Stacked authorship attribution of digital texts

作者：

Highlights：

• A novel stacked text authorship attribution method.

• A dynamic selection method for multiple authorship attribution scenarios.

• Robust results across multiple domains, languages, and settings.

摘要

•A novel stacked text authorship attribution method.•A dynamic selection method for multiple authorship attribution scenarios.•Robust results across multiple domains, languages, and settings.

论文关键词：Natural Language Processing,Authorship Attribution,Author Identification

论文评审过程：Received 27 July 2020, Revised 16 February 2021, Accepted 4 March 2021, Available online 13 March 2021, Version of Record 31 March 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.114866