Covid-19 fake news detection on social media

Paper

Mumenin, Khondoker Mirazul, Reza, Khondker Jahid, Shathi, Swarna Saha, Akter, Humayra, Raihan, M., Hassan, Md Mehedi, Rahman, Shagoto and Awal, Md Abdul. 2022. "Covid-19 fake news detection on social media." 2021 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2). Rajshahi, Bangladesh 26 - 27 Dec 2021 Bangladesh. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/IC4ME253898.2021.9768523
Paper/Presentation Title

Covid-19 fake news detection on social media

Presentation TypePaper
AuthorsMumenin, Khondoker Mirazul, Reza, Khondker Jahid, Shathi, Swarna Saha, Akter, Humayra, Raihan, M., Hassan, Md Mehedi, Rahman, Shagoto and Awal, Md Abdul
Journal or Proceedings TitleProceedings of 2021 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2)
Number of Pages4
Year2022
PublisherIEEE (Institute of Electrical and Electronics Engineers)
Place of PublicationBangladesh
ISBN9781665406376
9781665406383
Digital Object Identifier (DOI)https://doi.org/10.1109/IC4ME253898.2021.9768523
Web Address (URL) of Paperhttps://ieeexplore.ieee.org/document/9768523
Web Address (URL) of Conference Proceedingshttps://ieeexplore.ieee.org/xpl/conhome/9768399/proceeding
Conference/Event2021 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2)
Event Details
2021 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2)
Delivery
In person
Event Date
26 to end of 27 Dec 2021
Event Location
Rajshahi, Bangladesh
Abstract

Since the outbreak of COVID-19, social media plays an important role to circulate pandemic news around the world. Some malevolent users may take an advantage of this and spread fake news to attract people for business and research purposes. In this paper, we take an approach by applying existing machine learning algorithms to detect fake news in social media and show a comparison of their performances. In our study, the support vector classifier (SVC) outperforms the rest of the classifiers based on different statistical metrics. Therefore, the SVC classifier has been considered as our proposed classifier model to identify fake COVID-19 news in social media. Two word clouds have also been generated based on the appearance of words in the news that shows an insignificant difference between true and fake news.

KeywordsCOVID-19; fake news; social media; machine learning
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020460208. Natural language processing
Public Notes

Files associated with this item cannot be displayed due to copyright restrictions.

Byline AffiliationsKhulna University, Bangladesh
University of New England
North Western University, Bangladesh
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