Social media is a place where users present themselves and preferences to the world by daily posting. While social networks are entrenched as a central element of everyday life, posts to social networks tend to be more positive as individuals want to portray a positive image to their friends that vary from individual to another.
The research conducted in this paper has focused on the personality of Twitter's user based on research, that aims at benchmarking emotion recognition algorithms through face reaction. Previous studies concluded that the user's account profile picture refers to self-representation. Detection, extraction, and evaluation of these facial expressions in an image are being measured by algorithms which allow for automatic recognition of the human emotion. The objective of the present paper is to infer the personality traits from the profile pictures and analyse those pictures to indicate the personality traits that the users may have intended to portrait themselves on the social media. The input data in the study is 500 twitter profile pictures by using Face++ API. The paper described the type of data collected and the analysis methods that are utilized to predict the user's personality and measured the personality through the user's account profile picture and this is what the users chose to portray themselves into. The study has expounded that Twitter profile pictures carry relevant information for classifying the personality traits of the individuals who post them based on the standard Big- Five model. Therefore, the measured personalities are not necessarily the true personality.