Augmenting Stylometric Features to Improve Detection of Propaganda and Manipulation
| Authors | |
|---|---|
| Year of publication | 2023 |
| Type | Article in Proceedings |
| Conference | Proceedings of the Seventeenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2023 |
| MU Faculty or unit | |
| Citation | |
| web | |
| Keywords | stylometry; propaganda detection; manipulative style analysis; Propaganda dataset; Czech |
| Description | Identification of manipulative techniques in newspaper texts allows an informed reader to cope with the text content without being negatively influenced. In this paper, we present new developments in using stylometry to support a deep learning neural network model in labelling newspaper articles for the presence of specific manipulative techniques. We also evaluate all stylometric features in 16 groups and improve the manipulation detection results in 15 of 17 techniques. |
| Related projects: |