Carrying out consensual Group Decision Making processes under social networks using sentiment analysis over comparative expressions - Inserm - Institut national de la santé et de la recherche médicale
Article Dans Une Revue Knowledge-Based Systems Année : 2018

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

Résumé

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.
Fichier principal
Vignette du fichier
1-s2.0-S0950705118305938-main.pdf (1.03 Mo) Télécharger le fichier
Origine Publication financée par une institution

Dates et versions

inserm-03026812 , version 1 (26-11-2020)

Identifiants

Citer

J A Morente-Molinera, G Kou, K Samuylov, R Ureña, E Herrera-Viedma. Carrying out consensual Group Decision Making processes under social networks using sentiment analysis over comparative expressions. Knowledge-Based Systems, 2018, 165, pp.335 - 345. ⟨10.1016/j.knosys.2018.12.006⟩. ⟨inserm-03026812⟩

Collections

INSERM
80 Consultations
107 Téléchargements

Altmetric

Partager

More