Vachuska Karl
Department of Sociology, University of Wisconsin-Madison, 1180 Observatory Dr., Madison, WI 53703, USA.
Behav Sci (Basel). 2022 Oct 25;12(11):410. doi: 10.3390/bs12110410.
Recent research has attempted to document large-scale emotional contagion on online social networks. Despite emotional contagion being primarily driven by in-person mechanisms, less research has attempted to measure large-scale emotional contagion in in-person contexts. In this paper, I operationalize the temporal emotions associated with a particular city at particular points in time using sentiment analysis on Twitter data. Subsequently, I study how emotions converge between seven proximal cities in the state of Virginia, using two-way fixed effect models. I find that positive emotions tend to be synchronous between cities, but that effect is conditional on the level of contact between city residents at that period of time, as indicated by cell phone mobility data. I do not find any synchrony based on other types of emotions or general sentiment. I discourage drawing causal conclusions based on the presumed existence of several unmeasured sources of bias.
近期的研究试图记录在线社交网络上的大规模情绪感染现象。尽管情绪感染主要由面对面的机制驱动,但较少有研究尝试在面对面的情境中测量大规模情绪感染。在本文中,我利用推特数据进行情感分析,对特定时间特定城市的时间性情绪进行操作化处理。随后,我使用双向固定效应模型,研究弗吉尼亚州七个相邻城市之间的情绪如何趋同。我发现,城市之间积极情绪往往是同步的,但这种效应取决于该时间段内城市居民之间的接触程度,这由手机移动数据表明。我没有发现基于其他类型情绪或总体情绪的同步性。我不鼓励基于几个未测量的偏差来源的假定存在得出因果结论。