On Positivity Bias in Negative Reviews

Madhusudhan Aithal, Chenhao Tan


Abstract
Prior work has revealed that positive words occur more frequently than negative words in human expressions, which is typically attributed to positivity bias, a tendency for people to report positive views of reality. But what about the language used in negative reviews? Consistent with prior work, we show that English negative reviews tend to contain more positive words than negative words, using a variety of datasets. We reconcile this observation with prior findings on the pragmatics of negation, and show that negations are commonly associated with positive words in negative reviews. Furthermore, in negative reviews, the majority of sentences with positive words express negative opinions based on sentiment classifiers, indicating some form of negation.
Anthology ID:
2021.acl-short.39
Volume:
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
294–304
Language:
URL:
https://aclanthology.org/2021.acl-short.39
DOI:
10.18653/v1/2021.acl-short.39
Bibkey:
Cite (ACL):
Madhusudhan Aithal and Chenhao Tan. 2021. On Positivity Bias in Negative Reviews. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pages 294–304, Online. Association for Computational Linguistics.
Cite (Informal):
On Positivity Bias in Negative Reviews (Aithal & Tan, ACL 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/update-css-js/2021.acl-short.39.pdf
Code
 madhu-aithal/Positivity-Bias-in-Negative-Reviews
Data
IMDb Movie ReviewsPeerReadSST