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COVID-19 Fake News Detection on Social Media
6th International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering, IC4ME2 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1874263
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. © 2021 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 6th International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering, IC4ME2 2021 Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 6th International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering, IC4ME2 2021 Year: 2021 Document Type: Article