Classifying User Forum Participants: Separating the Gurus from the Hacks, and Other Tales of the Internet
Marco Lui, Timothy J. Baldwin · 2010
This paper introduces a novel user clas-sification task in the context of web user forums. We present a definition of four basic user characteristics and an anno-tated dataset. We outline a series of ap-proaches for predicting user characteris-tics, utilising aggregated post features and user/thread network analysis in a super-vised learning context. Using the pro-posed feature sets, we achieve results above both a naive baseline and a bag-of-words approach, for all four of our basic user characteristics. In all cases, our best-performing classifier is statistically indis-tinct from an upper bound based on the inter-annotator agreement for the task. 1