The SysFake Project


Broadly speaking, “Fake news” refers to false news stories to deceive or mislead people. Despite several recent high-profile incidents of fake news (e.g., pizzagate) and wide spread existence of fake news websites, however, we do not fully understand about fake news yet—i.e., how it is made, who/why makes them, how it spreads in the network, how it differs from legitimate news, or why/how people fall for it, etc. The better understanding of fake news would be able to help people equip better to handle fake news in future. With the risen interests on the topic and its huge societal implications, therefore, we believe that this is a right time to embark on a research project on fake news and make intellectual contributions with broader impacts on society. 

In particular, in this SysFake (pronounced as "Cease Fake") project at Penn State, we explore the possibility of training machines to detect fake news accurately and investigate whether they can do a better job than humans. We propose to combine complementary perspectives and understanding on fake news from both computer science and social science disciplines, implement such findings into a computational model, and carry out validating experiments and user studies.

Our results will not only have significant intellectual merit in building a machine-based solution for detecting fake news, but also have far-reaching broader impact on society and education by helping improve the quality of information used by citizens to make important decisions in almost all domains.

This project is being supported by Penn State's ICS seed grant, IST seed grant, and NSF CISE-SBE grant.


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