Socially-Informed Timeline Generation for Complex Events
This work addresses the limitation of existing timeline generation systems that ignore social media data, providing a more comprehensive view for users interested in event analysis.
The paper tackled the problem of generating timelines for complex events by incorporating social context from user comments alongside news articles, resulting in timelines that were more informative than state-of-the-art systems in automatic evaluations and had comment summaries rated more insightful in human evaluations.
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.