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Using Agent Based Modelling to Integrate Data on Attitude Change

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  • Edmund Chattoe-Brown

Abstract

This article has two goals. Firstly, it shows how a relatively novel technique (Agent Based Modelling, hereafter ABM) can integrate different data types that are often used only in separate strands of research (interviews, experiments and surveys). It does this by comparing a well-known ABM of attitude dynamics with an alternative model using data from surveys and experiments. Secondly, the article explains ABM methodology and why it is important to the distinctiveness of ABM as a research method. In particular, the ramifications of differing approaches to ABM calibration and validation are discussed using the two different ABM as examples. The article concludes by showing how ABM might provide a progressive research strategy for integrating different data types and thus different disciplines in attitude research.

Suggested Citation

  • Edmund Chattoe-Brown, 2014. "Using Agent Based Modelling to Integrate Data on Attitude Change," Sociological Research Online, , vol. 19(1), pages 159-174, February.
    • Handle: RePEc:sae:socres:v:19:y:2014:i:1:p:159-174
    DOI: 10.5153/sro.3315
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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. Guillaume Deffuant & Frederic Amblard & Gérard Weisbuch, 2002. "How Can Extremism Prevail? a Study Based on the Relative Agreement Interaction Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(4), pages 1-1.
    3. Ebonya Washington & Sendhil Mullainathan, 2009. "Sticking with Your Vote: Cognitive Dissonance and Political Attitudes," American Economic Journal: Applied Economics, American Economic Association, vol. 1(1), pages 86-111, January.
    4. Gary Mckeown & Noel Sheehy, 2006. "Mass Media and Polarisation Processes in the Bounded Confidence Model of Opinion Dynamics," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-11.
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    Cited by:

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    2. Liu, Yun & Onggo, Bhakti Stephan & Busby, Jerry, 2024. "Agent-based modelling of user engagement in new product development," Technovation, Elsevier, vol. 135(C).

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