First impressions - predicting user personality from Twitter profile images

This paper proposes a computer vision based pipeline for inferring the perceived personality of users from their Twitter profile images. We humans make impressions on a daily basis during communication. The perception of personality of a person gives information about the person’s behaviour and is an important attribute in developing rapport. The personality assessment in this paper is referred to as first impressions, which is similar to how humans create a mental image of another person by just looking at their profile pictures. In the proposed automated pipeline, hand crafted (engineered) and learnt feature descriptors are computed on user profile images. The effect of image background is assessed on the perception of the personality from a profile picture. A multivariate regression approach is used to predict the big five personality traits - agreeableness, conscientiousness, extraversion, openness and neuroticism. We study the correlation between the big five personality traits generated from Tweet analysis with the proposed profile image based framework. The experiments show high correlation for scene based first impressions perception. It is interesting to note that the results generated by analysing a profile image uploaded by a user in a particular point in time are in sync with the first impression traits generated by investigating Tweets posted over a longer duration of time.