Fake News Detection: Covid-19 Perspective

1
Md. Ziaur Rahman Shamim
Md. Ziaur Rahman Shamim
2
Shaheena Sultana
Shaheena Sultana
3
Anika Tabassum
Anika Tabassum
4
Israt Tabassum
Israt Tabassum
5
Sarkar Binoyee Farha
Sarkar Binoyee Farha
1 Notre Dame University Bangladesh

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The development of social media has contributed to a remarkable rise in the spread of fake news. Today people rely more on online news outlets. The chance of receiving fake news on an online platform is high. As we went through a pandemic and the Covid-19 was the most absorbing topic of 2020, much news on Covid-19 was published every day in traditional media and social media. Among that news, some are fake. In this work, we have collected a new dataset for detecting fake news from traditional media on Covid-19. We have gathered more than 3000 pieces of news from traditional media out of the 170 are fake ones that were collected from fact-checking sites. Then we have tested the existing four classification algorithms with our dataset using Count Vectorizer and TF-IDF. We have merged 170 fake news with four scales of true news and analyzed the outcome.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

Md. Ziaur Rahman Shamim. 2026. \u201cFake News Detection: Covid-19 Perspective\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 22 (GJCST Volume 22 Issue C2): .

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Artificial intelligence in Covid-19 info verification.
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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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GJCST-C Classification: DDC Code: 004.678 LCC Code: TK5105.875.I57
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July 19, 2022

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English

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The development of social media has contributed to a remarkable rise in the spread of fake news. Today people rely more on online news outlets. The chance of receiving fake news on an online platform is high. As we went through a pandemic and the Covid-19 was the most absorbing topic of 2020, much news on Covid-19 was published every day in traditional media and social media. Among that news, some are fake. In this work, we have collected a new dataset for detecting fake news from traditional media on Covid-19. We have gathered more than 3000 pieces of news from traditional media out of the 170 are fake ones that were collected from fact-checking sites. Then we have tested the existing four classification algorithms with our dataset using Count Vectorizer and TF-IDF. We have merged 170 fake news with four scales of true news and analyzed the outcome.

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Fake News Detection: Covid-19 Perspective

Md. Ziaur Rahman Shamim
Md. Ziaur Rahman Shamim Notre Dame University Bangladesh
Shaheena Sultana
Shaheena Sultana
Anika Tabassum
Anika Tabassum
Israt Tabassum
Israt Tabassum
Sarkar Binoyee Farha
Sarkar Binoyee Farha

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