Nowadays, social networks store a massive amount of data, which can say a lot about our personality. Given the ease to access the internet everywhere at any time, many people use social networks in daily life, reflecting in a certain way their behaviour from the "real world" to the "virtual world", by storing in social networks what they like, hate, feel, where they travel to, their relationships, opinions, etc. Once obtained the access to this data, some authors have tried to infer the personality of the individual without the use of long questionnaires, only working with data in an implicit way, that is, transparently to user. In this scenario, our work is focused on predicting just one of the human personality traits, the Curiosity. In this paper, we analyse the information that can be extracted from the users' profile on Facebook and the set of features that can be used to describe their degree of curiosity. Finally, we generate a prediction model in the form of a decision tree.
['Alan Menk', 'Laura Sebastia']
Predicting the Human Curiosity from Users' Profiles on Facebook