کاربست مدلهای عامل بنیان در تحلیل اطلاعاتی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشیار دانشکده و پژوهشکده پیامبر اعظم (ص) دانشگاه جامع امام حسین(ع)، تهران، ایران

2 دانشجو دکتری تحلیل اطلاعات دانشکده و پژوهشکده پیامبر اعظم (ص) دانشگاه جامع امام حسین(ع)، تهران، ایران

چکیده

علوم اجتماعی محاسباتی[1] یک رویکرد بین رشته‌ای و نوظهور به مطالعه سیستم‌های اجتماعی است. در اینجا بررسی می‌کنیم که چرا آزمایش رفتار افراد و گروه‌ها در سیستم‌های اجتماعی از یک نقطه نظر الگوریتمی فرصت‌های تحلیلی جدید و شگفت‌آوری را برای جامعه اطلاعاتی و به جهت ارتقای روش‌های تحلیل اطلاعاتی فراهم می‌آورد. با بکارگیری جوامع مصنوعی[1] که عموماً به آن‌ها مدلهای عامل بنیان[1] گفته می‌شود، تحلیلگران اطلاعاتی می‌توانند ارزیابی‌های اطلاعاتی خود را به وسیله منافع برامده از اصول علمی محاسبات کامپیوتری ارتقا دهند. یافته‌های پژوهش نشان می‌دهد که مدلسازی عامل بنیان در ادبیات امنیتی-اطلاعاتی کاربرد چشمگیری یافته بنحوی که مدلسازی آشوب‌های اجتماعی، بحران، فریب اطلاعاتی و جنگ روزبه روز غنای بیشتری می‌یابند.

کلیدواژه‌ها


عنوان مقاله [English]

Application of Factor-Based Models in Intelligence Analysis

نویسندگان [English]

  • Hossein Hosseini 1
  • Saeed Mohammadi 2
1 Associate Professor of the Faculty and Research Institute of the Great Prophet (pbuh), Imam Hossein University (pbuh), Tehran, Iran
2 Ph.D. student of Intelligence Analysis of the Faculty and Research Institute of the Great Prophet (pbuh), Imam Hossein (pbuh) University, Tehran, Iran
چکیده [English]

Computational social science is an emerging interdisciplinary approach to the study of social systems. Here we examine why testing the behavior of individuals and groups in social systems from an algorithmic point of view provides new and surprising analytical opportunities for the intelligence society and for the improvement of intelligence analysis methods. By using artificial communities, which are generally called factor-based models, intelligence analysts can improve their intelligence evaluations through the benefits of scientific principles of computer computing. The findings of the research show that factor-based modeling has been significantly used in the security- intelligence literature in such a way that the modeling of socialunrest, crisis, intelligence deception, and war are getting richer day by day

کلیدواژه‌ها [English]

  • .
Adhikari, A. et al. (2023) ‘Agent Based Modeling of the Spread of Social Unrest Using Infectious Disease Models’, ACM Transactions on Spatial Algorithms and Systems [Preprint]. Available at: https://doi.org/10.1145/3587463.
Bosse, S. (2021) ‘Large-Scale Agent-Based Simulation and Crowd Sensing with Mobile Agents’, in Handbook of Computational Social Science, Volume 2. Routledge.
Cartes, C. (2022) ‘Mathematical modeling of the Chilean riots of 2019: An epidemiological non-local approach’, Chaos (Woodbury, N.Y.), 32(12), p. 123113. Available at: https://doi.org/10.1063/5.0116750.
Conte, R. and Paolucci, M. (2014) ‘On agent-based modeling and computational social science’, Frontiers in Psychology, 5, p. 668. Available at: https://doi.org/10.3389/fpsyg.2014.00668.
Davis, P.K., O’Mahony, A. and Pfautz, J. (eds) (2019) Social-Behavioral Modeling for Complex Systems. 1st edition. Hoboken, NJ: Wiley.
DeAngelis, D.L. and Diaz, S.G. (2019) ‘Decision-Making in Agent-Based Modeling: A Current Review and Future Prospectus’, Frontiers in Ecology and Evolution, 6. Available at: https://www.frontiersin.org/article/10.3389/fevo.2018.00237 (Accessed: 13 January 2022).
Epstein, J.M. (2002) ‘Modeling civil violence: An agent-based computational approach’, Proceedings of the National Academy of Sciences of the United States of America, 99(Suppl 3), pp. 7243–7250. Available at: https://doi.org/10.1073/pnas.092080199.
Frank, A. (2017) ‘Computational social science and intelligence analysis’, Intelligence and National Security, 32(5), pp. 579–599. Available at: https://doi.org/10.1080/02684527.2017.1310968.
Gaeta, A., Loia, V. and Orciuoli, F. (2021) ‘A comprehensive model and computational methods to improve Situation Awareness in Intelligence scenarios’, Applied Intelligence, 51(9), pp. 6585–6608. Available at: https://doi.org/10.1007/s10489-021-02673-z.
Jager, W. (2021) ‘Using agent-based modelling to explore behavioural dynamics affecting our climate’, Current Opinion in Psychology, 42, pp. 133–139. Available at: https://doi.org/10.1016/j.copsyc.2021.06.024.
Lemos, C., Lopes, R.J. and Coelho, H. (2016) ‘On Legitimacy Feedback Mechanisms in Agent-Based Modeling of Civil Violence’, International Journal of Intelligent Systems, 31(2), pp. 106–127. Available at: https://doi.org/10.1002/int.21747.
Sabzian, H. et al. (2018) ‘A review of agent-based modeling (ABM) concepts and some of its main applications in management science’, Iranian Journal of Management Studies, 11(4), pp. 659–692. Available at: https://doi.org/10.22059/ijms.2018.261178.673190.
Scholz, G. et al. (2021) ‘Social Identity in Agent-Based Models—Exploring the State of the Art’, in P. Ahrweiler and M. Neumann (eds) Advances in Social Simulation. Cham: Springer International Publishing (Springer Proceedings in Complexity), pp. 59–64. Available at: https://doi.org/10.1007/978-3-030-61503-1_6.
Spoor, B. and Rothman, M. (2021) ‘On the critical utility of complexity theory in intelligence studies’, Intelligence and National Security, 36(4), pp. 555–568. Available at: https://doi.org/10.1080/02684527.2021.1893076.
Thron, C. and Jackson, E. (2015) ‘Practicality of Agent-Based Modeling of Civil Violence: an Assessment’. arXiv. Available at: https://doi.org/10.48550/arXiv.1501.05838.