A System for Personality and Happiness Detection

نویسندگان

  • Yago Sáez
  • Carlos Navarro
  • Asunción Mochón
  • Pedro Isasi Viñuela
چکیده

— 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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عنوان ژورنال:
  • IJIMAI

دوره 2  شماره 

صفحات  -

تاریخ انتشار 2014