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Understanding Homophily and More-Becomes-More Through Adaptive Temporal-Causal Network Models

  • Sven van den Beukel
  • Simon H. Goos
  • Jan TreurEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 619)

Abstract

This study describes the use of adaptive temporal-causal networks to model and simulate the development of mutually interacting opinion states and connections between individuals in social networks. The focus is on adaptive networks combining the homophily principle with the more becomes more principle. The model has been used to analyse a data set concerning opinions about the use of alcohol and tobacco, and friendship relations. The achieved results provide insights in the potential of the approach.

Keywords

Homophily More becomes more Temporal-causal networks Alcohol Tobacco 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Sven van den Beukel
    • 1
  • Simon H. Goos
    • 1
  • Jan Treur
    • 1
    Email author
  1. 1.Behavioural Informatics GroupVrije Universiteit AmsterdamAmsterdamThe Netherlands

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