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Automatic Estimation of Web Bloggers’ Age Using Regression Models

Simaki, Vasiliki LU ; Aravantinou, Christina; Mporas, Iosif and Megalooikonomou, Vasileios (2015) In Lecture Notes in Computer Science 9319 . p.113-120
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Author’s age estimation, Text processing, Regression algorithms
in
Lecture Notes in Computer Science
editor
Ronzhin, Andrey; Potapova, Rodmonga; Fakotakis, Nikos; ; and
volume
9319
pages
113 - 120
publisher
Springer
external identifiers
  • scopus:84945961208
ISSN
0302-9743
ISBN
978-3-319-23132-7
DOI
10.1007/978-3-319-23132-7_14
language
English
LU publication?
no
id
827cbf81-b90e-452f-98cc-536530b68620
date added to LUP
2017-06-02 18:37:01
date last changed
2017-06-14 12:06:08
@inbook{827cbf81-b90e-452f-98cc-536530b68620,
  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.},
  author       = {Simaki, Vasiliki and Aravantinou, Christina and Mporas, Iosif and Megalooikonomou, Vasileios},
  editor       = {Ronzhin, Andrey and Potapova, Rodmonga and Fakotakis, Nikos},
  isbn         = {978-3-319-23132-7},
  issn         = {0302-9743},
  keyword      = {Author’s age estimation,Text processing,Regression algorithms },
  language     = {eng},
  pages        = {113--120},
  publisher    = {Springer},
  series       = {Lecture Notes in Computer Science},
  title        = {Automatic Estimation of Web Bloggers’ Age Using Regression Models},
  url          = {http://dx.doi.org/10.1007/978-3-319-23132-7_14},
  volume       = {9319 },
  year         = {2015},
}