Fake news detection

Abstract

Rumors are one of the oldest mass mediums in the world. Primarily writing and spreading false information over the internet, recently, they have emerged as a dangerous threat to governments, businesses, and citizens. In the financial markets, where all action is based on news, the stakes are much higher. The biggest challenge with rumors is to tell them apart from accurate information. Furthermore, due to the abundance of data over social media, manual scanning of financial rumors is inefficient. Several studies have been done to study rumor detection using big data analytics. In this project, we aim to create an automated model for rumor detection using two existing datasets.