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.
翻译:我们研究了在一大批Tweets数据集中发现的自我披露事件,该数据集代表了用户主导的关于Corona病毒大流行病的英语对话。我们采用不受监督的方法检测自愿披露个人信息的情况。我们提供了早期证据,说明围绕Corona病毒大流行病的情况因素可能影响个人的隐私微积分。文本分析揭示了在Twitter上支持和支持自我披露对话的热点转变。我们对哈维飓风的Tweets进行了可比分析,以提供观察到的影响的背景,并提出进一步研究的机会。