TY  - JOUR
AU  - Simaki, Vasiliki 
AU  - Mporas, Iosif 
AU  - Megalooikonomou, Vasileios 
PY  - 2016
TI  - Evaluation and Sociolinguistic Analysis of Text Features for Gender and Age Identification
JF  - American Journal of Engineering and Applied Sciences
VL  - 9
IS  - 4
DO  - 10.3844/ajeassp.2016.868.876
UR  - https://thescipub.com/abstract/ajeassp.2016.868.876
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.