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Personality Detection by Analysis of Twitter Profiles

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Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016) (SoCPaR 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 614))

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Abstract

With the boom of social networks, the amount of personal information that is put online has seen an exponential increase. Social media profiles can reveal important details about individuals and their preferences. Psychological studies have revealed that humans can be divided into types, based on their personality traits. This paper explores the usefulness of Twitter profiles in predicting the personality types of the users. The results of analysis of 450 Twitter profiles and over 1 million tweets are reported. It is shown that high degrees of correlation exist between the information from tweets and personality traits. Prediction accuracies up to 60% are also reported.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal, 576104, Karnataka, India

    Mehul Smriti Raje & Aakarsh Singh

Authors
  1. Mehul Smriti Raje
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  2. Aakarsh Singh
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Corresponding author

Correspondence to Mehul Smriti Raje .

Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research, Machine Intelligence Research Labs (MIR Labs), Auburn, Washington, USA

    Ajith Abraham

  2. VIT University, Vellore, Tamil Nadu, India

    Aswani Kumar Cherukuri

  3. School of Engineering, Polytechnic of Porto (ISEP/IPP), Porto, Portugal

    Ana Maria Madureira

  4. Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia

    Azah Kamilah Muda

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Raje, M.S., Singh, A. (2018). Personality Detection by Analysis of Twitter Profiles. In: Abraham, A., Cherukuri, A., Madureira, A., Muda, A. (eds) Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016). SoCPaR 2016. Advances in Intelligent Systems and Computing, vol 614. Springer, Cham. https://doi.org/10.1007/978-3-319-60618-7_65

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  • DOI: https://doi.org/10.1007/978-3-319-60618-7_65

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60617-0

  • Online ISBN: 978-3-319-60618-7

  • eBook Packages: EngineeringEngineering (R0)

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