Ordered Weighted Averaging in Social Networks

Manuel Förster (), Michel Grabisch and Agnieszka Rusinowska
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Manuel Förster: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, UCL - Université Catholique de Louvain = Catholic University of Louvain
Authors registered in the RePEc Author Service: Manuel Foerster

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Abstract: We study a stochastic model of influence where agents have yes-no inclinations on some issue, and opinions may change due to mutual influence among the agents. Each agent independently aggregates the opinions of the other agents and possibly herself. We study influence processes modelled by ordered weighted averaging operators. This allows to study situations where the influence process resembles a majority vote, which are not covered by the classical approach of weighted averaging aggregation. We provide an analysis of the speed of convergence and the probabilities of absoption by different terminal classes. We find a necessary and sufficient condition for convergence to consensus and characterize terminal states. Our results can also be used to understand more general situations, where ordered weighted averaging operators are only used to some extend. Furthermore, we apply our results to fuzzy linguistic quantifiers.

Keywords: fuzzy linguistic quantifier; social network; influence; convergence; speed of convergence; consensus; ordered weighted averaging operator; réseau social; vitesse de convergence; moyenne ordonnée pondérée; quantificateur linguistique flou (search for similar items in EconPapers)
Date: 2012-08
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00746988v1
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Published in 2012

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Related works:
Working Paper: Ordered Weighted Averaging in Social Networks (2012)
Working Paper: Ordered Weighted Averaging in Social Networks (2012)
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