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Voluntary sharing of personal information is at the heart of user engagement on social media and central to platforms' business models. From the users' perspective, so-called self-disclosure is closely connected with both privacy risks and social rewards. Prior work has studied contextual influences on self-disclosure, from platform affordances and interface design to user demographics and perceived social capital. Our work takes a mixed-methods approach to understand the contextual information which might be integrated in the development of privacy-enhancing technologies. Through observational study of several Reddit communities, we explore the ways in which topic of discussion, group norms, peer effects, and audience size are correlated with personal information sharing. We then build and test a prototype privacy-enhancing tool that exposes these contextual factors. Our work culminates in a browser extension that automatically detects instances of self-disclosure in Reddit posts at the time of posting and provides additional context to users before they post to support enhanced privacy decision-making. We share this prototype with social media users, solicit their feedback, and outline a path forward for privacy-enhancing technologies in this space. 

We investigate relationships between online self-disclosure and received social support and user engagement during the COVID-19 crisis. We crawl a total of 2,399 posts and 29,851 associated comments from the r/COVID19_support subreddit and manually extract fine-grained personal information categories and types of social support sought from each post. We develop a BERT-based ensemble classifier to automatically identify types of support offered in users’ comments. We then analyze the effect of personal information sharing and posts’ topical, lexical, and sentiment markers on the acquisition of support and five interaction measures (submission scores, the number of comments, the number of unique commenters, the length and sentiments of comments). Our findings show that: (1) users were more likely to share their age, education, and location information when seeking both informational and emotional support as opposed to pursuing either one; (2) while personal information sharing was positively correlated with receiving informational support when requested, it did not correlate with emotional support; (3) as the degree of self-disclosure increased, information support seekers obtained higher submission scores and longer comments, whereas emotional support seekers’ self-disclosure resulted in lower submission scores, fewer comments, and fewer unique commenters; and (4) post characteristics affecting audience response differed significantly based on types of support sought by post authors. These results provide empirical evidence for the varying effects of self-disclosure on acquiring desired support and user involvement online during the COVID-19 pandemic. Furthermore, this work can assist support seekers hoping to enhance and prioritize specific types of social support and user engagement.