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A Comparative Approach to Detecting COVID-19 Fake News through Machine Learning Models | IEEE Conference Publication | IEEE Xplore

A Comparative Approach to Detecting COVID-19 Fake News through Machine Learning Models


Abstract:

Identifying fake news has become an increasingly challenging task in recent years, with the proliferation of digital media and the ease of spreading misinformation. The p...Show More

Abstract:

Identifying fake news has become an increasingly challenging task in recent years, with the proliferation of digital media and the ease of spreading misinformation. The problem has only become more complex with the global pandemic situation, as false information about COVID-19 can have serious consequences for public health and safety. Fortunately, the same technological advancements that have made it easier to spread fake news have also enabled potential solutions to this problem. In this work, we aimed to test and evaluate approaches for automatically classifying fake news. We focused specifically on fake news related to COVID-19, given its widespread impact on public health and the urgency of addressing misinformation in this area. To do this, we trained and evaluated several machine learning models using a dataset of news articles labeled as either "fake" or "real." Our goal was to identify the most accurate and effective model for detecting COVID-19 related fake news. After testing several models, we found that an SVM classifier performed the best, achieving an accuracy of 93.83%. We also conducted an analysis of each model's performance, examining factors such as feature selection and model complexity that may have influenced their results.
Date of Conference: 17-19 January 2024
Date Added to IEEE Xplore: 03 July 2024
ISBN Information:
Print on Demand(PoD) ISSN: 1976-7684
Conference Location: Ho Chi Minh City, Vietnam

I. INTRODUCTION

Alongside the health and economic crisis that the COVID-19 pandemic is still causing in the whole world, there is another form of crisis that started before the pandemic but has grown to be more threatening to all people under the current circumstances – the COVID-19 fake news crisis. According to Cambridge dictionary, "fake news" is a term that refers to false stories that appear to be news, spread on the internet or other media, usually created to influence political views or as a joke [1]. This phenomenon has been evolving and most people have been exposed to fake news at some point. The main reason for our exposure to fake news is social media. According to [2], the use of social media has increased among the American adults by 1 – 2 additional hours per day as of March 2020. Furthermore, 46% of respondents on a survey stated that their use of social media was to stay up-to-date with the news [3]. Other reasons for the continuously increased widespread of fake news, include political influence, lack of awareness towards fake news, the higher levels of uncertainty and distrust and the existence of fake-news-spreading bots [4].

References

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