arxiv (@arxiv_org) tweetou: XFake: Explainable Fake News Detector with Visualizations. https://t.co/Y08bjt7cUD https://t.co/NtoQQslm4n https://twitter.com/arxiv_org/status/1152410197740023808?s=17
XFake: Explainable Fake News Detector with Visualizations
In this demo paper, we present the XFake system, an explainable fake news
detector that assists end-users to identify news credibility. To effectively
detect and interpret the fakeness of news items, we jointly consider both
attributes (e.g., speaker) and statements. Specifically, MIMIC, ATTN and PERT
frameworks are designed, where MIMIC is built for attribute analysis, ATTN is
for statement semantic analysis and PERT is for statement linguistic analysis.
Beyond the explanations extracted from the designed frameworks, relevant
supporting examples as well as visualization are further provided to facilitate
the interpretation. Our implemented system is demonstrated on a real-world
dataset crawled from PolitiFact, where thousands of verified political news
have been collected.
Utilidade pública: como parar o spam chato por SMS de Rappi, Uber e iFood – #ficadica – UOL