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Automatic Estimation of Web Bloggers’ Age Using Regression Models

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter (peer-reviewed) › peer-review

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Automatic Estimation of Web Bloggers’ Age Using Regression Models. / Simaki, Vasiliki; Aravantinou, Christina; Mporas, Iosif et al.
Speech and Computer: SPECOM 2015. ed. / A. Ronzhin; R. Potapova; N. Fakotakis. Cham: Springer, 2015. p. 113-120 (Lecture Notes in Computer Science; Vol. 9319).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter (peer-reviewed) › peer-review

Harvard

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: SPECOM 2015. Lecture Notes in Computer Science, vol. 9319, Springer, Cham, pp. 113-120. https://doi.org/10.1007/978-3-319-23132-7_14

APA

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: SPECOM 2015 (pp. 113-120). (Lecture Notes in Computer Science; Vol. 9319). Springer. https://doi.org/10.1007/978-3-319-23132-7_14

Vancouver

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: SPECOM 2015. Cham: Springer. 2015. p. 113-120. (Lecture Notes in Computer Science). Epub 2015 Sept 4. doi: 10.1007/978-3-319-23132-7_14

Author

Simaki, Vasiliki ; Aravantinou, Christina ; Mporas, Iosif et al. / Automatic Estimation of Web Bloggers’ Age Using Regression Models. Speech and Computer: SPECOM 2015. editor / A. Ronzhin ; R. Potapova ; N. Fakotakis. Cham : Springer, 2015. pp. 113-120 (Lecture Notes in Computer Science).

Bibtex

@inbook{b3d19b4787634e9993a3043dbe851956,
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",
isbn = "9783319231310",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "113--120",
editor = "A. Ronzhin and R. Potapova and N. Fakotakis",
booktitle = "Speech and Computer",

}

RIS

TY - CHAP

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 - Chapter (peer-reviewed)

SN - 9783319231310

T3 - Lecture Notes in Computer Science

SP - 113

EP - 120

BT - Speech and Computer

A2 - Ronzhin, A.

A2 - Potapova, R.

A2 - Fakotakis, N.

PB - Springer

CY - Cham

ER -