Research on Personality detection from the text has been increased tremendously in recent times. Research on personality detection models is an interdisciplinary area as it includes the studies from the behavioural science, psychology, sociology, and computer science. Personality detection from text means to extract the behavior characteristics of authors written the text. Personality detection models can be very useful in various domains like information filtering, e-commerce etc. by a user interface with help of interaction according to user's personality. In this paper, we propose to improve the performance of the personality detection method by including prominent emotion features with prominent text features. Prominent features are
extracted using Information Gain feature selection method. Proposed approach to develop the machine learning model with the help of proposed feature set produces the best results among other feature sets. Evaluation of the proposed personality detection models are performed on benchmark datasets.
Experimental results evidence the better performance of the proposed personality detection model .
Personality detection, Emotion features, Machine learning Algorithms