An Enterprise Public Opinion Emergency Response System

Abstract

The public opinion emergency response on the Internet has become one of the effective means for modern enterprises to prevent and respond to network risks. This paper describes an enterprise public opinion emergency response system based on natural language processing (NLP) technology and search engine optimization technology. The proposed system consists of network information collection, data analysis, public opinion monitoring, strategy recommendation, and emergency response. The system's characteristics and technical architecture are introduced and some related core algorithms such as public opinion collection and filtering algorithms and public opinion response strategy recommendation algorithms are stated. Through an integrated network marketing solution, the system supports the response to public opinion response based on the results of big data analysis, and solves the empirical and timeliness problems that traditional online marketing has in the case of public opinion response.