Social media vs fake news: Machine learning

As the use of social media is proliferating, there has also been a rise in the circulation of fake news. Fake news in social media involves misleading information to harm and confuse users. The increase in fake news is overwhelming for social media users and academic research continues to propose ways to detect, mitigate and control it. However, various efforts proposed by other users and researchers have failed. Current advancements in artificial intelligence (AI) and machine learning (ML) have the ability to understand human actions and behaviors and interpret them. Moreover, ML could succeed where other methods have failed so far in detecting, mitigating, and controlling fake news on social media platforms.

According to recent research, social media has increased the ease of users' ability to report misleading information and fake news on social media. Fake news on social media is a challenging issue for society because of the consequences on individuals and organizations. Fake news has managed to redefine the human perception of truth and reality in society as Kahn et al. state in 2021. Through literature, it is evidently seen that fake news on social media is impacting societies and organizations, but little is known about how to detect them. This Research Topic aims to examine how machine learning (ML) can detect, control, and mitigate fake news on social media.

Submissions can address but are not limited to the following topics:

- Detecting fake news on social media

- Using machine learning to detect fake news on social media

- Machine Learning classification in detecting fake news on social media

- Mitigating fake news on social media

- Controlling fake news on social media

- The application of machine learning in managing fake news on social media

- The algorithm for detecting fake news on social media