EPISODE · Nov 5, 2020 · 32 MIN
Detecting Fake News
from The Data Exchange with Ben Lorica · host Ben Lorica
Subscribe: Apple • Android • Spotify • Stitcher • Google • RSS.In this episode of the Data Exchange I speak with Xinyi Zhou, a graduate student in Computer and Information Science at Syracuse University. Xinyi and her advisor (Reza Zafarani) recently wrote a comprehensive survey paper entitled “A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities”. They set out to organize the many different methods and perspectives used to detect fake news. Their paper is a great resource for anyone wanting to understand the strengths and limitations of various state-of-the-art techniques, and a feel for where the research community might be headed in the near future.Download the 2020 NLP Survey Report and learn how companies are using and implementing natural language technologies.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.
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Subscribe: Apple • Android • Spotify • Stitcher • Google • RSS. In this episode of the Data Exchange I speak with Xinyi Zhou, a graduate student in Computer and Information Science at Syracuse University. Xinyi and her advisor (Reza Zafarani) recently wrote a comprehensive survey paper entitled “A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities”. They set out to organize the many different methods and perspectives used to detect fake news. Th...
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Detecting Fake News
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