# Privacy in Crisis: A study of self-disclosure during the Coronavirus pandemic

arXiv: https://arxiv.org/abs/2004.09717 · HTML: https://mlsanity.com/paper/2004.09717/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Apr 2020.

## Built on by (most cited first, 2 of 2)

- [Reducing Privacy Risks in Online Self-Disclosures with Language Models](https://mlsanity.com/paper/2311.09538/) (2023)
- [Measuring, Modeling, and Helping People Account for Privacy Risks in Online Self-Disclosures with AI](https://mlsanity.com/paper/2412.15047/) (2024)

## Abstract (arXiv)

We study observed incidence of self-disclosure in a large dataset of Tweets representing user-led English-language conversation about the Coronavirus pandemic. Using an unsupervised approach to detect voluntary disclosure of personal information, we provide early evidence that situational factors surrounding the Coronavirus pandemic may impact individuals' privacy calculus. Text analyses reveal topical shift toward supportiveness and support-seeking in self-disclosing conversation on Twitter. We run a comparable analysis of Tweets from Hurricane Harvey to provide context for observed effects and suggest opportunities for further study.