Abstract
The global spread of public networks and social media has transformed us into a society where information exchange, decision making, and consensus building are performed across various boundaries. In particular, public opinion tends to decline owing to the amplification of the echo chamber in unconscious consensus building. Furthermore, it can be seen that online speech has a major impact on mental health. In this study, comments on social media were analyzed and labeled as negative, positive, and neutral based on their sentiments. This was done using comments from various videos on YouTube, which is a social media platform that enables the sharing of videos and information related to our daily lives. Thus, we analyzed the distribution of opinions in various cases.
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References
Shepherd, A., et al.: Using social media for support and feedback by mental health service users: thematic analysis of a twitter conversation. BMC Psychiatry 15(1), 29 (2015)
Doan, S., et al.: Extracting health-related causality from Twitter messages using natural language processing. BMC Med. Inform. Decis. Mak. 19(3), 79 (2019)
French, J.R.P.: A formal theory of social power. Psychol. Rev. 63, 181–194 (1956)
Kawahata, Y.: Examination of analysis method of opinion distribution in News media transferred on web IES2019, in press
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 (1997)
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)
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)
NLTK Project, Natural Language Toolkit. https://www.nltk.org
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We would like to acknowledge the support from the 2019 Scholarly Scholars Research Grant Program (Leading Initiative for Excellent Young Researchers (LEADER)).
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Kawahata, Y. (2020). Opinion Distribution Analysis of Video Media Related to Social Life. 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_15
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DOI: https://doi.org/10.1007/978-3-030-37442-6_15
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