ARQUSUMM: AI Quantifies Arguments for Deeper Online Conversation Summaries
By An Quang Tang, Xiuzhen Zhang, Minh Ngoc Dinh, Zhuang Li
Published on November 24, 2025| Vol. 1, Issue No. 1
Content Source
This is a curated briefing. The original article was published on cs.CL updates on arXiv.org.
Summary
The research introduces ARQUSUMM, a novel framework designed for argument-aware quantitative summarization of online conversations. Traditional summarization often misses the deep 'claim-reason' structure and quantitative strength of arguments found in platforms like Reddit. ARQUSUMM addresses this by leveraging LLM few-shot learning, guided by argumentation theory, to identify propositions and their relationships within sentences. It then employs structure-aware clustering algorithms to aggregate arguments and quantify their support, demonstrating superior performance over existing models in generating helpful, high-quality, and accurate summaries.
Why It Matters
This research signifies a crucial advancement in how AI understands and distills human discourse, moving beyond mere topic extraction to deep argumentative analysis. For AI professionals, ARQUSUMM offers a powerful new tool in the fight against online polarization and misinformation. By explicitly identifying claim-reason structures and quantifying argument strength, it enables systems to provide balanced, comprehensive overviews of complex discussions, crucial for informed decision-making in everything from policy analysis to product development. This approach also showcases the immense potential of grounding Large Language Models (LLMs) with formal theories like argumentation theory, pushing them beyond pattern recognition towards genuine understanding and reasoning. It paves the way for more sophisticated content moderation, automated debate analysis, and even AI-powered tools that could help users navigate and comprehend highly controversial topics with greater clarity and less bias, ultimately fostering healthier online environments. The ability to automatically 'score' or quantify arguments is a game-changer for understanding public sentiment and the dynamics of online influence, offering profound implications for both commercial applications and societal well-being.