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Explore the Influence of Politics on Cultural Attention Based on Sentiment Analysis of Social Network Data

Published: 24 January 2020 Publication History

Abstract

With the increasingly frequent cultural exchanges between China and foreign countries, more and more Chinese people advocate western festivals. Foreign culture has invaded China and our traditional culture has been neglected seriously, which results in the more servere sense of loss of traditional culture. Therefore, Chinese government has stepped up efforts to spread traditional culture and issued relevant documents to make the public pay more attention to the inheritance and development of traditional culture.
By mining relevant festival data in Sina Weibo which is sent before and after the policy release, this paper use Chinese word segmentation technology and naive bayes classifier to analyze the change of public sentiment value and the distribution of emotional tendency to explore whether the Policy can promote the spread of culture and the positive significance of policy for the transmission of traditional culture.

References

[1]
Ye H, Chai X R. Reflection about Popular Culture in the Context of Visual Communication [J]. Advanced Materials Research, 2012, 433--440:5390--5395.
[2]
J. Read, "Using emoticons to reduce dependency in machine learning techniques for sentiment classification," in Proc. ACL Student Res. Workshop, 2005, pp. 43--48.
[3]
A. Go, R. Bhayani, and L. Huang, "Twitter sentiment classification using distant supervision," Stanford Univ., Stanford, CA, USA, Project Rep. CS224N, 2009, p. 12.
[4]
A. Pak and P. Paroubek, "Twitter as a corpus for sentiment analysis and opinion mining," in Proc. LREc, vol. 10. 2010, pp. 1320--1326.
[5]
L. Zhang, R. Ghosh, M. Dekhil, M. Hsu, and B. Liu, "Combining lexiconbased and learning-based methods for twitter sentiment analysis," HP Lab., Palo Alto, CA, USA, Tech. Rep. HPL-2011-89, 2011.
[6]
Taboada M, Brooke J, Tofiloski M, et al. Lexicon-based methods for sentiment analysis [J]. Computational Linguistics, 2011, 37(2):267--307.
[7]
Das S, Chen M, Yahoo! for Amazon: Entracting Market Sentiment from Stock Message Boards[C].In:Proceedings of the 8th Asia Pacific Finance Association Annual Conference, 2001.
[8]
Pang B, Lee L, and Vaithyanathan S. Thumbs up?: sentiment classification using machine learning techniques[C].Proceedings of the 2002 conference on Empirical methods in natural language processing (EMNLP 2002).Philadelphia:ACL, 2002:79--86.
[9]
Turney P D, Littman M L. Measuring praise and criticism:Inference of semantic orientation from association[J]. Acm Transactions on Information Systems, 2003, 21(4):315--346
[10]
J. Lin, W. Mao, and D. D. Zeng, "Personality-based refinement for sentiment classification in microblog," Knowl.-Based Syst., vol. 132, pp. 204--214, Sep. 2017.
[11]
A. Tripathy, A. Agrawal, and S. K. Rath, '"Classification of sentiment reviews using n-gram machine learning approach," Expert Syst. Appl., vol. 57, pp. 117--126, Sep. 2016.

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    ICAIP '19: Proceedings of the 2019 3rd International Conference on Advances in Image Processing
    November 2019
    232 pages
    ISBN:9781450376754
    DOI:10.1145/3373419
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    • Southwest Jiaotong University

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    New York, NY, United States

    Publication History

    Published: 24 January 2020

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    Author Tags

    1. Policy
    2. sentiment distribution
    3. social data

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