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http://dx.doi.org/10.3745/JIPS.2013.9.4.538

Opinion Bias Detection Based on Social Opinions for Twitter  

Kwon, A-Rong (Dept. of Computer Science & Engineering, CAIIT, Chonbuk National University)
Lee, Kyung-Soon (Dept. of Computer Science & Engineering, CAIIT, Chonbuk National University)
Publication Information
Journal of Information Processing Systems / v.9, no.4, 2013 , pp. 538-547 More about this Journal
Abstract
In this paper, we propose a bias detection method that is based on personal and social opinions that express contrasting views on competing topics on Twitter. We used unsupervised polarity classification is conducted for learning social opinions on targets. The $tf{\cdot}idf$ algorithm is applied to extract targets to reflect sentiments and features of tweets. Our method addresses there being a lack of a sentiment lexicon when learning social opinions. To evaluate the effectiveness of our method, experiments were conducted on four issues using Twitter test collection. The proposed method achieved significant improvements over the baselines.
Keywords
Social opinion; Personal opinion; Bias detection; Sentiment; Target;
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