ArguSense: Argument-Centric Analysis of Online Discourse
Arman Irani, Michalis Faloutsos, Kevin Esterling

TL;DR
ArguSense is a comprehensive framework for modeling, visualizing, and analyzing argument structures and content in online forum discussions, enabling deeper understanding of dialogical processes.
Contribution
We introduce ArguSense, a novel system that detects argument topics, visualizes argument structures, and quantifies content diversity in online forums.
Findings
Effective unsupervised argument topic detection
Visualizations reveal argument dynamics within threads
Quantitative analysis of argument diversity across communities
Abstract
How can we model arguments and their dynamics in online forum discussions? The meteoric rise of online forums presents researchers across different disciplines with an unprecedented opportunity: we have access to texts containing discourse between groups of users generated in a voluntary and organic fashion. Most prior work so far has focused on classifying individual monological comments as either argumentative or not argumentative. However, few efforts quantify and describe the dialogical processes between users found in online forum discourse: the structure and content of interpersonal argumentation. Modeling dialogical discourse requires the ability to identify the presence of arguments, group them into clusters, and summarize the content and nature of clusters of arguments within a discussion thread in the forum. In this work, we develop ArguSense, a comprehensive and systematic…
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