NLP-based Feature Extraction for the Detection of COVID-19 Misinformation Videos on YouTube
Juan Carlos Medina Serrano, Orestis Papakyriakopoulos, Simon Hegelich
Abstract
We present a simple NLP methodology for detecting COVID-19 misinformation videos on YouTube by leveraging user comments. We use transfer learning pre-trained models to generate a multi-label classifier that can categorize conspiratorial content. We use the percentage of misinformation comments on each video as a new feature for video classification.- Anthology ID:
- 2020.nlpcovid19-acl.17
- Volume:
- Proceedings of the 1st Workshop on NLP for COVID-19 at ACL 2020
- Month:
- July
- Year:
- 2020
- Address:
- Online
- Editors:
- Karin Verspoor, Kevin Bretonnel Cohen, Mark Dredze, Emilio Ferrara, Jonathan May, Robert Munro, Cecile Paris, Byron Wallace
- Venue:
- NLP-COVID19
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- Language:
- URL:
- https://aclanthology.org/2020.nlpcovid19-acl.17
- DOI:
- Cite (ACL):
- Juan Carlos Medina Serrano, Orestis Papakyriakopoulos, and Simon Hegelich. 2020. NLP-based Feature Extraction for the Detection of COVID-19 Misinformation Videos on YouTube. In Proceedings of the 1st Workshop on NLP for COVID-19 at ACL 2020, Online. Association for Computational Linguistics.
- Cite (Informal):
- NLP-based Feature Extraction for the Detection of COVID-19 Misinformation Videos on YouTube (Medina Serrano et al., NLP-COVID19 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2020.nlpcovid19-acl.17.pdf
- Code
- JuanCarlosCSE/YouTube_misinfo