Author ORCID Identifier
Document Type
Article
Publication Date
2-23-2022
Publication Title
Proceedings of International Conference on Information (iConference)
Abstract
The COVID-19 pandemic ushered in an era of unprecedented hardship worldwide, bringing uncertainty to new levels as people’s routines were disrupted and what was once considered normal was called into question. Citizens initiated online local communities to support information-seeking amidst the pandemic. In this paper, we explore what types of information were sought and how people engaged in uncertainty reduction with others in their area during the initial phase of COVID-19. We conducted content analysis on a pandemic-relief online local community. We found that people leveraged local networks to get updates about timely situations in local areas, clear confusion around local COVID-19 regulations, and seek confirmation on emerging social norms. However, there existed inaccurate information exchange about regulations and conflicting opinions on social norms. We provide design suggestions to increase the potentials of uncertainty management through online local communities.
Recommended Citation
Jo, J., Knearem, T., Tsai, C. H., & Carroll, J. M. (2022). Using Local Community to Ease Long Haul Uncertainty during the COVID-19 Pandemic. Proceedings of International Conference on Information (iConference). https://doi.org/10.1007/978-3-030-96960-8_15
Comments
Part of the Lecture Notes in Computer Science book series (LNISA,volume 13193)
This is the accepted manuscript version of a chapter that has been accepted for publication and is subject to Springer’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at:
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