Carrying out consensual Group Decision Making processes under social networks using sentiment analysis over comparative expressions
Juan Antonio Morente-Molinera,Gang Kou,K. Samuylov,Raquel Ureña,Enrique Herrera-Viedma,Enrique Herrera-Viedma +5 more
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TLDR
This paper presents a novel model for experts to carry out Group Decision Making processes using free text and alternatives pairwise comparisons and introduces two ways of applying consensus measures over the Group decision Making process.Abstract:
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.read more
Citations
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Journal ArticleDOI
Opinion Mining Using Enriched Joint Sentiment-Topic Model
TL;DR: In this article , the authors proposed two novel topic models that extend and improve Joint Sentiment-Topic model through a new parameter (the author's view), which care about the author's inherent characteristics, which is the most important factor in writing a comment.
Proceedings ArticleDOI
Understanding IMF Decision-Making with Sentiment Analysis
TL;DR: This paper introduces a novel dataset, Executive Board meeting minutes of the IMF, in which the sentences are labelled as positive, neutral, or negative and demonstrates that sentiment classification with state-of-the-art language models yields high performance when trained with domain-specific data.
Proceedings ArticleDOI
A Large-Scale Group Decision-Making Method based on Sentiment Analysis for the Detection of Cooperative Group
TL;DR: In this article , a large-scale group decision-making method that classifies experts according to their cooperativeness is presented. But the method is based on using sentiment analysis to detect the degree of aggressiveness of each expert.
Book ChapterDOI
Group Consensus Decision-Making Methods with DHHFLPRs, LPOs and Self-confident DHLPRs
Xunjie Gou,Zeshui Xu +1 more
TL;DR: This chapter will first focus on developing methods to manage the consensus reaching process and ensure that all experts reach consensus in GDM.
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