Fake News Detection via NLP is Vulnerable to Adversarial Attacks

Understand

News plays a significant role in shaping people's beliefs and opinions.

• Fake news has always been a problem, which wasn't exposed to the mass public until the past election cycle for the 45th President of the United States.
• While quite a few detection methods have been proposed to combat fake news since 2015, they focus mainly on linguistic aspects of an article without any fact checking.
• In this paper, we argue that these models have the potential to misclassify fact-tampering fake news as well as under-written real news.