On information reliability, source trustworthiness and fake news
Event type: Open lecture
Event dates: Ср, 07/25/2018
Country, city: Ukraine, Львів
Address of the event: MSc in Data Science at UCU Kozelnytska, 2a
Web-site of the event: https://www.facebook.com/events/26007428...
In recent years, social media and online social networking sites have become a major disseminator of false facts, urban legends, fake news, or, more generally, misinformation. To overcome this problem, online platforms are, on the one hand, empowering their users—the crowd—with the ability to evaluate the content they are exposed to and, on the other hand, resorting to trusted third parties for fact checking stories. However, given the noise in the evaluations provided by the crowd and the high cost of fact checking, the above mentioned measures require careful reasoning and smart algorithms. In this talk, I will first describe a modeling framework based on marked temporal point process that links noisy evaluations
provided by the crowd to robust, unbiased and interpretable notions of information reliability and source trustworthiness. Then, I will introduce a scalable online algorithm, CURB, to select which stories to send for fact checking and when to do so to efficiently reduce the spread of fake news and misinformation with provable guarantees. Finally, I will show the effectiveness of our modeling framework and our algorithm using real-world data gathered from Wikipedia, Stack Overflow, Twitter and Weibo. This talk includes joint work with Behzad Tabibian, Jooyeon Kim, Isabel Valera, Mehrdad Farajtabar, Le Song, Alice Oh and Bernhard Schoelkopf.
Speaker: Dr. Manuel Gomez Rodriguez
Manuel Gomez Rodriguez is a tenure-track faculty at Max Planck Institute for Software Systems. Manuel develops machine learning and large-scale data mining methods for the analysis, modeling and control of large social and information online systems. He is particularly interested in the creation, acquisition and/or dissemination of reliable knowledge and information, which is ubiquitous in the Web and social media and has received several recognitions for his research, including an Outstanding Paper Award at NIPS’13 and a Best Research Paper Honorable Mention at KDD’10 and WWW’17. Manuel holds a BS in Electrical Engineering from Carlos III University in Madrid (Spain), a MS and PhD in Electrical Engineering from Stanford University, and has received postdoctoral training at the Max Planck Institute for Intelligent Systems. You can find more about him at http://learning.mpi-sws.org
Meeting language is English.
Free entrance after registration.