Topic-Specific Sentiment Analysis Can Help Identify Political Ideology

Sumit Bhatia, Deepak P


Abstract
Ideological leanings of an individual can often be gauged by the sentiment one expresses about different issues. We propose a simple framework that represents a political ideology as a distribution of sentiment polarities towards a set of topics. This representation can then be used to detect ideological leanings of documents (speeches, news articles, etc.) based on the sentiments expressed towards different topics. Experiments performed using a widely used dataset show the promise of our proposed approach that achieves comparable performance to other methods despite being much simpler and more interpretable.
Anthology ID:
W18-6212
Volume:
Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
Month:
October
Year:
2018
Address:
Brussels, Belgium
Editors:
Alexandra Balahur, Saif M. Mohammad, Veronique Hoste, Roman Klinger
Venue:
WASSA
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
79–84
Language:
URL:
https://aclanthology.org/W18-6212
DOI:
10.18653/v1/W18-6212
Bibkey:
Cite (ACL):
Sumit Bhatia and Deepak P. 2018. Topic-Specific Sentiment Analysis Can Help Identify Political Ideology. In Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 79–84, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
Topic-Specific Sentiment Analysis Can Help Identify Political Ideology (Bhatia & P, WASSA 2018)
Copy Citation:
PDF:
https://aclanthology.org/W18-6212.pdf