THE ROLE OF AGENT-BASED MODELING AND COMPUTER SIMULATIONS IN POLITICAL SCIENCE
Abstract
It considers opportunities for using computer agent-based modeling in studies related to political process analyses. Gives information about the historical context of computer simulation based on agent model implementation, and emphasizes the significance of T. Shelling and R. Axelrod models. It is noted usefulness of this method is applied to complex dynamic system analysis, wherein participants have complex interconnections, and their behavior depends on the situation.
Gives information about an agent-based model's main elements, especially space and agents, and describes what they can represent. Draws attention to the importance of the researcher’s study goal understanding using this approach, which in turn affects the model parameters setting that determines model will be abstract, realistic, or mixed.
Considered opportunities applying agent-based modeling for the course of social and political processes forecasting, and showed the opinion of other researchers on this issue.
Provides examples of ten studies related to the analysis of various political processes, the authors of which applied this approach and their own agent models with different realism levels.
Shows possibilities applied of computer simulations for forecasting the results of future and reproducing the results of past elections, evaluating election campaign strategies, the emergence of ideological polarization, modeling political discourse, evaluating the effectiveness of implemented policies, analyzing the risks of social instability in the state under the influence of external and internal factors.
It is concluded that agent-based modeling can be a helpful tool in the hands of political scientists and noted that the use of this approach significantly expands the possibilities for analyzing complex political processes.
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References
Chornenkyi Oleksandr. 2022. Use of Information and Communication Technologies for Political Science Research. The journal of V. N. Karazin Kharkiv National University. Series «Issues of Political Science» 42: 38-44. https://doi.org/10.26565/2220-8089-2022-42-06
Klein, D., Marx, J., &Fischbach, K. 2018. Agent-based modeling in social science, history, and philosophy. An introduction. Historical Social Research, Historische Sozial for schung 43(1): 7-27. https://doi.org/10.12759/hsr.43.2018.1.7-27
Fischbach, K., Marx, J. &Weitzel, T. 2021. Agent-based modeling in social sciences, Journal of Business Economics 91: 1263–1270. https://doi.org/10.1007/s11573-021-01070-9
Voinea, C. F. 2016. Politica lAttitudes. Computational and Simulation Modelling. Chichester: John Wiley&Sons, Ltd. 306 p.
Johnson, P. E. 1999. Simulation Modelingin Political Science, American Behaviora lScientist Vol. 42, Iss. 10 : 1509-1530. https://doi.org/10.1177/0002764299042010004
Axelrod, R. 1980. Effective choice in the prisoner's dilemma, Journal of conflict resolution, Vol. 24, Iss. 1, 3-25. https://doi.org/10.1177/002200278002400101
Schelling, T. C. 1969. Models of segregation, The American economic review 59(2), 488-493.
Bruch, E., &Atwell, J. 2015. Agent-based model sinempirical social research. Sociological methods&research,Vol. 44, Iss.2 : 186-221. https://doi.org/10.1177/0049124113506405
Macy, M. W.&Willer, R. 2002. From factors to actors: Computational sociology and agent-based modeling, Annual Review of Sociology, Vol. 28(1): 143-166. https://doi.org/10.1146/annurev.soc.28.110601.141117
Bankes, S., Lempert, R., & Popper, S. 2002. Making computational social science effective: Epistemology, methodology, and technology, Social Science Computer Review, Vol. 20 Iss. 4: 377-388. https://doi.org/10.1177/089443902237317
Chattoe-Brown, E. 2023. Is agent-based modelling the future of prediction? International Journal of Social Research Methodology Vol. 26 Iss. 2: 143-155. https://doi.org/10.1080/13645579.2022.2137923
Gao, M., Wang, Z., Wang, K., Liu, C., & Tang, S. 2022. Forecasting elections with agent-based modeling: Two live experiments, Plos one, 17(6), e0270194. https://doi.org/10.1371/journal.pone.0270194
Kononovicius, A. 2017. Empirical analysis and agent-based modeling of the Lithuanian parliamentary elections. Complexity, 2017 .https://doi.org/10.1155/2017/7354642
Madsen, J. K., & Pilditch, T. D. 2018. A method for evaluating cognitively informed micro-targeted campaign strategies: An agent-based model proof of principle. PloS one 13(4): e0193909. https://doi.org/10.1371/journal.pone.0193909
Axelrod, R., Daymude, J. J., & Forrest, S. 2021. Preventing extreme polarization of political attitudes, Proceedings of the National Academy of Sciences, 118(50), e2102139118. https://doi.org/10.1073/pnas.2102139118
Schweighofer, S., Garcia, D., & Schweitzer, F. 2020. An agent-based model of multi-dimensional opinion dynamics and opinion alignment. Chaos: An Interdisciplinary Journal of Nonlinear Science, 30(9) https://doi.org/10.1063/5.0007523
Leifeld, P. 2014. Polarization of coalitions in an agent-based model of political discourse, Computational Social Networks 1(1), 1-22. https://doi.org/10.1186/s40649-014-0007-y
Dosi, G., Roventini, A., & Russo, E. 2021. Public policies and the art of catching up: matching the historical evidence with a multicountry agent-based model, Industrial and Corporate Change, Vol. 30, Iss. 4: 1011-1036. https://doi.org/10.1093/icc/dtaa057
Ceschi, A., Sartori, R., Dickert, S., Scalco, A., Tur, E. M., Tommasi, F., & Delfini, K. 2021. Testing a norm-based policy for waste management: An agent-based modeling simulation on nudging recycling behavior, Journal of Environmental Management, 294, 112938. https://doi.org/10.1016/j.jenvman.2021.112938
Natalini, D., Bravo, G., & Jones, A. W. 2019. Global food security and food riots–an agent-based modelling approach. Food Security, 11, 1153-1173 .https://doi.org/10.1007/s12571-017-0693-z
Cioffi-Revilla, C., & Rouleau, M. 2010. MASON RebeLand: An agent-based model of politics, environment, and insurgency. International Studies Review 12(1), 31-52 . https://doi.org/10.1111/j.1468-2486.2009.00911.x
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