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Diffusion of Multiple Information

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  • Nicole Tabasso

    (University of Surrey)

Abstract

We model the diffusion of two types of information through a population under the assumption that communication time is limited. When a meeting between individuals occurs, at most one information can be communicated. Preferences over information types divide the population into two groups, and if a choice has to be made about which information to communicate, members of either group will choose their preferred information. We find that crowding out of information does occur, but information is rarely eradicated entirely. Somewhat surprisingly, the parameter values under which a unique information would survive in the population are sufficient for both information to survive. Only if in- formation preferences in the entire population are aligned, i.e., every individual prefers to communicate the same information, does the second information die out. We apply our framework to answer questions on the impact that segregation has on information diffusion and polarization. We find that segregation unambiguously increases polarization and decreases the proportions of informed individuals, and derive the conditions under which agents endogenously choose to segregate.

Suggested Citation

  • Nicole Tabasso, 2014. "Diffusion of Multiple Information," School of Economics Discussion Papers 0914, School of Economics, University of Surrey.
  • Handle: RePEc:sur:surrec:0914
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    File URL: https://repec.som.surrey.ac.uk/2014/DP09-14.pdf
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    References listed on IDEAS

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    Cited by:

    1. Halberstam, Yosh & Knight, Brian, 2016. "Homophily, group size, and the diffusion of political information in social networks: Evidence from Twitter," Journal of Public Economics, Elsevier, vol. 143(C), pages 73-88.

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    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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