Statistical Analysis of Personality and Identity in Chats Using a Keylogging Platform

Interacting via text chats can be considered as a hybrid type of communication, in which textual information delivery follows turn-taking dynamics, resembling spoken interactions. An interesting research question is whether personality can be observed in chats, similarly as happening in face-to-face exchanges. After an encouraging preliminary work on Skype, in this study we have set up our own chat service in which key-logging functionalities have been activated, so that the timings of each key pressing can be measured. Using this framework, we organized semi-structured chats between 50 subjects, whose personality traits have been analyzed through psychometric tests, and a single operator, for a total of 16 hours of conversation. On this data, we have observed that some personality traits are linked with the way we are chatting (measured by stylometric cues), by means of statistically significant correlations and regression studies. Finally, we have assessed that some of the stylometric cues are very discriminative for the recognition of a user in a identification scenario. These facts taken together could underlie that some personality traits drive us in chatting in a particular fashion, which turns out to be very recognizable.