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Discovering negative comments by sentiment analysis on web forum

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Abstract

Social media enables people to communicate with each other on the Internet in real-time and rich styles. In other words, there is a lot of information on the social media. If we can extract negative opinions of some brands, enterprises or politics, we can use these opinions to know the market demands and solve problems. In this paper, we propose a novel approach to extract negative-sentiment-oriented features and identify negative opinions in social media with text mining and machine learning techniques, support vector machine and neural network, as well as data collection with Web crawler. The experimental results show that our proposed methods can work effectively.

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Acknowledgements

This research was partially supported by Ministry of Science and Technology, Taiwan, under grant no. MOST 106-3114-E-009-008 and MOST 104-2811-E-009-050.

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Authors and Affiliations

  1. Department of Computer Science, College of Computer Science, National Chiao Tung University, Hsinchu, Taiwan

    Wei-Yun Hsu & Vincent S. Tseng

  2. Tamkang University, New Taipei City, Taiwan

    Hui-Huang Hsu

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  1. Wei-Yun Hsu
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  2. Hui-Huang Hsu
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  3. Vincent S. Tseng
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Correspondence to Hui-Huang Hsu.

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Guest Editors: Timothy K. Shih, Lin Hui, Somchoke Ruengittinun, and Qing Li

This article belongs to the Topical Collection: Special Issue on Social Media and Interactive Technologies

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Hsu, WY., Hsu, HH. & Tseng, V.S. Discovering negative comments by sentiment analysis on web forum. World Wide Web 22, 1297–1311 (2019). https://doi.org/10.1007/s11280-018-0561-6

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  • DOI: https://doi.org/10.1007/s11280-018-0561-6

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