Zhao Zhe
College of Electronics and Information Engineering, Tongji University, 201804, Shanghai, People Republic of China
Xiang Yang
College of Electronics and Information Engineering, Tongji University, 201804, Shanghai, People Republic of China
Zhang Bo
College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai, 200234, People Republic of China
Zhang Qi
College of Electronics and Information Engineering, Tongji University, 201804, Shanghai, People Republic of China
Pan Tao
Shen Hua Hollysys Information Technology Co. Ltd., Beijing, 100000, People Republic of China
ABSTRACT
Microblog has been an important platform for expression of public opinion towards policy decisions. One key challenge for policymakers is to mine public opinions from microblog platforms as soon as possible. In order to deal with the challenge, this paper proposes a Topic Detection and Tracking (TDT) algorithm based on self-adjusting vector space model (VSM) and an opinion mining method based on comments. Furthermore, an innovative opinion mining system is developed, using mciroblog as the opinion mining platform and combining natural language processing techniques with similarity calculation and polarity calculation. A series of related experiments are employed to verify the efficiency and maneuverability of the algorithm.
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How to cite this article
Zhao Zhe, Xiang Yang, Zhang Bo, Zhang Qi and Pan Tao, 2013. A Novel Public Opinion Mining Method on Microblog Platform. Journal of Applied Sciences, 13: 3315-3319.
DOI: 10.3923/jas.2013.3315.3319
URL: https://scialert.net/abstract/?doi=jas.2013.3315.3319
DOI: 10.3923/jas.2013.3315.3319
URL: https://scialert.net/abstract/?doi=jas.2013.3315.3319
REFERENCES
- Pang, B., L. Lee and S. Vaithyanathan, 2002. Thumbs up? Sentiment classification using machine learning techniques. Proceedings of the ACL-02 Conference on Empirical methods in natural language processing, Volume 10, July 6-7, 2002, Philadelphia, PA., USA., pp: 79-86.
CrossRef - Li, Z., B. Wang, M. Li and W. Ma, 2005. A probabilistic model for retrospective news event detection. Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, August 15-19, 2005, Salvador, Brazil, pp: 106-113.
CrossRefDirect Link - Cortes, C. and V. Vapnik, 1995. Support-vector networks. Mach. Learn., 20: 273-297.
CrossRefDirect Link