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Differential Equation Models Derived from an Individual-Based Model Can Help to Understand Emergent Effects

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Abstract

We study a model of primacy effect on individual's attitude. Typically, when receiving a strong negative feature first, the individual keeps a negative attitude whatever the number of moderate positive features it receives afterwards. We consider a population of individuals, which receive the features from a media, and communicate with each other. We observe that interactions favour the primacy effect, compared with a population of isolated individuals. We derive a differential equation system ruling the evolution of probabilities that individuals retain different sets of features. The study of this aggregated model of the IBM shows that interaction can increase or decrease the number of individuals exhibiting a primacy effect. We verify on the IBM that the interactions can decrease the primacy effect in the conditions suggested by the study of the aggregated model. We finally discuss the interest of such a double-modelling approach (using a model of the individual based model) for this application.

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  • Sylvie Huet & Guillaume Deffuant, 2008. "Differential Equation Models Derived from an Individual-Based Model Can Help to Understand Emergent Effects," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-10.
    • Handle: RePEc:jas:jasssj:2007-74-2
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    1. Haugtvedt, Curtis P & Wegener, Duane T, 1994. "Message Order Effects in Persuasion: An Attitude Strength Perspective," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(1), pages 205-218, June.
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    5. Margaret Edwards & Sylvie Huet & François Goreaud & Guillaume Deffuant, 2003. "Comparing an Individual-Based Model of Behaviour Diffusion with Its Mean Field Aggregate Approximation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 6(4), pages 1-9.
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