Topicality, time, and sentiment in online news comments

Authors:
Nicholas Diakopoulos;Mor Naaman
Affiliations:
Rutgers University, New Brunswick, NJ, USA;Rutgers University, New Brunswick, NJ, USA
Venue:
CHI '11 Extended Abstracts on Human Factors in Computing Systems
Year:
2011

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Abstract

In this paper we examine the relationships between news comment topicality, temporality, sentiment, and quality in a dataset of 54,540 news comments. Initial observations indicate that comment sentiments, both positive and negative, can be useful indicators of discourse quality, and that aggregate temporal patterns in positive sentiment exist on comment threads.