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 signi_cant 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 identi_cation 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