Using the Gini coefficient to calculate the degree of consensus in group decision making process

Nowadays, almost all people in the world can communicate and exchange information on the Internet. The Internet is an open structure where everyone can express their opinions. In social networks millions of users are registered around the world, and the data of their interaction can be used for specific purposes, for instance, in group decision making problems. Therefore, social network is one of the best environments to raise any questions, discuss them and make decisions. The process of reaching consensus and many different approaches to the solution of this problem have already been well studied. In recent years, modeling of the process of reaching consensus in the context of social networks is of special interest. In addition, the development of improved structures for GDM processes and consensus decision making is actual now, as they can be used in new social networking services. Group decision making is the process of selecting the best alternative or a set of alternatives from all possible. In conditions that are far from reality, decision-makers come to full agreement. However, most often such result is impossible. Actually, it is interesting to understand how much the experts had reached agreement through discussion. Calculation of the degree of agreement usually requires the calculation and aggregation of distance measures, which assess how close each expert's preferences to each pair of alternatives. Such calculations can have long time in view of the selected aggregation operator and require the construction of a collective preference matrix before it can be obtained. In this paper we propose to use the Gini coefficient and present the formula, which shows the degree of agreement between the experts. We also offer a method for assessing the effectiveness of consensus reached by decision-makers. Copyright © 2018 for the individual papers by the papers' authors.

Сборник материалов конференции
  • 1 Peoples' Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya St., Moscow, 117198, Russian Federation
  • 2 Faculty of Electrical Engineering and Communication, Brno University of Technology, 3058/10 Technická, Brno, 61600, Czech Republic
  • 3 Federal Research Center Computer Science and Control, Russian Academy of Sciences (FRC CSC RAS), 44-2 Vavilov St., Moscow, 119333, Russian Federation
Ключевые слова
Consensus level; Fuzzy logic; Gini coefficient; Group decision making; Social network analysis
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