Carrying out consensual Group Decision Making processes under social networks using sentiment analysis over comparative expressions

Social networks are the most preferred mean for the people to communicate. Therefore, it is quite usual that experts use them to carry out Group Decision Making processes. One disadvantage that recent Group Decision Making methods have is that they do not allow the experts to use free text to express themselves. On the contrary, they force them to follow a specific user–computer communication structure. This is against social network nature where experts are free to express themselves using their preferred text structure. This paper presents a novel model for experts to carry out Group Decision Making processes using free text and alternatives pairwise comparisons. The main advantage of this method is that it is designed to work using social networks. Sentiment analysis procedures are used to analyze free texts and extract the preferences that the experts provide about the alternatives. Also, our method introduces two ways of applying consensus measures over the Group Decision Making process. They can be used to determine if the experts agree among them or if there are different postures. This way, it is possible to promote the debate in those cases where consensus is low. © 2018 The Authors

Authors
Morente-Molinera J.A.1 , Kou G.2 , Samuylov K. 3 , Ureña R.4 , Herrera-Viedma E. 1, 5
Publisher
Elsevier B.V.
Language
English
Pages
335-345
Status
Published
Volume
165
Year
2019
Organizations
  • 1 Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain
  • 2 School of Business Administration, Southwestern University of Finance and Economics, Chengdu, China
  • 3 Peoples’ Friendship University of Russia (RUDN University), Moscow, Russian Federation
  • 4 IAI Institute of Artificial Intelligence, School of Computer Science, De Montfort University, Leicester, United Kingdom
  • 5 Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah, Saudi Arabia
Keywords
Consensus measures; Group Decision Making; Sentiment analysis; Social networks
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