Design of Early Warning Mechanism of Network Public Opinion Using Deep Learning

With the increasing use of social networks, the public has been used to releasing and spreading information with the help of online media, which aggravates the regulation pressure of online public opinion. Online public opinion is increasing, which is exactly one of the most prominent characteristics of the social network era. Under such circumstances, it is necessary to think about how to deal with the rapid increase of public opinion data and how to strengthen the management of public security incidents. While strengthening the management of public opinion, we need to take into account the complexity and variability of the social development environment at home and abroad, grasp the sudden nature of online public opinion, and conscientiously monitor online public opinions and warn of risks. In this context, we analyzed the needs of the early warning system of network public opinion by using big data and then articulated its design framework based on deep learning. The system is used to effectively identify the risks of public opinion information during the germination period and prevent the adverse impact.