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://preview.aclanthology.org/add_missing_videos/W18-6212/
- DOI:
- 10.18653/v1/W18-6212
- 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)
- PDF:
- https://preview.aclanthology.org/add_missing_videos/W18-6212.pdf