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

Vasiliki Simaki, Iosif Mporas, Vasileios Megalooikonomou

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)868-876
Number of pages9
JournalAmerican Journal of Engineering and Applied Sciences
Issue number4
Publication statusPublished - 2016


  • Age identification
  • Feature ranking
  • Gender detection
  • ReliefF algorithm
  • Sociolinguistics
  • Text mining


Dive into the research topics of 'Evaluation and sociolinguistic analysis of text features for gender and age identification'. Together they form a unique fingerprint.

Cite this