A data-driven large-scale group decision-making framework for managing ratings and text reviews

Even though the integration of sentiment analysis and decision-making techniques has become popular in recent years, most of the related studies only consider the obtained sentiment score, thus neglecting the numerical ratings that are usually attached to text reviews. This paper introduces STandR (Sentiment from Text and Ratings)-BUI (Basic Uncertain Information), a novel preference-modeling structure for data-driven decision- making using social media microblogging information. STandR-BUI combines both the numerical rating and the sentiment score of a product into a BUI value, which provides amore precise representation of users' opinions. In addition, we propose a consensus framework to make decisions based on the STandR-BUI values which can manage thousands of user reviews. Finally, an illustrative example is provided to demonstrate its effectiveness.