In social psychology, it is generally accepted that one discloses more of his/her personal information to someone in a strong relationship. We present a computational framework for automatically analyzing such self-disclosure behavior in Twitter conversations. Our framework uses text mining techniques to discover topics, emotions, sentiments, lexical patterns, as well as personally identifiable information (PII) and personally embarrassing information (PEI). Our preliminary results illustrate that in relationships with high relationship strength, Twitter users show significantly more frequent behaviors of self-disclosure.
JinYeong Bak, Suin Kim, Alice H. Oh