Predicting Success and Failure in Weight Loss Blogs through Natural Language Use

Cindy K. Chung, Clinton Jones, Alexander Liu, James W. Pennebaker

We explore the emerging phenomenon of blogging about personal goals, and demonstrate how natural language processing tools can be used to uncover psychologically meaningful constructs in blogs. We describe features of a blog community (2638 blogs) devoted to weight loss. We compare several approaches to text analysis in predicting weight loss from natural language use in a subset of the blogs (258 users; over 13,000 entries). First, we use a bag of words approach to distinguish the degree to which individual words can predict success and failure. Next, we compare the results to a deductive word count and categorization tool, Linguistic Inquiry and Word Count. We discuss the theoretical significance of the words and word categories that distinguish between bloggers who succeed and those who fail in their weight loss attempts, along with the implications of automated text analysis in summarizing psychological features of blogs.

Subjects: 13. Natural Language Processing; 13.1 Discourse

Submitted: Feb 15, 2008

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