Detecting Disagreement in Conversations using Pseudo-Monologic Rhetorical Structure

Kelsey Allen, Giuseppe Carenini, Raymond T. Ng

Abstract: Casual online forums such as Reddit, Slashdot and Digg, are continuing to increase in popularity as a means of communication. Detecting disagreement in this domain is a considerable challenge. Many topics are unique to the conversation on the forum, and the appearance of disagreement may be much more subtle than on political blogs or social media sites such as twitter. In this analysis we present a crowd-sourced annotated corpus for topic level disagreement detection in Slashdot, showing that disagreement detection in this domain is difficult even for humans. We then proceed to show that a new set of features determined from the rhetorical structure of the conversation significantly improves the performance on disagreement detection over a baseline consisting of unigram/bigram features, discourse markers, structural features and meta-post features.