Following the American presidential election in 2016, the terms ”fake news” was popularized and has since been a common term in the public vocabulary. While quite recently popularized, fake news is a phenomenon that is as old as news itself and is most commonly defined as purposeful disinformation used to untrue information or skewed reporting intended to push a certain narrative. In recent years, fake news has seen frequently in attempts to influence elections or by organized crime organizations in various efforts to make money, not least drawing from the ongoing CoVid-19 pandemic. We argue that the phenomenon must be researched from technical as well as from social aspects, since it involved using technical tools to spread information targeted humans. In this paper, we identify key methods for automatic fake news detection in order to lay the foundation for end-user support system designed to help users identify and avoid fake news.