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Information Feedback and Mass Media Effects in Cultural Dynamics

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Abstract

We study the effects of different forms of information feedback associated with mass media on an agent-agent based model of the dynamics of cultural dissemination. In addition to some processes previously considered, we also examine a model of local mass media influence in cultural dynamics. Two mechanisms of information feedback are investigated: (i) direct mass media influence, where local or global mass media act as an additional element in the network of interactions of each agent, and (ii) indirect mass media influence, where global media acts as a filter of the influence of the existing network of interactions of each agent. Our results generalize substantiate previous findings showing that cultural diversity builds-up by increasing the strength of the mass media influence. We find that this occurs independently of the mechanisms of action (direct or indirect) of the mass media message. However, through an analysis of the full range of parameters measuring cultural diversity, we establish that the enhancement of cultural diversity produced by interaction with mass media only occurs for strong enough mass media messages. In comparison with previous studies a main different result is that weak mass media messages, in combination with agent-agent interaction, are efficient in producing cultural homogeneity. Moreover, the homogenizing effect of weak mass media messages are more efficient for direct local mass media messages than for global mass media messages or indirect global mass media influences.

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  • Juan Carlos González-Avella & Mario G. Cosenza & Konstantin Klemm & Víctor M. Eguíluz & Maxi San Miguel, 2007. "Information Feedback and Mass Media Effects in Cultural Dynamics," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(3), pages 1-9.
    • Handle: RePEc:jas:jasssj:2007-6-2
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    1. Loet Leydesdorff, 2001. "Technology and Culture: the Dissemination and the Potential 'Lock-In' of New Technologies," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 4(3), pages 1-5.
    2. Ravi Bhavnani, 2003. "Adaptive Agents, Political Institutions and Civic Traditions in Modern Italy," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 6(4), pages 1-1.
    3. Klemm, Konstantin & Eguiluz, Victor M. & Toral, Raul & Miguel, Maxi San, 2005. "Globalization, polarization and cultural drift," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 321-334, January.
    4. Klemm, Konstantin & Eguı́luz, Vı́ctor M & Toral, Raúl & Miguel, Maxi San, 2003. "Role of dimensionality in Axelrod's model for the dissemination of culture," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 327(1), pages 1-5.
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    5. Pfau, Jens & Kirley, Michael & Kashima, Yoshihisa, 2013. "The co-evolution of cultures, social network communities, and agent locations in an extension of Axelrod’s model of cultural dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(2), pages 381-391.
    6. Yaofeng Zhang & Renbin Xiao, 2015. "Modeling and Simulation of Polarization in Internet Group Opinions Based on Cellular Automata," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-15, August.
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