Automatic label generation for news comment clusters.

We present a supervised approach to automat-ically labelling topic clusters of reader com-ments to online news. We use a feature setthat includes both features capturing proper-ties local to the cluster and features that cap-ture aspects from the news article and fromcomments outside the cluster. We evaluatethe approach in an automatic and a manual,task-based setting. Both evaluations show theapproach to outperform a baseline method,which uses tf*idf to select comment-internalterms for use as topic labels. We illustrate howcluster labels can be used to generate clustersummaries and present two alternative sum-mary formats: a pie chart summary and an ab-stractive summary.