Creating a System for Detecting Fake News in Online Social Networks.

Detecting and combating fake news on social media is crucial due to its social and economic impact. Fake news disrupts news authenticity, leading to biased beliefs and wrong decisions. The challenge lies in automatic and early detection, considering well-written content, privacy issues, and evolving truth values. We propose a system that compiles evidence from public sources for each social media news, enabling dynamic verification. The system handles multimedia and cross-lingual data to enhance evidence extraction. This approach ensures efficient fake news detection while providing transparent justification, suitable for various users and applications.