitative approach was applied for data collection and analysis. For data collection, an online survey was published in several Australian university weblog communities. An additional paper-based survey was distributed to the respondents in order to gain adequate sample size. For data analysis, confirmatory factor analysis (CFA) was applied to eliminate measurement items that shared a significant residual value with other measurement items. Further, the models obtained from confirmatory factor analysis were used to test the hypotheses by multiple regression analysis. Results from multiple regression analysis on online knowledge sharing suggest that trust, personal reputation and enjoy helping are positively associated with individual online knowledge sharing. The stepwise estimation procedure was further adapted in the regression model. The results show that four independent variables became significant to the study. These four significant variables were individual expertise, trust, personal reputation and enjoy helping. Lastly, several limitations in this study such as the sample of university online setting and respondents' activities on weblogs are discussed. These limitations lead to the direction of future research provided in conclusion of this study.