首页|Engaging with underserved communities during times of crises: A computational analysis of social media interactions with government information about COVID-19 economic relief programs

Engaging with underserved communities during times of crises: A computational analysis of social media interactions with government information about COVID-19 economic relief programs

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  • NETL
  • NSTL
  • Elsevier
© 2024 The Author(s)Racial and social inequalities in the digital landscape remain pressing concerns in society. Previous research on government efforts to address digital inequality has largely focused on improving access to digital infrastructure and literacy. However, there is a severe shortage of research that examines how underserved communities engage with government information on relief measures and policies during crises. This study fills these gaps by drawing insights from three bodies of literature – digital inequality, the situational theory of problem solving, and fear. We investigate how underserved communities, such as low-income individuals, communities of color, and rural populations, interacted with government information about COVID-19 economic relief programs designed to mitigate the adverse effects of crises, and how fear influenced public engagement patterns. We analyzed Facebook posts (N = 28,887) containing links (URLs) to government websites on COVID-19 economic relief programs from 2020 to 2022. Our findings show that posts shared within underserved communities generated higher levels of engagement (shares, comments) compared to those shared in nonunderserved communities. This indicates that underserved communities showed great interest in and participation with government information about relief programs during the pandemic. Notably, engagement significantly decreased when fear was expressed in discussions, and such a pattern was more pronounced in underserved communities than in nonunderserved ones. These results offer valuable insights into the communication dynamics of underserved communities during crises, contributing to a deeper understanding of digital inequality within the policy context.

Computational methodsCrisisDigital inequalityFearGovernment informationSituational theory of problem solvingSocial media

Lee J.、Kim S.

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Stan Richards School of Advertising and Public Relations Moody College of Communication The University of Texas at Austin

Department of Communication University of California Davis

2024

10.1016/j.tele.2024.102209

Telematics and informatics

Telematics and informatics

EI
ISSN：0736-5853
年,卷(期)：2024.95(Nov.)
  • 92