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An agent-based model of directed advertising on a social network

Author

Listed:
  • C. Castaldi
  • F. Alkemade

Abstract

Network economics holds the view that individual actions and, in turn aggregate outcomes, are mainly determined by the interaction structure between heterogeneous economic agents. In this paper we study the diffusion of an innovation over a social network. More specifically, we study whether firms that receive only aggregate sales data can learn strategies to increase the size and the speed of the diffusion of their innovation over a network consisting of consumers. In order to do so the firm has to take into account both the characteristics of individual consumers and the topology of the social network. We use evolutionary agent-based experiments to simulate the learning behaviour of the firm and to study the diffusion dynamics. We find that firms can learn directed advertising strategies that take into account both the topology of the social consumer network and the characteristics of the consumer. These learned strategies lead to an increase in both the size and the speed of the innovation diffusion.

Suggested Citation

  • C. Castaldi & F. Alkemade, 2004. "An agent-based model of directed advertising on a social network," Computing in Economics and Finance 2004 221, Society for Computational Economics.
    • Handle: RePEc:sce:scecf4:221
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    Cited by:

    1. Orlando Gomes, 2008. "Can interaction contribute to the explanation of business cycles?," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 35(3), pages 159-173, February.

    More about this item

    Keywords

    social networks; innovation diffusion; agent-based economics;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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