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The Application of Keirsey’s Temperament Model to Twitter Data in Portuguese

  • Cristina Fátima ClaroEmail author
  • Ana Carolina E. S. LimaEmail author
  • Leandro N. de CastroEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11352)

Abstract

Temperament is a set of innate tendencies of the mind related with the processes of perception, analysis and decision making. The purpose of this paper is to predict Twitter users temperament based on Portuguese tweets and following Keirsey’s model, which classifies the temperament into artisan, guardian, idealist and rational. The proposed methodology uses a Portuguese version of LIWC, which is a dictionary of words, to analyze the context of words, and supervised learning using the KNN, SVM and Random Forests for training the classifiers. The resultant average accuracy obtained was 88.37% for the artisan temperament, 86.92% for the guardian, 55.61% for the idealist, and 69.09% for the rational. For classification using TF-IDF the SVM algorithm obtained the best performance to the artisan temperament with average accuracy of 88.28%.

Keywords

Machine learning Social media Keirsey temperament model 

Notes

Acknowledgements

The authors thank CAPES, CNPq, Fapesp, and MackPesquisa for the financial support. The authors also acknowledge the support of Intel for the Natural Computing and Machine Learning Laboratory as an Intel Center of Excellence in Artificial Intelligence.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Mackenzie Presbyterian UniversitySão PauloBrazil

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