Research on Big Data Real-Time Public Opinion Monitoring under the Double Cloud Architecture

摘要

In order to filter useful information from internet public opinion quickly, this paper proposes a mode of using double cloud architecture and optimizes clustering algorithm to monitor the massive network information in real time. In this way, the delay of the bandwidth limitation is reduced, and the locking speed of the effective information is accelerated, which ensures the real-time and effectiveness of the big data of the monitoring of public opinion. Thereby it can provide timely information, assist decision making, and provide the feasibility of the scheme for the relevant departments to handle unexpected group events. At last, this paper carries out an experimental comparison between big data of real-time public opinion monitoring model under the double layer cloud architecture and the traditional centralized deployment algorithm, the results show that the method in this paper has a faster operating speed, strong reliability and faster convergence rate, especially with the increase of the amount of data, the advantages of the speed of convergence is more obvious.