Socially-Informed Timeline Generation for Complex Events
Lu Wang, Claire Cardie, Galen Marchetti

TL;DR
This paper introduces a framework for generating socially-informed timelines for complex events by integrating news summaries with relevant user comments, improving informativeness and insightfulness over existing methods.
Contribution
It proposes an optimization approach that combines news and social media content to produce more comprehensive and insightful event timelines.
Findings
System outperforms state-of-the-art in informativeness
Comment summaries rated more insightful in human evaluations
Automatically generates more comprehensive timelines
Abstract
Existing timeline generation systems for complex events consider only information from traditional media, ignoring the rich social context provided by user-generated content that reveals representative public interests or insightful opinions. We instead aim to generate socially-informed timelines that contain both news article summaries and selected user comments. We present an optimization framework designed to balance topical cohesion between the article and comment summaries along with their informativeness and coverage of the event. Automatic evaluations on real-world datasets that cover four complex events show that our system produces more informative timelines than state-of-the-art systems. In human evaluation, the associated comment summaries are furthermore rated more insightful than editor's picks and comments ranked highly by users.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsVideo Analysis and Summarization · Advanced Text Analysis Techniques · Topic Modeling
