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On Twitter, so-called verified accounts represent celebrities and organizations of public interest, selected by Twitter based on criteria for both activity and notability. Our work seeks to understand the involvement and influence of these accounts in patterns of self-disclosure, namely, voluntary sharing of personal information. In a study of 3 million COVID-19 related tweets, we present a comparison of self-disclosure in verified vs ordinary users. We discuss evidence of peer effects on self-disclosing behaviors and analyze topics of conversation associated with these practices.more » « less
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Blose, Taylor; Umar, Prasanna; Squicciarini, Anna; Rajtmajer, Sarah (, First Monday)We study observed incidence of self-disclosure in a large set 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.more » « less
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