Topic-Specific Sentiment Analysis Can Help Identify Political Ideology
Computation and Language
2018-10-31 v1 Information Retrieval
Machine Learning
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.
Cite
@article{arxiv.1810.12897,
title = {Topic-Specific Sentiment Analysis Can Help Identify Political Ideology},
author = {Sumit Bhatia and Deepak P},
journal= {arXiv preprint arXiv:1810.12897},
year = {2018}
}
Comments
Presented at EMNLP Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, 2018