Rahman, Munshi MahbuburFoulds, James R.2020-05-182020-05-18Munshi Mahbubur Rahman and James R. Foulds,End-to-End Joint Modeling for Fake News Detection, http://jfoulds.informationsystems.umbc.edu/papers/2020/Rahman%20(2020)%20-%20End-to-End%20Joint%20Modeling%20for%20Fake%20News%20Detection%20(MASC-SLL).pdfhttp://hdl.handle.net/11603/18650Mid-Atlantic Student Colloquium on Speech, Language and Learning (MASC-SLL)The rapid spread of misinformation, including misleading and manipulative content, is a current and urgent threat to our society and to our democracy (Starbird, 2017). Several fact-checking websites (e.g., Snopes.com and PolitiFact.com) have been formed to manually verify/falsify claims, but this process is expensive and lacks scalability. An automated process to verify these claims is in high demand so that we can keep up with the speed that misinformation spreads.2 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.Text