Did the public attribute the Flint Water Crisis to racism as it was happening? Text analysis of Twitter data to examine causal attributions to racism during a public health crisis.

IF 2 Q2 SOCIAL SCIENCES, MATHEMATICAL METHODS
Journal of Computational Social Science Pub Date : 2023-04-01 Epub Date: 2022-12-03 DOI:10.1007/s42001-022-00192-6
Neslihan Bisgin, Halil Bisgin, Daniel Hummel, Jon Zelner, Belinda L Needham
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引用次数: 0

Abstract

The Flint Water Crisis (FWC) was an avoidable public health disaster that has profoundly affected the city's residents, a majority of whom are Black. Although many scholars and journalists have called attention to the role of racism in the water crisis, little is known about the extent to which the public attributed the FWC to racism as it was unfolding. In this study, we used natural language processing to analyze nearly six million Flint-related tweets posted between April 1, 2014, and June 1, 2016. We found that key developments in the FWC corresponded to increases in the number and percentage of tweets that mentioned terms related to race and racism. Similar patterns were found for other topics hypothesized to be related to the water crisis, including water and politics. Using sentiment analysis, we found that tweets with a negative polarity score were more common in the subset of tweets that mentioned terms related to race and racism when compared to the full set of tweets. Next, we found that word pairs that included terms related to race and racism first appeared after the January 2016 state and federal emergency declarations and a corresponding increase in media coverage of the FWC. We conclude that many Twitter users connected the events of the water crisis to race and racism in real-time. Given growing evidence of negative health effects of second-hand exposure to racism, this may have implications for understanding minority health and health disparities in the US.

弗林特水危机发生时,公众是否将其归因于种族主义?通过对推特数据进行文本分析,研究公共卫生危机期间种族主义的因果关系。
弗林特水危机(FWC)是一场本可避免的公共卫生灾难,对该市居民造成了深远影响,其中大部分是黑人。尽管许多学者和记者都呼吁关注种族主义在水危机中的作用,但对于公众在多大程度上将弗林特水危机归因于种族主义却知之甚少。在这项研究中,我们使用自然语言处理技术分析了2014年4月1日至2016年6月1日期间发布的近600万条与弗林特有关的推文。我们发现,弗林特事件的主要进展与提及种族和种族主义相关词汇的推文数量和比例的增加相对应。与水危机相关的其他假设话题,包括水和政治,也发现了类似的模式。通过情感分析,我们发现与全部推文相比,在提及种族和种族主义相关词汇的推文子集中,极性得分为负的推文更为常见。接下来,我们发现包含种族和种族主义相关词汇的词对首次出现是在 2016 年 1 月州和联邦宣布紧急状态以及媒体对《联邦妇女儿童委员会》的报道相应增加之后。我们的结论是,许多推特用户实时地将水危机事件与种族和种族主义联系起来。鉴于越来越多的证据表明,二手接触种族主义会对健康产生负面影响,这可能会对了解美国少数民族的健康状况和健康差异产生影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Computational Social Science
Journal of Computational Social Science SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
6.20
自引率
6.20%
发文量
30
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