Identifying the role of individual user messages in an online discussion and its use in thread retrieval

Abstract

Online discussion forums have become a popular medium for users to discuss with and seek information from other users having similar interests. A typical discussion thread consists of a sequence of posts posted by multiple users. Each post in a thread serves a different purpose providing different types of information and, thus, may not be equally useful for all applications. Identifying the purpose and nature of each post in a discussion thread is thus an interesting research problem as it can help in improving information extraction and intelligent assistance techniques. We study the problem of classifying a given post as per its purpose in the discussion thread and employ features based on the post's content, structure of the thread, behavior of the participating users, and sentiment analysis of the post's content. We evaluate our approach on two forum data sets belonging to different genres and achieve strong classification performance. We also analyze the relative importance of different features used for the post classification task. Next, as a use case, we describe how the post class information can help in thread retrieval by incorporating this information in a state-of-the-art thread retrieval model.