Based on SVM Tibetan Web Public Opinion Sentiment Classification

Abstract:

Tibetan Web text has increased rapidly in recent years. According to mining and analyzing the data about user’s comments, we could identify the Sentimental tendency and evolution. Therefore we can better understand the user's behavior. Hot Tibetan public opinion analysis at the same time also can give enterprise, government and other institutions to provide important decision-making basis. The paper first describes SVM algorithm. Then the study of public opinion and target Tibetan Web Sentiment classification is defined and described, after that the paper gives the basic ideas and experimental research program. Finally, we summarize the achievements and shortcomings of Tibetan sentiment classification, as well as describe the challenges and the prospects of its development prospects.

• Periodical: Advanced Materials Research (Volumes 989-994)
• Pages: 4375-4378
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.989-994.4375
• Online since: July 2014
• Authors: Ying Xing Li*, Zong Jun Zheng, Ya Ni E
• Keywords: Sentiment Classification, SVM, Tibetan, Web Public Opinion

References

[1] Hayes, Steven P, Weinstein. A System for Content-Based Indexing of a Database of News Stories[C]. Proceedings of The Second Conference on Innovative Applications of Artificial Intelligence, 1009: 54-56.

[2] Cortes C. Vapnik V. Support-vector networks [J]. Machine Learning, 1995, 20(3): 73-297.

[3] Vapnik Vladimir N. Overview of statistical learning theory [J]. IEEE Transactions on Neural Networks, 1999, 10(5): 988-999.

DOI: 10.1109/72.788640

[4] Yan Chao, research and implementation of SVM Chinese text automatic classification system [D], ​​based Taiyuan: Taiyuan University of Technology, (2010).

[5] Zhu Shuxian, Zhang Renjie, research SVM kernel function selection [J]. Science Technology and Engineering, 2008. 8, 8 (16).

[6] Jia Huiqiang, Li Yonghong. design and implementation Tibetan text classifier [J]. Technology rich wizard, 2010, (4) : 30-31 under.

[7] Xu Guixian. Tibetan web-based text automatic classification column [J]. Chinese Information Technology 2011 (4) : 20-23.

[8] Li Y X, Deng K Y. User browsing interest in the propagation of public opinion in Tibetan internet to determine research[C]. CISP, 2012, pp.859-862.

DOI: 10.1109/csip.2012.6308989

[9] Deng J W, Deng K Y, Li Y S, Li Y X. Opinion Spreading Models on Tibetan Networks [J], Computer Systems & Applications. 2013, 22(3), pp.209-211.

[10] Li Y X, E Y N. The Research on Learning Behavior of Tibetan Network Teaching Systems[C]. IERI Procedia (2012) pp.127-132.

DOI: 10.1016/j.ieri.2012.06.062

[11] Deng J W, Deng K Y, Li Y S, Li Y X. Study on Evolution Model and Simulation Based on Social Networks[C]. ICNC (2012) pp.1249-1252.