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Inside out and outside in: How the COVID-19 pandemic affects self-disclosure on social media
Open accessAbstract
As social distancing and lockdown orders grew more pervasive, individuals increasingly turned to social media for support, entertainment, and connection to others. We posit that global health emergencies - specifically, the COVID-19 pandemic - change how and what individuals self-disclose on social media. We argue that IS research needs to consider how privacy (self-focused) and social (other-focused) calculus have moved some issues outside in (caused by a shift in what is considered socially appropriate) and others inside out (caused by a shift in what information should be shared for the public good). We identify a series of directions for future research that hold potential for furthering our understanding of online self-disclosure and its factors during health emergencies.
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“The COVID-19 pandemic has accelerated the digitization of our lives and normalized our communication and interaction within the online environment (e.g., social media, virtual community, and else) (Nabity-Grover et al., 2020).”
From Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy (2022) · cites this paper as Nabity-Grover et al., 2020
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Metadata
- Authors
- Nabity-Grover, T., Cheung, C. M. K., & Thatcher, J. B.
- Affiliations
- Boise State University (US)
- Hong Kong Baptist University (HK)
- Temple University (US)
- Corresponding author
- Thatcher, Jason Bennett
- Venue
- International Journal of Information Management
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 55
- Pages
- 102188
- ISSN
- 0268-4012 (ISSN-L)
- PMC
- PMC7320916
- OpenAlex
- W3037942277
- Semantic Scholar
- 112631e5ace683d45daea194f5c518abd5d9a91f
- Cited by
- 309
- References
- 48
- Citations by year
- 2026: 4 · 2025: 20 · 2024: 39 · 2023: 48 · 2022: 95 · 2021: 87 · 2020: 16
- FWCI
- 76.50
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- International Journal of Information Management (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Scholar Works (Boise State University) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Social Sciences › Communication › Communication and COVID-19 Impact
- Social Sciences › Communication › Public Relations and Crisis Communication
- Keywords
- COVID-19 pandemic, self-disclosure, social media, privacy calculus, health emergencies, social distancing, lockdown, online self-disclosure, public goods, information sharing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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