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Prediction of social mood on Chinese societal risk perception

机译:对中国社会风险感知的社会情绪预测

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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.
机译:现代中国在社会转型和全球化过程中接触了许多社会风险。以前的心理研究证明,情绪对个人风险感知是重要的。这种效果是否适用于大型社会?通过使用五个基于基本情绪词典和基于术语的匹配技术来分析日常新浪微博的文本内容,获得了幸福,厌恶,恐惧,愤怒和悲伤的五个社交情绪时间序列。然后通过百度搜索引擎上的公众搜索行为得到了社会稳定风险,公共道德风险,公共道德风险,政府管理风险,国家安全风险和经济金融风险,包括社会稳定性风险,日常生活风险,资源风险,国家安全风险和经济金融风险社会风险感知心理上。然后通过格兰杰因果区分析和衬里回归模型研究了社会情绪与社会风险感知之间的相关性。结果发现,社会情绪是对社会风险感知的预测,但不同种类的社会情绪的影响是区别的。四种负面情绪预测社会风险的感知,这意味着负面的社会情绪增加对社会风险因素的公共风险感知。该研究表现出捕捉社交媒体的公共心理特征是可行的。

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