Construction of risk prevention and control model for catering industry during 2019-nCoV situation based on text mining

At the beginning of 2020, 2019-nCoV caused serious adverse effects on China and the world economy. Due to the sudden drop in passenger traffic during the epidemic, the catering industry has become one of the industries most affected by the epidemic. How to maintain survival on the basis of reasonable prevention and control of epidemic situation has become a major problem facing the catering industry. This research collects the reviews and reports of catering companies during the epidemic, and uses ROST Content Mining software to extract high-frequency feature words and analyze the main risk factors. Then this paper builds a social semantic network between high-frequency words and analyzes the mechanism of risk. Finally, based on the different stages of the epidemic, the prevention and control model of the epidemic risk in the catering industry is constructed to provide feasible suggestions for catering companies to deal with the risk of the epidemic, safe resumption of production, transformation and upgrade.