Health Mentions on Twitter: A Case Study to Identify Privacy Leaks

User generated content in social networks has become a rich source of information into health conditions. This information is not only discussed privately on social networks by the users, but is increasingly publicly given out. This article analyzes the health condition mentions in tweets. Since health mentions can be used in different contexts, whether as a joke, in a news article link, or a genuine disclosure of a health condition suffered by the user, it is important to understand the contexts of the tweets. We address this by categorizing the tweets based on context. We found each health mention to have differing disclosure rates, affecting privacy leaks differently and peaking in disclosure rate at different times of the day. We also found that personal privacy leaks and secondary privacy leaks are affected differently by each health mention.