Political expression through social media has already taken root as a form of political participation. However, it is less clear how a government's performance is linked with people's political expression on social media. The present study hypothesizes that when government performance worsens, people become frustrated and send uncivil messages to the government on social media. To test this hypothesis, the present study classified over 8 million tweets directed at U.S. state governors as uncivil or not, using a neural-network machine-learning model, and examined the impact of worsening state-level COVID-19 cases on the number of uncivil tweets directed at state governors. The results show that increasing state-level COVID-19 cases led to higher numbers of uncivil tweets against state governors. Then, the present study discusses the implications of the findings from two perspectives: non-institutionalized political participation and the importance of elections in democracies.
翻译:通过社交媒体的政治表达方式已经作为一种政治参与形式扎根。然而,政府的表现如何与民众在社交媒体上的政治表达方式联系在一起,这一点还不清楚。本研究报告的假设是,当政府的表现恶化时,人们会灰心丧气,并在社交媒体上向政府发送不文明的信息。为检验这一假设,本研究报告使用神经网络机器学习模式,将针对美国各州州长的800多万条推特归类为不文明或不文明的,并审查了州级COVID-19案件恶化对州州长的不文明推文数量的影响。结果显示,州级COVID-19案件增多导致针对州州长的不文明推文数量增多。 然后,本研究报告从两个角度讨论了调查结果的影响:非制度化的政治参与和民主选举的重要性。