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Sociolinguistic Features for Author Gender Identification: From Qualitative Evidence to Quantitative Analysis
Linnaeus University, Faculty of Technology, Department of Computer Science. Lund University.
Univ Patras, Greece.
Univ Hertfordshire,England.
Univ Patras, Greece.
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2017 (English)In: Journal of Quantitative Linguistics, ISSN 0929-6174, E-ISSN 1744-5035, Vol. 24, no 1, 65-84 p.Article in journal (Refereed) Published
Abstract [en]

Theoretical and empirical studies prove the strong relationship between social factors and the individual linguistic attitudes. Different social categories, such as gender, age, education, profession and social status, are strongly related with the linguistic diversity of people's everyday spoken and written interaction. In this paper, sociolinguistic studies addressed to gender differentiation are overviewed in order to identify how various linguistic characteristics differ between women and men. Thereafter, it is examined if and how these qualitative features can become quantitative metrics for the task of gender identification from texts on web blogs. The evaluation results showed that the "syntactic complexity", the "tag questions", the "period length", the "adjectives" and the "vocabulary richness" characteristics seem to be significantly distinctive with respect to the author's gender.

Place, publisher, year, edition, pages
Routledge, 2017. Vol. 24, no 1, 65-84 p.
National Category
Language Technology (Computational Linguistics) Computer Science
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-62067DOI: 10.1080/09296174.2016.1226430ISI: 000396571200004OAI: oai:DiVA.org:lnu-62067DiVA: diva2:1086632
Available from: 2017-04-03 Created: 2017-04-03 Last updated: 2017-05-22Bibliographically approved

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Simaki, Vasiliki
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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • text
  • asciidoc
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