Are you Curious? Predicting the Human Curiosity from Facebook
| Autor: | Alan Menk, Laura Sebastia |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Virtual world
Computer science media_common.quotation_subject 05 social sciences 050109 social psychology 0102 computer and information sciences Recommender system 01 natural sciences Data science 010201 computation theory & mathematics Artificial Intelligence Control and Systems Engineering Personality Curiosity 0501 psychology and cognitive sciences Big Five personality traits Set (psychology) Software Predictive modelling Information Systems media_common |
| Zdroj: | International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. 25:79-95 |
| ISSN: | 1793-6411 0218-4885 |
| DOI: | 10.1142/s0218488517400128 |
| Popis: | Nowadays, social networks are daily used to share what people like, feel, where they travel to, etc. This huge amount of data can say a lot about their personality because it may reect their behaviour from the “real world” to the “virtual world”. 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 the user. In this scenario, our work is focused on predicting 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 use these data to generate several prediction models. The best generated model is able to predict the degree of curiosity with an accuracy of 87%. |
| Databáze: | OpenAIRE |
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