Abstract:
The increased use of social media platform usage such as Facebook has given an oppor tunity to express one’s thoughts and ideas to everyone. Social media posts can be used
as a medium for determining different psychological traits, such as dark triad character istics. In our thesis, we used peoples’ social media posts, and using those posts we tried
to detect presence of dark triad traits based on the hand crafted features extracted from
their posts. We also have shown, the usage of code mixing as a effective feature. We
have used traditional machine learning models, ensemble models as well as transformer
based language models to find the best possible outcome. For finding linguistic fea tures analysis we have used Polarity of text, subjectivity, lexical density, word tokens,
word count, avg word length, word freq dist, stopword count, part of speech, Topic seg mentation and many more. We then compared the performance of all the models.For
all the traits, ensemble of 4 traditional machine learning models outperformed all other
models.The highest accuracy achieved in narcissist detection was 96.36% , for Machi avelli it was 98.27%, and for psychopathy it was 99.62%.
