Theoretical and Natural Science

Theoretical and Natural Science

TNS Vol.2 (CIAP 2022), 02 February 2023


Open Access | Article

The Covid-19 Disinformation Detection on Social Media Using the NLP Approaches

Yi Quan 1
1 School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guangdong, 510006, China

* Author to whom correspondence should be addressed.

Theoretical and Natural Science, TNS Vol.2 (CIAP 2022), 241-246
Published 02 February 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Yi Quan. The Covid-19 Disinformation Detection on Social Media Using the NLP Approaches. TNS (2023) TNS Vol.2 (CIAP 2022): 241-246.

Abstract

Artificial intelligence has emerged with big data technologies in natural language processing and been applied to creative solutions for overload information especially around the time of the COVID-19 epidemic. This paper provides a comprehensive review of research dedicated to applications of artificial intelligence in misinformation detection. This work organizes the necessary background material for COVID-19-related misinformation detection in NLP, concentrating on the transfer learning technique. Database, data preparation, and modeling make up the major body of information. In the part of modeling, it will merge the attributes of the pre-trained model with the specifical task scenario to explain and present pertinent comments on the future model's improvement under the task scenario. This research will benefit the decision-making and information screen for people's inability to distinguish truth from fiction during the COVID-19 pandemic.

Keywords

Language Model, BERT, Natural Language Processing, COVID-19, XLNet

References

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Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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