Decision making in social media with consistent data

The use of data obtained from social media in decision-making is growing, because people are increasingly using these means to inform themselves, express opinions or make valuations of brands, services, etc. Increasingly, people and organizations use this information to make strategic decisions for their business. This decision process involves, among other thing, obtaining a ranking of alternatives to support the decision. However, in many decision-making models the use of data is done without considering important aspects such as consistency or contextualization, which causes the results to be questioned in a general way due to lack of rigor in the decision-making. In this work, a decision-making model is proposed to obtain an alternative ranking contextualizing the feelings opinions of the users represented through intervals of feeling consistent, using data obtained from the social media. This model uses an interval majority aggregation operator, which constructs opinion intervals using data extracted from the social media; a consistency index for pairwise-comparison interval matrices; an algorithm to reconstruct consistent interval pairwise-comparison matrices, by means of a deflationary process of intervals' diameter; and an operator to obtain a ranking of alternatives in the interval pairwise-comparison matrices. The model has been applied to a real case showing adequate results according to the market. (C) 2019 Published by Elsevier B.V.