Using big data to stop fake newsPosted on October 20, 2017
Dongwon Lee, an associate professor in the College of Information Sciences and Technology, and S. Shyam Sundar, distinguished professor in the Donald P. Bellisario College of Communications, will speak on “Big Data and Fake News:
The Penn State Institute for CyberScience (ICS) is hosting the event as part of the ICS CyberScience Seminars, a series of talks on cutting-edge topics of interest to the cyberscience research community at Penn State.
Lee and Sundar will discuss their research on how machine learning may help to detect fake news—stories that are intended to deceive, such as the ones surrounding the recent “Pizzagate” conspiracy theory. Fake news is becoming epidemic; spread through social media and fake news websites, it can even be picked up by mainstream news sources.
Responding to this problem, Lee and Sundar are undertaking a multi-year investigation into the analysis, detection, and educational use of fake news. The ultimate goal is to devise effective machine learning methods for detecting this kind of misinformation.
“This problem is impacting regular citizens around the world. ‘Pizzagate’ is just a single example of how big this epidemic truly is,” said Lee. “Our efforts are to design machine-learning algorithms that will eventually detect false news and fake information in the future.”
Space is limited, so please reserve a seat at the seminar by October 30. The event includes Lee and Sundar’s talk, an extended question-and-answer session, and time to socialize. Refreshments will be served.
ICS CyberScience Seminars explore a wide range of topics. Check out the full slate of speakers for 2017-18.
Lee is an associate professor in the College of Information Sciences and Technology. From 2014 to 2017, he has also served as a program director at National Science Foundation (NSF), co-managing cybersecurity programs such as SFS and SaTC with the yearly budget of $55M. He researches broadly in Data Science, in particular, on the management of and mining in data in diverse forms including structured records, text, multimedia, social media, and Web. He is also interested in applying the human computation framework to solve data science problems, and detecting/curbing challenging online frauds using machine learning techniques.
Sundar is a distinguished professor in the Donald P. Bellisario College of Communications. He is the founder of the Media Effects Research Laboratory, a leading facility of its kind in the country. His research investigates social and psychological effects of technological elements unique to online communication, ranging from websites to newer social and personal media. In particular, his studies experimentally investigate the effects of interactivity, navigability, multi-modality, and agency (source attribution) in digital media interfaces upon online users’ thoughts, emotions, and actions.
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