  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.
