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Author Profiling: Predicting Gender from Document

  • Sunakshi MamgainEmail author
  • Rakesh C. Balabantaray
  • Ajit K. Das
  • Srikant Kumar
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 37)

Abstract

As the Internet is aging, a massive amount of data is being created on the web, out of which mostly is text. Therefore, authorship of the contents and prediction of characteristics of the author is becoming a new domain of data analytics making Author Profiling a research area with huge scope of possibilities and outcomes. The ability to describe the features or traits of an author has a key application in many security and forensic areas. The PAN labs provide a platform for scholars by organizing author profiling tasks, for example, language, gender prediction, etc. In this paper, we are attempting to predict gender of a particular author, for which we have considered English dataset of PAN 2017.

Keywords

NLP Classification Cross-validation Logistic regression SVM and Multinomial Naïve Bayes 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Sunakshi Mamgain
    • 1
    Email author
  • Rakesh C. Balabantaray
    • 2
  • Ajit K. Das
    • 2
  • Srikant Kumar
    • 1
  1. 1.IIITBhubaneswarIndia
  2. 2.Department of CS-ITIIITBhubaneswarIndia

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