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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
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Multidimensional attributes expose Heider balance dynamics to measurements.

Joanna Linczuk1, Piotr J Górski2, Boleslaw K Szymanski3,4

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Heider Balance Theory dynamics are observable when edge signs reflect multidimensional opinions. This study demonstrates how to empirically measure triadic influence in social networks using student opinion data.

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Area of Science:

  • Social Network Analysis
  • Computational Social Science
  • Psychological Theory

Background:

  • Social interactions are often studied as dyadic relationships.
  • Heider Balance Theory posits triadic dynamics, but empirical observation has been challenging.

Purpose of the Study:

  • To discover a condition for observing Heider dynamics.
  • To model and measure triadic influence in social networks based on multidimensional opinions.

Main Methods:

  • Utilized longitudinal records of university student contacts and opinions.
  • Developed coevolving network models incorporating opinion multidimensionality and influence on relations.
  • Defined edge signs based on multidimensional opinion differences.

Main Results:

  • Triadic influence is empirically measurable when edge signs reflect multidimensional opinion differences.
  • When edge signs are based on single-topic opinion differences, triadic influence becomes indistinguishable from noise.

Conclusions:

  • Multidimensionality of opinions is crucial for observing Heider dynamics.
  • The study provides a method for empirically validating triadic influence in social networks.