MCWDST: a Minimum-Cost Weighted Directed Spanning Tree Algorithm for Real-Time Fake News Mitigation in Social Media

With the accelerated technology adoption by a growing number of users, social media have become the main medium for the dissemination of information on current news and events. While these new media bring several benefits (e.g., a large number of consumers reached, instant and continuous updates on one's topics of interest), they also enable the spread of harmful information in the form of fake news, and may thus polarize public discourse regarding critical topics (e.g., elections [32], vaccination [30], health hazards [24]) and threaten democratic values [35]. Because of its detrimental effects on society at large, the fake news phenomenon has been studied by scientists and practitioners alike; fake news is defined as news articles that intentionally contain verifiably false misleading information inconsistent with factual reality [2, 23, 46, 10, 4, 13, 43]. To mitigate the threat of fake news, journalists have started to manually classify news and offer websites with fact-checking mechanisms that provide a verdict regarding its veracity, such as PolitiFact (https://www.politifact.com/)