Dataset Information

Defining facets of social distancing during the COVID-19 pandemic: Twitter analysis.

ABSTRACT:

Objectives

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.

Materials and methods

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.

Results

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.

Discussion

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.

Conclusion

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.

SUBMITTER: Kwon J

PROVIDER: S-EPMC7553881 | biostudies-literature |

REPOSITORIES: biostudies-literature

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