Visualizing Emotions from Chinese Blogs by Textual Emotion Analysis and Recognition Techniques

Changqin Quan () and Fuji Ren
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Changqin Quan: AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine, School of Computer and Information, HeFei University of Technology, Tunxi Road No. 193 Hefei, 230009, China
Fuji Ren: Faculty of Engineering, University of Tokushima, 2-1 Minamijosanjima, Tokushima 770-8506, Japan

International Journal of Information Technology & Decision Making (IJITDM), 2016, vol. 15, issue 01, 215-234

Abstract: The research on blog emotion analysis and recognition has become increasingly important in recent years. In this study, based on the Chinese blog emotion corpus (Ren-CECps), we analyze and compare blog emotion visualization from different text levels: word, sentence, and paragraph. Then, a blog emotion visualization system is designed for practical applications. Machine learning methods are applied for the implementation of blog emotion recognition at different textual levels. Based on the emotion recognition engine, the blog emotion visualization interface is designed to provide a more intuitive display of emotions in blogs, which can detect emotion for bloggers, and capture emotional change rapidly. In addition, we evaluated the performance of sentence emotion recognition by comparing five classification algorithms under different schemas, which demonstrates the effectiveness of the Complement Naive Bayes model for sentence emotion recognition. The system can recognize multi-label emotions in blogs, which provides a richer and more detailed emotion expression.

Keywords: Natural language processing; affective computing; emotion recognition; emotion visualization (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1142/S0219622014500710

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