International Sentiment Analysis for News and Blogs

Authors

  • Mikhail Bautin Stony Brook University
  • Lohit Vijayarenu Yahoo! Inc.
  • Steven Skiena Stony Brook University

Abstract

There is a growing interest in mining opinions using sentiment analysis methods from sources such as news, blogs and product reviews. Most of these methods have been developed for English and are difficult to generalize to other languages. We explore an approach utilizing state-of-the-art machine translation technology and perform sentiment analysis on the English translation of a foreign language text. Our experiments indicate that (a) entity sentiment scores obtained by our method are statistically significantly correlated across nine languages of news sources and five languages of a parallel corpus; (b) the quality of our sentiment analysis method is largely translator independent; (c) after applying certain normalization techniques, our entity sentiment scores can be used to perform meaningful cross-cultural comparisons.

Downloads

Published

2021-09-25

How to Cite

Bautin, M., Vijayarenu, L., & Skiena, S. (2021). International Sentiment Analysis for News and Blogs. Proceedings of the International AAAI Conference on Web and Social Media, 2(1), 19-26. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/18606