Abstract
The global spread of public networks and social environment systems is not only a positive has some potential downsides aspect. It is transforming us into a society where information exchange, decision making, and consensus building are made across various boundaries. In particular, public opinion tends to decline due owing to the amplification of the echo chambers in unconscious consensus building, and it can be seen that online speech tends to have a major impact on mental health. In this research, the sentiments (Negative/Positive/Neutral), we are obtained from comments made from in response to videos transferred from various news media found on YouTube, which transmits media and information related to our daily lives, and is considered in the analysis of the distribution of opinions in various references.
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References
French, J.R.P.: A formal theory of social power. Psychol. Rev. 63, 181–194 (1956)
Harary, F.: A criterion for unanimity in French ’s theory of social power. In: Cartwright, D. (ed.) Studies in Social Power. Institute for Social Research, Ann Arbor (1959)
Yoshiaki, Z., Sugiyama, M., Yamaki, N.: Group AHP using consensus building model. J. Oper. Res. 40(2), 236–244 (2017)
Yahata, N., et al.: A population interval AHP method using dissatisfaction function. J. Oper. Res. Soc. Japan 45(3), 268–284 (2002)
Yamaki, N., Sekiya, K.: Large-scale AHP with incomplete data (determination theory and related fields) (1998)
Hjarvard, S.: The mediatization of society. Nordicom Rev. 29(2), 102–131 (2008)
Pak, A., Paroubek, P.: Twitter as a corpus for sentiment analysis and opinion mining. LREC 10, 2010 (2010)
Agarwal, A., et al.: Sentiment analysis of Twitter data. In: Proceedings of the Workshop on Languages in Social Media. Association for Computational Linguistics (2011)
Siersdorfer, S., et al.: How useful are your comments?: analyzing and predicting youtube comments and comment ratings. In: Proceedings of the 19th International Conference on World Wide Web. ACM (2010)
Wilson, T., Wiebe, J., Hoffmann, P.: Recognizing contextual polarity in phrase-level sentiment analysis. In: Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing, pp. 347–354. Association for Computational Linguistics, October 2005
Sato, K., et al.: Correlation between web data and stock price fluctuations by negative-positive analysis (2015)
Lasswell, H.D.: The measurement of public opinion. Am. Political Sci. Rev. 25(2), 311–326 (1931)
Lasswell, H.D.: Why be quantitative. Lang. Politics 40–52, 1949 (1949)
Galam, S.: Rational group decision making: a random field Ising model at T = 0. Phys. A 238(1–4), 66–80 (1997)
Sznajd-Weron, K., Sznajd, J.: Opinion evolution in closed community. Int. J. Mod. Phys. C 11(6), 1157–1165 (2000)
Bird, S., Loper, E.: NLTK: the natural language toolkit. In: Proceedings of the ACL 2004 on Interactive Poster and Demonstration Sessions. Association for Computational Linguistics (2004)
Kawahata, Y., Ishii, A.: Consideration of simulation of consensus formation Online using Sociophysics method, GDN 2019 (2019)
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We would like to also thank you for the support from the 2019 Scholarly Scholars Research Grant Program (Leading Initiative for Excellent Young Researchers (LEADER)), which provided support for this research in general.
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Kawahata, Y. (2020). Examination of Analysis Method of Opinion Distribution in News Media Transferred on Web. In: Sato, H., Iwanaga, S., Ishii, A. (eds) Proceedings of the 23rd Asia Pacific Symposium on Intelligent and Evolutionary Systems. IES 2019. Proceedings in Adaptation, Learning and Optimization, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-030-37442-6_14
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