Defining facets of social distancing during the COVID-19 pandemic: Twitter analysis.
Defining facets of social distancing during the COVID-19 pandemic: Twitter analysis.
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DOI：
10.1016/j.jbi.2020.103601
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发表时间：
2020-11
影响因子：
4.5
通讯作者：
Fodeh SJ
中科院分区：
文献类型：
--
作者：
Kwon J;Grady C;Feliciano JT;Fodeh SJ
使用Twitter，我们的目标是(1)在时空背景下定义和量化美国COVID-19大流行期间社交距离方面的流行和演变；(2)研究社交距离方面的放大推文。我们使用Twitter API分析了2020年1月23日至3月24日期间包含“冠状病毒”的英语和美国推文。包含关键词的推文被分为六个社交距离方面：实施、目的、社会破坏、适应、积极情绪和消极情绪。共有259,529条独立推文被纳入分析。从1月下旬到3月，社交距离推文变得更加普遍，但在地理上并不均匀。社交距离的早期方面出现在洛杉矶、旧金山和西雅图，这是首批受COVID-19疫情影响的城市。与“实施”和“负面情绪”方面相关的推文在很大程度上与“社会破坏”和“适应”主题结合在一起，尽管程度较低。社交颠覆性推文被转发最多，实施性推文最受欢迎。社会距离可以通过应对和代表大流行中的某些事件的方面来定义，包括旅行限制和病例数上升。例如，迈阿密的社交距离推文数量很低，但随着新冠肺炎病例的增加，3月份推文数量有所增加。推特上社交距离的演变反映了实际事件，可能预示着潜在的疾病热点。我们的方面也可以用来理解关于社会距离的公众话语，这可能为未来的公共卫生措施提供信息。
Using Twitter, we aim to (1) define and quantify the prevalence and evolution of facets of social distancing during the COVID-19 pandemic in the US in a spatiotemporal context and (2) examine amplified tweets among social distancing facets. We analyzed English and US-based tweets containing “coronavirus” between January 23-March 24, 2020 using the Twitter API. Tweets containing keywords were grouped into six social distancing facets: implementation, purpose, social disruption, adaptation, positive emotions, and negative emotions. A total of 259,529 unique tweets were included in the analyses. Social distancing tweets became more prevalent from late January to March but were not geographically uniform. Early facets of social distancing appeared in Los Angeles, San Francisco, and Seattle: the first cities impacted by the COVID-19 outbreak. Tweets related to the “implementation” and “negative emotions” facets largely dominated in combination with topics of “social disruption” and “adaptation”, albeit to lesser degree. Social disruptiveness tweets were most retweeted, and implementation tweets were most favorited. Social distancing can be defined by facets that respond to and represent certain events in a pandemic, including travel restrictions and rising case counts. For example, Miami had a low volume of social distancing tweets but grew in March corresponding with the rise of COVID-19 cases. The evolution of social distancing facets on Twitter reflects actual events and may signal potential disease hotspots. Our facets can also be used to understand public discourse on social distancing which may inform future public health measures.
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影响因子：
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通讯作者：
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