A method for the dynamic collaboration of the public and experts in large-scale group emergency decision-making: Using social media data to evaluate the decision-making quality

Abstract

Aiming at the complex and changeable environment and the low public participation in emergency decision-making, this article proposes a method for the dynamic collaboration of the public and experts in large-scale group emergency decision-making (LSGEDM) based on social media data. First, sentiment analysis is carried out on text data from social media platforms to evaluate the quality of LSGEDM at both the attribute and comprehensive levels. Then, according to the decision-making quality at the attribute level, a method for the dynamic updating of attribute weights is proposed. Next, in the social network environment, the trust relationship between experts is dynamically updated based on the comprehensive quality of decision-making and the distance between the expert and group preferences, and expert weights are calculated by the improved PageRank algorithm. Finally, the effectiveness and superiority of the proposed method are verified via its application to the COVID-19 epidemic in China and a comparative analysis.