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Fuzzy Networks

  • Dawn Iacobucci
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 258)

Abstract

Knowledge discovery and fuzzy logic have great potential for social network models. Networks are currently extraordinarily popular, and while it’s fun to work in an area that people find interesting, there is such a thing as a topic being too popular. Networks are too popular in the sense that they are not widely understood by users, hence they are thought to be the new, new thing, capable of answering all questions, from “Will my brand’s presence on Facebook help its equity?” to “ Will a network bring peace to the Middle East?” Fuzzy logic should help new users proceed from naïve enthusiasm to thoughtful application, because fuzzification embraces approximation; huge questions cannot be answered with simple, precise estimates, but a fuzzy approach can put the inquirer in the rough vicinity of an answer (Martínez-López and Casillas, 2008).

Keywords

Fuzzy Logic Brand Community Fuzzy Network Recommendation Agent Suggested Item 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Iacobucci, D., Arabie, P., Bodapati, A.: Recommendation Agents on the Internet. Journal of Interactive Marketing 14(3), 2–11 (2000)CrossRefGoogle Scholar
  2. Knoke, D., Yang, S.: Social Network Analysis, 2nd edn. Sage, Thousand Oaks (2007)Google Scholar
  3. Martinez-Lopez, F.J., Casillas, J.: Marketing Intelligent Systems for Consumer Behavior Modeling by a Descriptive Induction Approach Based on Genetic Fuzzy Systems. Industrial Marketing Management Press (2008), doi:10.1016/j.indmarman.2008.02.003Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Dawn Iacobucci
    • 1
  1. 1.E. Bronson Ingram Professor in Marketing, Owen Graduate School of ManagementVanderbilt UniversityNashvilleUSA

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