Evaluation and sociolinguistic analysis of text features for gender and age identification

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskrift

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.

Detaljer

Författare
Enheter & grupper
Externa organisationer
  • Linnaeus University
  • University of Hertfordshire
  • University of Patras
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Jämförande språkvetenskap och lingvistik

Nyckelord

Originalspråkengelska
Sidor (från-till)868-876
Antal sidor9
TidskriftAmerican Journal of Engineering and Applied Sciences
Volym9
Utgåva nummer4
StatusPublished - 2016
PublikationskategoriForskning
Peer review utfördJa