skip to main content
10.1145/3508546.3508591acmotherconferencesArticle/Chapter ViewAbstractPublication PagesacaiConference Proceedingsconference-collections
research-article

A Simulation model on the propagation of terrorist ideology in social community

Published: 25 February 2022 Publication History

Abstract

Nowadays, terrorism is rampant but the propagation mechanism of terrorist ideology is still remaining mysterious. For the purpose to understand how terrorists spread their ideas and affect the community, the paper developed an agent-based simulation model based on existed opinion propagation models. By considering the special behavior characteristics of both heterogeneous crowd and terrorist group, the model could describe the process better, and supplied a pattern to compare the impact of different social factors. The results is explainable and consistent with our cognitive. Also, the model could be a supplement to the field of opinion propagation, at the same time understand the terrorism ideology propagation in a quantitative perspective.

References

[1]
Borum, R. (2011). Radicalization into violent extremism i: a review of social science theories. Journal of Strategic Security, 4(4).
[2]
The United Nations. (2015). Plan of action to prevent violent extremism report of the secretary generalL. The 70th conference 16&117.
[3]
Castellano, C., Fortunato, S., & Loreto, V. (2012). Statistical physics of social dynamics. Review of Modern Physics, 81(2), 591-646.
[4]
Weidlich, W. (1971). The statistical description of polarization phenomena in society . British Journal of Mathematical & Statistical Psychology, 24(2), 251–266.
[5]
Galam, S., Gefen, Y., & Shapir, Y. (1982). Sociophysics: a new approach of sociological collective behavior. i. mean-behaviour description of a strike. math soc 9:1-13., 9(1), 1-13.
[6]
Redner, S. (2001). A guide to first-passage processes (cambridge. American Journal of Physics, 70(11), 49-70(22).
[7]
Sznajd-Weron, K. (2004). Dynamical model of ising spins. Physical Review E Statistical Nonlinear & Soft Matter Physics, 70(3 Pt 2), 037104.
[8]
Deffuant, G., Amblard, F., & Weisbuch, G. (2004). Modelling group opinion shift to extreme : the smooth bounded confidence model. HAL - ENS.
[9]
Amblard, F., Deffuant, G., & Weisbuch, G. (2002). How can extremism prevail? a study based on the relative agreement interaction model. Journal of Artificial Societies & Social Simulation, 5(4), 1.
[10]
Deffuant, G. (2006). Comparing extremism propagation patterns in continuous opinion models. Journal of Artificial Societies & Social Simulation, 9(3), 8.
[11]
Kurmyshev, E., Juárez, H. A., & González-Silva, R. A. (2011). Dynamics of bounded confidence opinion in heterogeneous social networks:concord against partial antagonism. Physica A Statistical Mechanics & Its Applications, 390(16), 2945-2955.
[12]
Franks, D. W., Noble, J., Kaufmann, P., & Stagl, S. (2008). Extremism propagation in social networks with hubs. Adaptive Behavior, 16(4), 264-274.
[13]
Chen, S., Wang, G., Yan, G., & Xie, D. (2017). Multi‐dimensional fuzzy trust evaluation for mobile social networks based on dynamic community structures. Concurrency & Computation Practice & Experience.
[14]
Rogers, E. M. (1983). Diffusion of innovations (3rd edition)., 95(1-3), 241–264.
[15]
Helbing, D., & Molnár, P. (1995). Social force model for pedestrian dynamics. Phys.rev.e, 51(5), 4282.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
ACAI '21: Proceedings of the 2021 4th International Conference on Algorithms, Computing and Artificial Intelligence
December 2021
699 pages
ISBN:9781450385053
DOI:10.1145/3508546
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]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 February 2022

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Agent-based modeling
  2. Opinion propagation
  3. System dynamics
  4. Terrorist ideology

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Funding Sources

  • Natural Science Foundation of Hunan Province, China
  • National Nature Science Foundation of China

Conference

ACAI'21

Acceptance Rates

Overall Acceptance Rate 173 of 395 submissions, 44%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 34
    Total Downloads
  • Downloads (Last 12 months)4
  • Downloads (Last 6 weeks)0
Reflects downloads up to 28 Feb 2025

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media