Evaluation and Sociolinguistic Analysis of Text Features for Gender and Age Identification
| Autor: | Vasiliki Simaki, Iosif Mporas, Vasileios Megalooikonomou |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Environmental Engineering
General Computer Science General Chemical Engineering Energy Engineering and Power Technology 02 engineering and technology computer.software_genre Age and gender Text mining 0202 electrical engineering electronic engineering information engineering Profiling (information science) Social media Feature ranking 060201 languages & linguistics business.industry General Engineering 06 humanities and the arts Geotechnical Engineering and Engineering Geology Linguistics 0602 languages and literature 020201 artificial intelligence & image processing Artificial intelligence business Psychology computer Natural language processing Sociolinguistics |
| Zdroj: | American Journal of Engineering and Applied Sciences. 9:868-876 |
| ISSN: | 1941-7020 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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