POCA4SD: A Public Opinion Cellular Automata for Situation Deduction

People can post their comments on public events on the Internet, such as their ideas, emotions, and attitudes that can affect others. Online public opinions may affect the stability or security of the country because of the speed and convenience of information disseminating on the Internet. This article proposes the public opinion cellular automata for situation deduction to predict the possible trending of public events. In the cellular automata, online users are represented by cells, and their eigenvalues are calculated from the user's historical comment data. The cell and their neighbors form a cellular space, whose topology is a directed graph. We set the state of each cell based on its attributes and initialize the cellular automata. The automata can deduce public opinion and predict the trend of public opinion by following the set evolutionary rules in advance. Experiments with the real data from Sina Weibo online users show that the cells in the cellular automata can accurately simulate users' behavior, and the deduction results are close to the trend of real historical events. The cellular automata-based prediction of the number of participants and emotional trending are more accurate than other methods.

Automated summary

The article introduces a public opinion cellular automata model to analyze and predict the trending of public events based on users' behavior simulated from real data, showing more accurate results compared to other methods.