Research on Sentiment Analysis of Online Public Opinion Based on Semantic

  • Zhengtao JiangEmail author
  • Lu Liu
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 849)


In this paper, we combine the traditional analysis method based on sentiment dictionary and two kinds of text sentiment based on semantic pattern. We then propose an improved text sentiment analysis technology, including constructing an emotional dictionary, and designing 4 kinds of calculation rules based on dependency syntax and 3 kinds of calculation rules based on complex sentences. Finally, we construct the emotional semantic relation tree to calculate the value of text sentiment. Experimental results show that the accuracy rate, recall rate and F-measure of our method are significantly better than traditional algorithms.


Network public opinion Affective tendency analysis Affective lexicon Semantic model The affective tendency value 



This work was financially supported by the National Natural Science Foundation of China (61103199), the Engineering Program Project of CUC (3132015XNG1541, JXJYG1603) and the outstanding young teacher training project of CUC, Natural Science Basic Research Plan in Shaanxi Province of China (No. 2016JM6002) and the National Cryptography Development Fund of China (No. MMJJ20170208).


  1. 1.
    Bo, P., Li, L., Vaithyanathan, S.: Thumbs up? Sentiment classification using machine learning techniques. In: Acl-2002 Conference on Empirical Methods in Natural Language Processing, pp. 79–86. Association for Computational Linguistics (2002)Google Scholar
  2. 2.
    Whitelaw, C., Garg, N., Argamon, S.: Using appraisal groups for sentiment analysis. In: ACM International Conference on Information and Knowledge Management, pp. 625–631. ACM (2005)Google Scholar
  3. 3.
    He, F.Y.: Orientation analysis for Chinese blog text based on semantic comprehension. Comput. Appl. 31(8), 2130–2137 (2011)Google Scholar
  4. 4.
    Feng, S., Fu, Y.C., Yang, F., Wang, D.L.: Blog sentiment orientation analysis based on dependency parsing. J. Comput. Res, Dev. 11(49), 2395–2406 (2012)Google Scholar
  5. 5.
    Research Center for Social Computing and Information Retrieval. Language Technology platform [EB/OL].
  6. 6.
    Yang, P., Tao, L.I., Zhao, K.: Quantitative method for analyzing public opinions on internet. Appl. Res. Comput. 3(26), 1065–1066 (2009)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.School of Computer ScienceCommunication University of ChinaBeijingChina

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