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:
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/2020.nlpcovid19-acl.17.pdf
Code
 JuanCarlosCSE/YouTube_misinfo