Language-independent gender identification through keystroke analysis |
The purpose of this paper is to investigate the feasibility of identifying the gender of an author by measuring the keystroke duration when typing a message. Three classifiers were constructed and tested. The authors empirically evaluated the effectiveness of the classifiers by using empirical data. The authors used primary data as well as a publicly available dataset containing keystrokes from a different language to validate the language independence assumption. The results of this paper indicate that it is possible to identify the gender of an author by analyzing keystroke durations with a probability of success in the region of 70 per cent.
Tsimperidis I, Katos V, Clarke NL