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Title: A Comparison of Lexicons for Detecting Controversy
We collect a corpus of 1554 online news articles from 23 RSS feeds and analyze it in terms of controversy and sentiment. We use several existing sentiment lexicons and lists of controversial terms to perform a number of statistical analyses that explore how sentiment and controversy are related. We conclude that the negative sentiment and controversy are not necessarily positively correlated as has been claimed in the past. In addition, we apply an information theoretic approach and suggest that entropy might be a good predictor of controversy.  more » « less
Award ID(s):
1704113
PAR ID:
10463434
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
LREC 2018 Workshop Natural Language Processing meets Journalism III
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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