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Automatic Estimation of Web Bloggers’ Age Using Regression Models

  • Vasiliki Simaki
  • Christina Aravantinou
  • Iosif Mporas
  • Vasileios Megalooikonomou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9319)

Abstract

In this article, we address the problem of automatic age estimation of web users based on their posts. Most studies on age identification treat the issue as a classification problem. Instead of following an age category classification approach, we investigate the appropriateness of several regression algorithms on the task of age estimation. We evaluate a number of well-known and widely used machine learning algorithms for numerical estimation, in order to examine their appropriateness on this task. We used a set of 42 text features. The experimental results showed that the Bagging algorithm with RepTree base learner offered the best performance, achieving estimation of web users’ age with mean absolute error equal to 5.44, while the root mean squared error is approximately 7.14.

Keywords

Author’s age estimation Text processing Regression algorithms 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Vasiliki Simaki
    • 1
  • Christina Aravantinou
    • 1
  • Iosif Mporas
    • 1
  • Vasileios Megalooikonomou
    • 1
  1. 1.Multidimensional Data Analysis and Knowledge Management Laboratory Department of Computer Engineering and InformaticsUniversity of PatrasRionGreece

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