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Research on Multi-Agent Simulation of Epidemic News Spread Characteristics

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  • Xiaoguang Gong
  • Renbin Xiao

Abstract

The spread of news about an epidemic can easily lead to a social panic. In order to devise measures to control such a panic, it is necessary to consider characteristics of the spread of epidemic news, based on mechanisms at the individual level. In this paper, first, some features of multi-agent simulation are reviewed. Then a multi-agent simulation model of epidemic news spread (ENS) is designed and realized. Based on simulation experiments and sensitivity analyses, the influence of social relationships, the degree of trust in news of the epidemic, the epidemic spread intensity and the network structure of the epidemic news spread are studied. The research results include: (1) As the number of social relationships increases, the rate of spread of epidemic news rapidly rises, and the ratio of people who have heard the news directly decreases. The result is that the 'radiation effect' of the epidemic news spread will be enhanced when the number of social relationships increases. (2) With the increase of the degree of trust in the news, the rate of spread of the news will also rapidly increase, but variation in the ratio of the people who have heard the news directly is not significant. This means that the 'radiation effect' of the spread of the news does not change much more in relation to the degree of trust in the epidemic news. (3) The ratio of the people who have heard the news directly increases when the infection range increases (i.e. the spread intensity of epidemic increases), and vice versa. But the variation of the speed of the epidemic news spread is not significant. (4) When the network structure is assumed to be a small world network, the spread speed will be slower than that in a random network with the same average vertex degree and the forgetting speed will be faster than that in a random network with the same average vertex degree.

Suggested Citation

  • Xiaoguang Gong & Renbin Xiao, 2007. "Research on Multi-Agent Simulation of Epidemic News Spread Characteristics," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(3), pages 1-1.
    • Handle: RePEc:jas:jasssj:2006-22-4
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    1. H. N. Agiza & A. S. Elgazzar & S. A. Youssef, 2003. "Phase Transitions In Some Epidemic Models Defined On Small-World Networks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 14(06), pages 825-833.
    2. Chris Goldspink, 2002. "Methodological Implications of Complex Systems Approaches to Sociality: Simulation As a Foundation for Knowledge," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(1), pages 1-3.
    3. Chung-Yuan Huang & Chuen-Tsai Sun & Ji-Lung Hsieh & Holin Lin, 2004. "Simulating SARS: Small-World Epidemiological Modeling and Public Health Policy Assessments," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 7(4), pages 1-2.
    4. A. G. Zawadowski & R. Karadi & J. Kertesz, 2002. "Price Drops, Fluctuations, and Correlation in a Multi-Agent Model of Stock Markets," Papers cond-mat/0204574, arXiv.org.
    5. Zawadowski, A.G & Karádi, R & Kertész, J, 2002. "Price drops, fluctuations, and correlation in a multi-agent model of stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 403-412.
    6. Manfred M. Fischer & Josef Fröhlich (ed.), 2001. "Knowledge, Complexity and Innovation Systems," Advances in Spatial Science, Springer, number 978-3-662-04546-6.
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    2. Erik Johnston & Yushim Kim & Mitali Ayyangar, 2007. "Intending the Unintended: The act of building agent-based models as a regular source of knowledge generation," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 5(2), pages 81-91.
    3. Hua Guo & Jiandong Zhang & Shihui Feng & Boyin Chen & Minhong Wang, 2022. "Risk Communication in the Alert Phase of the COVID-19 Pandemic: Analysis of News Flow at National and Global Levels," IJERPH, MDPI, vol. 19(15), pages 1-20, August.

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