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Decision making in social networks
Author(s) -
Squillante Massimo
Publication year - 2010
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.20397
Subject(s) - citation , computer science , library science , world wide web , sociology , operations research , mathematics
The aim of this special issue is to present different approaches to decision making in social networks, based on analytical and algebraic tools. Decision-making procedures that apply in many fields of economic and social sciences can be usefully modeled by algebraic and ordered structures. The special issue is composed of the contributions that we describe in the following. The problem to characterize stable social networks is managed by G. De Marco in “On the Effects of Heterogeneity in One-way Flow Network Formation” and the related results are obtained by considering the concept of Pareto–Nash equilibrium and its refinements. M. Eboli provides an algorithm that enables us to evaluate diffusion of events and actions across networks of agents; the algorithm works for networks representable by weighted directed graphs; several applications for social and financial diffusion events are shown. In the paper, “Centrality in organizational networks” Grassi, S. Stefani and A. Torriero analyze the role of individuals in organizational networks, based on topological graph theoretical arguments and centrality measures; a case study concerning an ICT consulting company is presented. A. Maturo and A. Ventre in the paper “Reaching Consensus in Multiagent Decision Making” describe a procedure and a suitable algorithm for obtaining consensus in a group decision context; the judgements of the experts are represented by points of a metric space and the consensus is managed by a construction whose dynamics is controlled in a game theoretical context, in terms of a maximal winning coalition contained in a ball with a fixed and suitably small diameter. In the paper, M. Squillante and V. Ventre, “Assessing False Consensus Effects in a Consensus-Enhancing Procedure” false consensus effect is examined, which represents the tendency to overestimate consensus for one’s attitudes and behavior. The consensus-reaching process is modeled within fuzzy set theory by ordered weighted averaging operators.