A multi-period intuitionistic fuzzy consensus reaching model for group decision making problem in social network

Abstract

A new intuitionistic fuzzy consensus reaching model is developed with multi-period public opinions and expert evaluation values in social network environment. First, the public opinions are obtained by using the crawler software and sentiment analysis technology is used to transform public opinions into intuitionistic fuzzy decision matrix in each period. Attribute weights are calculated by using the time attenuation factor and changes in public opinion. Second, the social trust relationship is modeled and incomplete social trust relationships are completed by using Archimedean t-norm. The expert weights are calculated by using the dynamic trust degree and similarity degree. Third, a consensus framework is proposed for multiple-period decision making problem, which coordinates conflicts between experts through dual feedback paths. The collective opinion scores are calculated by using weights of periods and attribute weights obtained from the word frequency of public opinions. The tourism attraction recommendation method is used to illustrate the proposed method.