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Why Sociology Should Use Agent Based Modelling

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  • Edmund Chattoe-Brown

Abstract

Although Agent Based Models (hereafter ABM) are now regularly reported in sociology journals, explaining the approach, describing models and reporting results leaves little opportunity to examine wider implications of ABM for sociological practice. This article uses an established ABM (the Schelling model) for this. The first part argues that ABM integrates qualitative and quantitative data distinctively, provides novel tools for understanding social causes and offers a significantly different perspective on theory building. The second part shows how the emerging ABM methodology is compatible with existing sociological practice while undermining several criticisms of ABM perceived to limit its sociological relevance.

Suggested Citation

  • Edmund Chattoe-Brown, 2013. "Why Sociology Should Use Agent Based Modelling," Sociological Research Online, , vol. 18(3), pages 31-41, August.
  • Handle: RePEc:sae:socres:v:18:y:2013:i:3:p:31-41
    DOI: 10.5153/sro.3055
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    References listed on IDEAS

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    1. Erez Hatna & Itzhak Benenson, 2012. "The Schelling Model of Ethnic Residential Dynamics: Beyond the Integrated - Segregated Dichotomy of Patterns," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(1), pages 1-6.
    2. Oliver Will, 2009. "Resolving a Replication That Failed: News on the Macy & Sato Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(4), pages 1-11.
    3. Hessel Oosterbeek & Randolph Sloof & Gijs van de Kuilen, 2004. "Cultural Differences in Ultimatum Game Experiments: Evidence from a Meta-Analysis," Experimental Economics, Springer;Economic Science Association, vol. 7(2), pages 171-188, June.
    4. J. Gareth Polhill & Lee-Ann Sutherland & Nicholas M. Gotts, 2010. "Using Qualitative Evidence to Enhance an Agent-Based Modelling System for Studying Land Use Change," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(2), pages 1-10.
    5. Molana, H, 1993. "The Role of Income in the Consumption Function: A Review of On-Going Developments," Scottish Journal of Political Economy, Scottish Economic Society, vol. 40(3), pages 335-352, August.
    6. Edmund Chattoe & Nigel Gilbert, 2001. "Understanding Consumption: What Interviews with Retired Households Can Reveal about Budgetary Decisions," Sociological Research Online, , vol. 6(3), pages 1-12, November.
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    Cited by:

    1. Ngo-Hoang, Dai-Long, 2019. "A research paper of Hossein Sabzian (2019), Theories and Practice of Agent based Modeling: Some practical Implications for Economic Planners, ArXiv, 54p," AgriXiv xutyz, Center for Open Science.
    2. Alireza Mansouri & Fattaneh Taghiyareh, 2020. "Phase Transition in the Social Impact Model of Opinion Formation in Scale-Free Networks: The Social Power Effect," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 23(2), pages 1-3.
    3. Kenneth Hemmerechts & Nohemi Jocabeth Echeverria Vicente & Dimokritos Kavadias, 2017. "The Order of Human Interdependencies: Simulating Elias’ One-level Multi-person Models," Sociological Research Online, , vol. 22(4), pages 105-131, December.
    4. Chappin, Emile J.L. & Schleich, Joachim & Guetlein, Marie-Charlotte & Faure, Corinne & Bouwmans, Ivo, 2022. "Linking of a multi-country discrete choice experiment and an agent-based model to simulate the diffusion of smart thermostats," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    5. Hossein Sabzian & Mohammad Ali Shafia & Ali Maleki & Seyeed Mostapha Seyeed Hashemi & Ali Baghaei & Hossein Gharib, 2019. "Theories and Practice of Agent based Modeling: Some practical Implications for Economic Planners," Papers 1901.08932, arXiv.org.

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