Abstract: In recent years, more and more emergencies have severely affected our economic construction and social development, which urgently needs larger-scale expert wisdom experience to improve the quality of emergency decision-making for large groups. At the same time, with the rapid development and popularization of the Internet, emergencies will arouse the enthusiastic attention and discussion of the public, whose opinions and emotions will be transmitted through big data. While increasing the risk of events, it will also provide new opportunities for emergency decisions analysis and information channels. Therefore, through theoretical analysis and experimental research, research is conducted on the influencing factors and dynamic evolution of the large group emergency decision quality, in order to find methods to improve the large group emergency decision quality. Based on the real case data of “8.12 Tianjin Port Explosion”, the dynamic evolution process of the large group emergency decision quality is characterized and evaluated, and further empirical tests are made on the influencing factors obtained from the previous theoretical analysis. Different information diffusion models provide a new research entry point for traditional large-group theory research and methods. This article extracts and quantifies public risk perception by capturing big data on public big data during emergencies, and then from the level of public participation guided and evaluated the dynamic evolution process of the large group emergency decision quality, re-examined the impact of decision hesitation on the large group emergency decision quality, and put forward corresponding management countermeasures based on the research conclusions.

Key words: large group decision making; emergency decision quality; risk perception; preferences big data