Topic-driven semi-automatic reorganization of online discussion forums: A case study in an e-learning context

Abstract

Online discussion forums represent, nowadays, one of the main asynchronous communication means and information sources over the Internet. The forum paradigm is adopted by the most followed websites, such as social networks and blogs. The effectiveness of discussion forums as information source, i.e., the capability to satisfy their users' information needs, depends on their information richness first, but also on how their are organized and effectively moderated. Forums organized and moderated by topics of discussion tend to host messages on related subjects and, overall, provide a classification of message threads which eases information search. In this paper we propose a semi-automatic approach to detect topics of discussion in a forum and to enhance its organization by providing a hierarchical topic-driven navigation view on its messages. We adopt Information Retrieval (IR) techniques, such as topic modeling, and formal concept analysis (FCA) to identify discussion topics and to provide a hierarchical topic-centered view on messages. We tested the validity of our approach on four forums of the e-learning platform of an Italian distance-learning university which provides around 20 moderated and unmoderated main forums followed actively by almost 5000 users, including students and teachers, each year. We validated the topics identification and messages to topics allocation process with a specific empirical experiment obtaining promising results.