Determining Models of Influence

We consider a model of opinion formation based on aggregation functions. Each player modifies his opinion by arbitrarily aggregating the current opinion of all players. A player is influential on another player if the opinion of the first one matters to the latter. Generalization of an influential p...

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Main Authors: Michel Grabisch, Agnieszka Rusinowska
Format: Article
Language:English
Published: Wrocław University of Science and Technology 2016-01-01
Series:Operations Research and Decisions
Online Access:http://orduser.pwr.wroc.pl/DownloadFile.aspx?aid=1222
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spelling doaj-e146b8279e6d46bea841cd271123571a2020-11-24T21:02:13ZengWrocław University of Science and TechnologyOperations Research and Decisions2081-88582391-60602016-01-01vol. 26no. 26985171442022Determining Models of InfluenceMichel Grabisch0Agnieszka Rusinowska1Paris School of Economics - CNRS, Université Paris I Panthéon-SorbonneParis School of Economics - CNRS, Université Paris I Panthéon-SorbonneWe consider a model of opinion formation based on aggregation functions. Each player modifies his opinion by arbitrarily aggregating the current opinion of all players. A player is influential on another player if the opinion of the first one matters to the latter. Generalization of an influential player to a coalition whose opinion matters to a player is called an influential coalition. Influential players (coalitions) can be graphically represented by the graph (hypergraph) of influence, and convergence analysis is based on properties of the hypergraphs of influence. In the paper, we focus on the practical issues of applicability of the model w.r.t. a standard framework for opinion formation driven by Markov chain theory. For a qualitative analysis of convergence, knowing the aggregation functions of the players is not required, one only needs to know the set of influential coalitions for each player. We propose simple algorithms that permit us to fully determine the influential coalitions. We distinguish three cases: a symmetric decomposable model, an anonymous model, and a general model. (original abstract)http://orduser.pwr.wroc.pl/DownloadFile.aspx?aid=1222
collection DOAJ
language English
format Article
sources DOAJ
author Michel Grabisch
Agnieszka Rusinowska
spellingShingle Michel Grabisch
Agnieszka Rusinowska
Determining Models of Influence
Operations Research and Decisions
author_facet Michel Grabisch
Agnieszka Rusinowska
author_sort Michel Grabisch
title Determining Models of Influence
title_short Determining Models of Influence
title_full Determining Models of Influence
title_fullStr Determining Models of Influence
title_full_unstemmed Determining Models of Influence
title_sort determining models of influence
publisher Wrocław University of Science and Technology
series Operations Research and Decisions
issn 2081-8858
2391-6060
publishDate 2016-01-01
description We consider a model of opinion formation based on aggregation functions. Each player modifies his opinion by arbitrarily aggregating the current opinion of all players. A player is influential on another player if the opinion of the first one matters to the latter. Generalization of an influential player to a coalition whose opinion matters to a player is called an influential coalition. Influential players (coalitions) can be graphically represented by the graph (hypergraph) of influence, and convergence analysis is based on properties of the hypergraphs of influence. In the paper, we focus on the practical issues of applicability of the model w.r.t. a standard framework for opinion formation driven by Markov chain theory. For a qualitative analysis of convergence, knowing the aggregation functions of the players is not required, one only needs to know the set of influential coalitions for each player. We propose simple algorithms that permit us to fully determine the influential coalitions. We distinguish three cases: a symmetric decomposable model, an anonymous model, and a general model. (original abstract)
url http://orduser.pwr.wroc.pl/DownloadFile.aspx?aid=1222
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