A System for Personality and Happiness Detection
Autor:
Saez, Yago
; Navarro, Carlos
; Mochon, Asuncion
; Isasi, Pedro
Fecha:
03/2014Palabra clave:
Revista / editorial:
International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)Tipo de Ítem:
articleDirección web:
https://www.ijimai.org/journal/node/587Resumen:
This work proposes a platform for estimating personality and happiness. Starting from Eysenck's theory about human's personality, authors seek to provide a platform for collecting text messages from social media (Whatsapp), and classifying them into different personality categories. Although there is not a clear link between personality features and happiness, some correlations between them could be found in the future. In this work, we describe the platform developed, and as a proof of concept, we have used different sources of messages to see if common machine learning algorithms can be used for classifying different personality features and happiness.
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