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  • ajeassp.2016.868.876

    Rights statement: © 2016 Vasiliki Simaki, Iosif Mporas and Vasileios Megalooikonomou. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Evaluation and Sociolinguistic Analysis of Text Features for Gender and Age Identification

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Evaluation and Sociolinguistic Analysis of Text Features for Gender and Age Identification. / Simaki, Vasiliki; Mporas, Iosif; Megalooikonomou, Vasileios.
In: American Journal of Engineering and Applied Sciences, Vol. 9, No. 4, 25.09.2016, p. 868-876.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Simaki, V, Mporas, I & Megalooikonomou, V 2016, 'Evaluation and Sociolinguistic Analysis of Text Features for Gender and Age Identification', American Journal of Engineering and Applied Sciences, vol. 9, no. 4, pp. 868-876. https://doi.org/10.3844/ajeassp.2016.868.876

APA

Simaki, V., Mporas, I., & Megalooikonomou, V. (2016). Evaluation and Sociolinguistic Analysis of Text Features for Gender and Age Identification. American Journal of Engineering and Applied Sciences, 9(4), 868-876. https://doi.org/10.3844/ajeassp.2016.868.876

Vancouver

Simaki V, Mporas I, Megalooikonomou V. Evaluation and Sociolinguistic Analysis of Text Features for Gender and Age Identification. American Journal of Engineering and Applied Sciences. 2016 Sept 25;9(4):868-876. doi: 10.3844/ajeassp.2016.868.876

Author

Simaki, Vasiliki ; Mporas, Iosif ; Megalooikonomou, Vasileios. / Evaluation and Sociolinguistic Analysis of Text Features for Gender and Age Identification. In: American Journal of Engineering and Applied Sciences. 2016 ; Vol. 9, No. 4. pp. 868-876.

Bibtex

@article{82b78bf89fe3406ebf1dfa72b7c6ab1c,
title = "Evaluation and Sociolinguistic Analysis of Text Features for Gender and Age Identification",
abstract = "The paper presents an interdisciplinary study in the field of automatic gender and age identification, under the scope of sociolinguistic knowledge on gendered and age linguistic choices that social media users make. The authors investigated and gathered standard and novel text features used in text mining approaches on the author's demographic information and profiling and they examined their efficacy in gender and age detection tasks on a corpus consisted of social media texts. An analysis of the most informative features is attempted according to the nature of each feature and the information derived after the characteristics' score of importance is discussed.",
keywords = "Sociolinguistics, Text Mining, Feature Ranking, ReliefF Algorithm, Gender Detection, Age Identification",
author = "Vasiliki Simaki and Iosif Mporas and Vasileios Megalooikonomou",
note = "{\textcopyright} 2016 Vasiliki Simaki, Iosif Mporas and Vasileios Megalooikonomou. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.",
year = "2016",
month = sep,
day = "25",
doi = "10.3844/ajeassp.2016.868.876",
language = "English",
volume = "9",
pages = "868--876",
journal = "American Journal of Engineering and Applied Sciences",
publisher = "Neuroscience Publications",
number = "4",

}

RIS

TY - JOUR

T1 - Evaluation and Sociolinguistic Analysis of Text Features for Gender and Age Identification

AU - Simaki, Vasiliki

AU - Mporas, Iosif

AU - Megalooikonomou, Vasileios

N1 - © 2016 Vasiliki Simaki, Iosif Mporas and Vasileios Megalooikonomou. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

PY - 2016/9/25

Y1 - 2016/9/25

N2 - The paper presents an interdisciplinary study in the field of automatic gender and age identification, under the scope of sociolinguistic knowledge on gendered and age linguistic choices that social media users make. The authors investigated and gathered standard and novel text features used in text mining approaches on the author's demographic information and profiling and they examined their efficacy in gender and age detection tasks on a corpus consisted of social media texts. An analysis of the most informative features is attempted according to the nature of each feature and the information derived after the characteristics' score of importance is discussed.

AB - The paper presents an interdisciplinary study in the field of automatic gender and age identification, under the scope of sociolinguistic knowledge on gendered and age linguistic choices that social media users make. The authors investigated and gathered standard and novel text features used in text mining approaches on the author's demographic information and profiling and they examined their efficacy in gender and age detection tasks on a corpus consisted of social media texts. An analysis of the most informative features is attempted according to the nature of each feature and the information derived after the characteristics' score of importance is discussed.

KW - Sociolinguistics

KW - Text Mining

KW - Feature Ranking

KW - ReliefF Algorithm

KW - Gender Detection

KW - Age Identification

U2 - 10.3844/ajeassp.2016.868.876

DO - 10.3844/ajeassp.2016.868.876

M3 - Journal article

VL - 9

SP - 868

EP - 876

JO - American Journal of Engineering and Applied Sciences

JF - American Journal of Engineering and Applied Sciences

IS - 4

ER -