What Is an Opinion About? Exploring Political Standpoints Using Opinion Scoring Model
Abstract
In this paper, we propose a generative model to automatically discover the hidden associations between topics words and opinion words. By applying those discovered hidden associations, we construct the opinion scoring models to extract statements which best express opinionists’ standpoints on certain topics. For experiments, we apply our model to the political area. First, we visualize the similarities and dissimilarities between Republican and Democratic senators with respect to various topics. Second, we compare the performance of the opinion scoring models with 14 kinds of methods to find the best ones. We find that sentences extracted by our opinion scoring models can effectively express opinionists’ standpoints.
Cite
Text
Chen et al. "What Is an Opinion About? Exploring Political Standpoints Using Opinion Scoring Model." AAAI Conference on Artificial Intelligence, 2010. doi:10.1609/AAAI.V24I1.7717Markdown
[Chen et al. "What Is an Opinion About? Exploring Political Standpoints Using Opinion Scoring Model." AAAI Conference on Artificial Intelligence, 2010.](https://mlanthology.org/aaai/2010/chen2010aaai-opinion/) doi:10.1609/AAAI.V24I1.7717BibTeX
@inproceedings{chen2010aaai-opinion,
title = {{What Is an Opinion About? Exploring Political Standpoints Using Opinion Scoring Model}},
author = {Chen, Bi and Zhu, Leilei and Kifer, Daniel and Lee, Dongwon},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2010},
pages = {1007-1012},
doi = {10.1609/AAAI.V24I1.7717},
url = {https://mlanthology.org/aaai/2010/chen2010aaai-opinion/}
}