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Theory of Opinion Distribution in Human Relations Where Trust and Distrust Mixed

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Intelligent Decision Technologies (IDT 2020)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 193))

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Abstract

In this paper, we simulated based on the theory of the dynamics of a recent new opinion that incorporates both trust and distrust in human relationships. As a result, it was observed that the aspect of consensus building depends on the ratio between the confidence coefficient and the distrust coefficient. For the model proposed in this study, the ratio of confidence factor to mistrust tended to change, like a phase transition near 55%. This implies that 55% of the connections between people are sufficient for a Esociety to reach consensus.

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References

  1. Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Rev. Mod. Phys. 81, 591–646 (2009)

    Article  Google Scholar 

  2. Sîrbu, A., Loreto, V., Servedio, V.D.P., Tria, F.: Opinion dynamics: models, extensions and external effects. In: Loreto, V., et al. (eds.) Participatory Sensing, Opinions and Collective Awareness. Understanding Complex Systems. Springer, Cham (2017)

    Google Scholar 

  3. Deffuant, G., Neau, D., Amblard, F., Weisbuch, G.: Mixing beliefs among interacting agents. Adv. Complex Syst. 3, 87–98 (2000)

    Article  Google Scholar 

  4. Weisbuch, G., Deffuant, G., Amblard, F., Nadal, J.P.: Meet, discuss and Segéregate! Complexity 7(3), 55–63 (2002)

    Article  Google Scholar 

  5. Hegselmann, R., Krause, U.: Opinion dynamics and bounded confidence models, analysis, and simulation. J. Artif. Soc. Soc. Simul. 5, 1–33 (2002)

    Google Scholar 

  6. Ishii, A., Kawahata, Y.: Opinion dynamics theory for analysis of consensus formation and division of opinion on the internet. In: Proceedings of The 22nd Asia Pacific Symposium on Intelligent and Evolutionary Systems, pp. 71–76 (2018). arXiv:1812.11845 [physics.soc-ph]

  7. Ishii, A.: Opinion dynamics theory considering trust and suspicion in human relations. In: Morais D., Carreras A., de Almeida A., Vetschera R. (eds.) Group Decision and Negotiation: Behavior, Models, and Support. GDN 2019. Lecture Notes in Business Information Processing, vol. 351, pp. 193–204. Springer, Cham (2019)

    Google Scholar 

  8. Ishii, A., Kawahata, Y.: Opinion dynamics theory considering interpersonal relationship of trust and distrust and media effects. In: The 33rd Annual Conference of the Japanese Society for Artificial Intelligence, vol 33. JSAI2019 2F3-OS-5a-05 (2019)

    Google Scholar 

  9. Agarwal, A, Xie, B., Vovsha, I., Rambow, O. and Passonneau, R.: Sentiment analysis of twitter data. In: Proceedings of the Workshop on Languages in Social Media, pp. 30–38. Association for Computational Linguistics (2011)

    Google Scholar 

  10. Siersdorfer, S., Chelaru, S. and Nejdl, W.: How useful are your comments?: Analyzing and predicting youtube comments and comment ratings. In: Proceedings of the 19th International Conference on World Wide Web, pp. 891–900 (2010)

    Google Scholar 

  11. 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 (2005)

    Google Scholar 

  12. Sasahara, H., Chen, W., H Peng, H., Ciampaglia, G. L., Flammini, A., Menczer, F.: On the Inevitability of Online Echo Chambers (2020). arXiv:1905.03919v2

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Acknowledgements

This work was supported by JSPS KAKENHI Grant Number JP19K04881 and “R1 Leading Initiative for Excellent Young Researchers(LEADER)” based on Japan Society for the Promotion of Science(JSPS).

Author information

Authors and Affiliations

  1. Department of Applied Physics, Tottori University, Koyama, Tottori, 680-8552, Japan

    Akira Ishii

  2. Tottori University Cross-Informatics Research Center, Koyama, Tottori, 680-8552, Japan

    Akira Ishii

  3. Center for Computational Social Science, Kobe University, Kobe, 657-8501, Japan

    Akira Ishii

  4. Faculty of Social and Information Studies, Gunma University, 4-2 Aramaki-Machi, Maebashi, Gunma, 371-0044, Japan

    Yasuko Kawahata

Authors
  1. Akira Ishii
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  2. Yasuko Kawahata
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Corresponding author

Correspondence to Akira Ishii .

Editor information

Editors and Affiliations

  1. Gdynia Maritime University, Gdynia, Poland

    Ireneusz Czarnowski

  2. KES International Research, UK

    Robert J. Howlett

  3. Faculty of Engineering and Information Technology, Centre for Artificial Intelligence, University of Technology Sydney, Sydney, NSW, Australia

    Lakhmi C. Jain

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© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Ishii, A., Kawahata, Y. (2020). Theory of Opinion Distribution in Human Relations Where Trust and Distrust Mixed. In: Czarnowski, I., Howlett, R., Jain, L. (eds) Intelligent Decision Technologies. IDT 2020. Smart Innovation, Systems and Technologies, vol 193. Springer, Singapore. https://doi.org/10.1007/978-981-15-5925-9_40

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