Prediction of social mood on Chinese societal risk perception

Abstract

Modern China is exposed to many societal risks in the process of social transformation and globalization. Previous psychological researches have proven that emotion is of importance in individual risk perception. Could the effect apply to large societies? The five social mood time series including happiness, disgust, fear, anger and sadness were obtained by analyzing the text content of daily Sina Weibo using the five basic mood lexicon and term-based matching technique. Then the seven societal risk perceptions including social stability risk, daily life risk, resource & environment risk, public morals risk, government management risk, national security risk and economic & finance risk were gotten by corresponding the public searching behavior on Baidu search engine to the societal risk perception psychologically. Then the correlation between the social moods and societal risk perceptions was investigated by Granger causality analysis and liner regression model. The result found that social moods are predictive of societal risk perceptions but the effect of different kinds of social mood is distinguishing. The four negative moods predict societal risk perceptions positively which means negative social moods increase the public risk perception to societal risk factors. The research manifested that capturing public psychological characteristics on social media was feasible.