Examining the Impact of Personality on the Efficiency of Recommendation Systems

Abstract

Recent research shows great promise for predicting personality from social media data. This preliminary small sample review provides an idea on the possibilities that social media data and social media platforms could provide for measuring personal- ity. The review suggests that scientifically designed online environments or applications could provide interesting possibilities for collecting and analysing personal, social and mass-behavioural data. Furthermore, social media users interest to self-present align well with the interests of personality researchers, which suggests valuable motivational resources. A theoretical framework of these possibilities is provided as well as experi- ences regarding the small sample review method used in this study. This paper discusses personality-aware recommendation systems. With the evolution of artificial intelligence (AI) nowadays, personality-aware recommendation systems are considered a new re- search field related to AI and the psychology of personality. Also, it solves the most common problems, which are cold start and sparsity of data, of the traditional recom- mendation systems. The results of our comprehensive search, address the core research questions related to efficiency, personality theory, and techniques.