Survey on profiling age and gender of text authors

作者：

Highlights：

• Overview of studies and datasets on profiling of age and gender.

• Analysis of various age and gender datasets is presented.

• Interesting findings of age and gender classification are identified.

• Suitable features, preprocessing and machine learning methods are detected.

• Future research proposals for profiling age and gender are suggested.

摘要

•Overview of studies and datasets on profiling of age and gender.•Analysis of various age and gender datasets is presented.•Interesting findings of age and gender classification are identified.•Suitable features, preprocessing and machine learning methods are detected.•Future research proposals for profiling age and gender are suggested.

论文关键词：Age classification,Author profiling,Deep learning,Gender classification,Supervised machine learning,Text classification

论文评审过程：Received 10 June 2021, Revised 19 January 2022, Accepted 29 March 2022, Available online 5 April 2022, Version of Record 21 April 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117140