An individual’s personality has many correlates. Personalities covary with individuals’ attitudes, preferences, interactions, and ways of interacting with others. Hence, data analysts may want to assign a more central role to personality features when understanding users’ expectations and needs. For example, personality features may be included to design and operate better content recommenders.

Traditionally, personality features have been assessed using surveys. Digital interactions may offer a cheaper data source than surveys. Consider the MBTI Personality Type Twitter Dataset dataset available on Kaggle and assess how/to what extent it is possible to predict a Twitter user’s personality based on his/her history of tweets.