Automatic Estimation of Web Bloggers’ Age Using Regression Models

Vasiliki Simaki; Christina Aravantinou; Iosif Mporas; Vasileios Megalooikonomou

doi:10.1007/978-3-319-23132-7_14

Automatic Estimation of Web Bloggers’ Age Using Regression Models

Vasiliki Simaki, Christina Aravantinou, Iosif Mporas, Vasileios Megalooikonomou

University of Patras

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

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.

Original language	English
Title of host publication	Speech and Computer
Subtitle of host publication	17th International Conference, SPECOM 2015, Athens, Greece, September 20-24, 2015, Proceedings
Editors	Andrey Ronzhin, Rodmonga Potapova, Nikos Fakotakis
Publisher	Springer
Pages	113-120
ISBN (Electronic)	978-3-319-23132-7
DOIs	https://doi.org/10.1007/978-3-319-23132-7_14
Publication status	Published - 2015
Externally published	Yes

Publication series

Name	Lecture Notes in Computer Science
Volume	9319
ISSN (Print)	0302-9743

Subject classification (UKÄ)

General Language Studies and Linguistics

Free keywords

Author’s age estimation
Text processing
Regression algorithms

Access to Document

10.1007/978-3-319-23132-7_14

Cite this

Simaki, V., Aravantinou, C., Mporas, I., & Megalooikonomou, V. (2015). Automatic Estimation of Web Bloggers’ Age Using Regression Models. In A. Ronzhin, R. Potapova, & N. Fakotakis (Eds.), Speech and Computer: 17th International Conference, SPECOM 2015, Athens, Greece, September 20-24, 2015, Proceedings (pp. 113-120). (Lecture Notes in Computer Science; Vol. 9319 ). Springer. https://doi.org/10.1007/978-3-319-23132-7_14

Simaki, Vasiliki ; Aravantinou, Christina ; Mporas, Iosif et al. / Automatic Estimation of Web Bloggers’ Age Using Regression Models. Speech and Computer: 17th International Conference, SPECOM 2015, Athens, Greece, September 20-24, 2015, Proceedings. editor / Andrey Ronzhin ; Rodmonga Potapova ; Nikos Fakotakis. Springer, 2015. pp. 113-120 (Lecture Notes in Computer Science).

@inproceedings{827cbf81b90e452f98cc536530b68620,

title = "Automatic Estimation of Web Bloggers{\textquoteright} Age Using Regression Models",

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{\textquoteright} age with mean absolute error equal to 5.44, while the root mean squared error is approximately 7.14.",

keywords = "Author{\textquoteright}s age estimation, Text processing, Regression algorithms ",

author = "Vasiliki Simaki and Christina Aravantinou and Iosif Mporas and Vasileios Megalooikonomou",

year = "2015",

doi = "10.1007/978-3-319-23132-7_14",

language = "English",

series = "Lecture Notes in Computer Science",

publisher = "Springer",

pages = "113--120",

editor = "Andrey Ronzhin and Rodmonga Potapova and Nikos Fakotakis",

booktitle = "Speech and Computer",

address = "Germany",

}

Simaki, V, Aravantinou, C, Mporas, I & Megalooikonomou, V 2015, Automatic Estimation of Web Bloggers’ Age Using Regression Models. in A Ronzhin, R Potapova & N Fakotakis (eds), Speech and Computer: 17th International Conference, SPECOM 2015, Athens, Greece, September 20-24, 2015, Proceedings. Lecture Notes in Computer Science, vol. 9319 , Springer, pp. 113-120. https://doi.org/10.1007/978-3-319-23132-7_14

Automatic Estimation of Web Bloggers’ Age Using Regression Models. / Simaki, Vasiliki; Aravantinou, Christina; Mporas, Iosif et al.
Speech and Computer: 17th International Conference, SPECOM 2015, Athens, Greece, September 20-24, 2015, Proceedings. ed. / Andrey Ronzhin; Rodmonga Potapova; Nikos Fakotakis. Springer, 2015. p. 113-120 (Lecture Notes in Computer Science; Vol. 9319 ).

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

TY - GEN

T1 - Automatic Estimation of Web Bloggers’ Age Using Regression Models

AU - Simaki, Vasiliki

AU - Aravantinou, Christina

AU - Mporas, Iosif

AU - Megalooikonomou, Vasileios

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

KW - Author’s age estimation

KW - Text processing

KW - Regression algorithms

U2 - 10.1007/978-3-319-23132-7_14

DO - 10.1007/978-3-319-23132-7_14

M3 - Paper in conference proceeding

T3 - Lecture Notes in Computer Science

SP - 113

EP - 120

BT - Speech and Computer

A2 - Ronzhin, Andrey

A2 - Potapova, Rodmonga

A2 - Fakotakis, Nikos

PB - Springer

ER -

Simaki V, Aravantinou C, Mporas I, Megalooikonomou V. Automatic Estimation of Web Bloggers’ Age Using Regression Models. In Ronzhin A, Potapova R, Fakotakis N, editors, Speech and Computer: 17th International Conference, SPECOM 2015, Athens, Greece, September 20-24, 2015, Proceedings. Springer. 2015. p. 113-120. (Lecture Notes in Computer Science). doi: 10.1007/978-3-319-23132-7_14

Automatic Estimation of Web Bloggers’ Age Using Regression Models

Abstract

Publication series

Subject classification (UKÄ)

Free keywords

Access to Document

Fingerprint

Cite this