Using New York Times Picks to Identify Constructive Comments

Varada Kolhatkar, Maite Taboada

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Abstract
We examine the extent to which we are able to automatically identify constructive online comments. We build several classifiers using New York Times Picks as positive examples and non-constructive thread comments from the Yahoo News Annotated Comments Corpus as negative examples of constructive online comments. We evaluate these classifiers on a crowd-annotated corpus containing 1,121 comments. Our best classifier achieves a top F1 score of 0.84.
Anthology ID:
W17-4218
Volume:
Proceedings of the 2017 EMNLP Workshop: Natural Language Processing meets Journalism
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Editors:
Octavian Popescu, Carlo Strapparava
Venue:
WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
100–105
Language:
URL:
https://aclanthology.org/W17-4218
DOI:
10.18653/v1/W17-4218
Bibkey:
Cite (ACL):
Varada Kolhatkar and Maite Taboada. 2017. Using New York Times Picks to Identify Constructive Comments. In Proceedings of the 2017 EMNLP Workshop: Natural Language Processing meets Journalism, pages 100–105, Copenhagen, Denmark. Association for Computational Linguistics.
Cite (Informal):
Using New York Times Picks to Identify Constructive Comments (Kolhatkar & Taboada, 2017)
Copy Citation:
PDF:
https://preview.aclanthology.org/teach-a-man-to-fish/W17-4218.pdf