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    • UNIR REVISTAS
    • Revista IJIMAI
    • 2014
    • vol. 2, nº 5, march 2014
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    • UNIR REVISTAS
    • Revista IJIMAI
    • 2014
    • vol. 2, nº 5, march 2014
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    A System for Personality and Happiness Detection

    Autor: 
    Saez, Yago
    ;
    Navarro, Carlos
    ;
    Mochon, Asuncion
    ;
    Isasi, Pedro
    Fecha: 
    03/2014
    Palabra clave: 
    personality detection; Android OS; happiness; written text; machine learning; classifying algorithms; IJIMAI
    Tipo de Ítem: 
    article
    URI: 
    https://reunir.unir.net/handle/123456789/9764
    DOI: 
    http://dx.doi.org/10.9781/ijimai.2014.251
    Dirección web: 
    https://www.ijimai.org/journal/node/587
    Open Access
    Resumen:
    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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