Abstract
The success of authorship attribution relies on the presence of linguistic features specific to individual authors. There is, however, limited research assessing to what extent authorial style remains constant when individuals switch from one writing modality to another. We measure the effect of writing mode on writing style in the context of authorship attribution research using a corpus of documents composed online (in a web browser) and documents composed offline using a traditional word processor. The results confirm the existence of a “mode effect” on authorial style. Online writing differs systematically from offline writing in terms of sentence length, word use, readability, and certain part-of-speech ratios. These findings have implications for research design and feature engineering in authorship attribution studies.- Anthology ID:
- 2021.eacl-main.97
- Volume:
- Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
- Month:
- April
- Year:
- 2021
- Address:
- Online
- Editors:
- Paola Merlo, Jorg Tiedemann, Reut Tsarfaty
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1146–1155
- Language:
- URL:
- https://aclanthology.org/2021.eacl-main.97
- DOI:
- 10.18653/v1/2021.eacl-main.97
- Cite (ACL):
- Haining Wang, Allen Riddell, and Patrick Juola. 2021. Mode Effects’ Challenge to Authorship Attribution. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pages 1146–1155, Online. Association for Computational Linguistics.
- Cite (Informal):
- Mode Effects’ Challenge to Authorship Attribution (Wang et al., EACL 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2021.eacl-main.97.pdf