A dynamic group decision making process for high number of alternatives using hesitant Fuzzy Ontologies and sentiment analysis

The high spread of Internet and social networks have completely changed the way that Group Decision Making methods are designed, developed and implemented. Experts now operate in environments where a large amount of information is available and new ideas and participants can appear at any time; this results in a dynamically changing decision environment. In this paper, a novel group decision making method for dynamic contexts with a high number of decision alternatives is presented. As the main component of the proposal, a perceptual computing scheme is used in order to extract information from the experts. In the process, sentiment analysis is used when analyzing the debate texts in order to obtain information for selecting the best alternatives on each round. Moreover, interval type-2 hesitant Fuzzy Ontologies are used in order to store the information related to alternatives. By combining interval type-2 and hesitant fuzzy sets, imprecise information can be represented in a comfortable and intuitive way within the ontology. (C) 2020 Elsevier B.V. All rights reserved.