Using Twitter messages published online from October 2018 to June 2019, and opinion mining (OM) technology, the current study analyzes the geographic sentiments toward police in 82 metropolitan areas within the United States. Building on the frameworks of the neighborhood social contextual models, the construct validity of “sentiment toward the police” is assessed via its relationship with the features of various metropolitan areas. Results of the regression analysis indicate that the violent crime rate, racial heterogeneity, and economic disadvantage significantly affect sentiment toward the police. Our results suggest that opinion mining of social media can be an important instrument to understand public sentiment toward the police.

这项研究使用2018年10月至2019年6月在线发布的Twitter消息以及意见挖掘（OM）技术，分析了美国82个大都市地区对警察的地理情感。在邻里社会情境模型的框架上，通过“对警察的情感”与各个大都市区特征之间的关系来评估其构造效度。回归分析的结果表明，暴力犯罪率，种族异质性和经济劣势显着影响了警方的情绪。我们的研究结果表明，社交媒体的观点挖掘可以成为了解公众对警察情绪的重要工具。