Generalising Social Structure Using Interval Type-2 Fuzzy Sets

  • Christopher K. FrantzEmail author
  • Bastin Tony Roy Savarimuthu
  • Martin K. Purvis
  • Mariusz Nowostawski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9862)


To understand the operation of the informal social sphere in human or artificial societies, we need to be able to identify their existing behavioural conventions (institutions). This includes the contextualisation of seemingly objective facts with subjective assessments, especially when attempting to capture their meaning in the context of the analysed society. An example for this is numeric information that abstractly expresses attributes such as wealth, but only gains meaning in its societal context. In this work we present a conceptual approach that combines clustering techniques and Interval Type-2 Fuzzy Sets to extract structural information from aggregated subjective micro-level observations. A central objective, beyond the aggregation of information, is to facilitate the analysis on multiple levels of social organisation. We introduce the proposed mechanism and discuss its application potential.


Membership Function Interval Centre Lower Membership Function Input Interval Social Cluster 
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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Christopher K. Frantz
    • 1
    Email author
  • Bastin Tony Roy Savarimuthu
    • 2
  • Martin K. Purvis
    • 2
  • Mariusz Nowostawski
    • 3
  1. 1.College of Enterprise and DevelopmentOtago PolytechnicDunedinNew Zealand
  2. 2.Department of Information ScienceUniversity of OtagoDunedinNew Zealand
  3. 3.Faculty of Computer Science and Media TechnologyNorwegian University of Science and TechnologyGjøvikNorway

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