A Large-Scale Group Decision-Making Method based on Sentiment Analysis for the Detection of Cooperative Group

Group Decision-Making is a process by which a set of experts sort a set of alternatives. When there are a large number of experts, the process is called a Large-Scale Group Decision-Making process. In this kind of environment, there is a great variety of attitudes when discussing the set of alternatives. For instance, there may be experts who may be more aggressive or more peaceful. Aggressiveness is directly related to the degree of cooperativeness of the experts because if an expert is aggressive it implies that he/she will be less cooperative. Consequently, this paper develops a Large-Scale Group Decision-Making method that classifies experts according to their cooperativeness. This classification is based on using sentiment analysis to detect the degree of aggressiveness of each expert. Thus, it is possible to determine whether a specific behavior implies similar valuations and also to detect which experts are more cooperative and are able to reach a consensual ranking of alternatives and which ones would be less willing to cooperate to reach a consensual decision.