The business question driving my analysis is: can a machine learning system, trained on labeled examples of true and fake news from the 2016-2018 election cycle, learn to distinguish the two with meaningful accuracy - and in doing so, identify the linguistic, emotional, and topical fingerprints that separate misinformation from credible reporting? The answer has direct applications for social media platforms, news aggregators, fact-checking organizations, and election integrity agencies that need to evaluate the credibility of political content at scale and in near-real time.

This project was part of my Masters and Portfolio Project, where i built a Dashboard for providing quicks insights into Malawi Trade Information including, Value, Volume, and Trade Partners. I built it using PowerBi.