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CS Special Seminar: "Data Science for Healthy Online Interactions"

Event Type
Seminar/Symposium
Sponsor
ECE Illinois
Location
2405 Siebel Center
Date
Apr 4, 2019   10:00 am  
Speaker
Srijan Kumar
Views
2
Originating Calendar
ECE ILLINOIS Calendar

Abstract:  

The web enables users to interact with one another and shape opinion at an unprecedented speed and scale. However, the prevalence of disinformation and malicious users makes the web unsafe and unreliable, for example, 40% of users have experienced online harassment and platforms have disabled user comments because of trolling. In this talk, I will present data science methods that help us to create a better and safer web ecosystem for everyone. In particular, I will present methods to extract knowledge from the complex social graph structure to characterize, detect, and mitigate the damage of disinformation and malicious users. In the talk, I will describe graph mining collective classification and graph embedding methods to identify fake reviewers in e-commerce platforms and understand how online communities harass one another. These methods are being used in production at Flipkart, India's largest e-commerce platform, and being implemented at Reddit and Wikipedia.

I will conclude the talk by describing my future research directions to enable a healthy web ecosystem for everyone. I will describe my goal to proactively forecast how malicious behavior will evolve in the future, both on the web and face-to-face conversations.

 

Bio: 

Srijan Kumar (https://stanford.edu/~srijan/) is a postdoctoral scholar in Computer Science at Stanford University. His research investigates data science and machine learning to create healthy online and offline interactions, focusing on developing methods to curb deception, misbehavior, and disinformation. His methods have had a tangible real-world impact and are being used at major tech companies, including Flipkart, Reddit, and Wikipedia. His research has received the ACM SIGKDD Doctoral Dissertation Award runner-up 2018, Larry S. Davis Doctoral Dissertation Award 2018, and WWW Best Paper Award runner-up 2017. His research is interdisciplinary and has been included in the curriculum at several universities, including UIUC, University of Michigan, and Stanford University. His research has been included in documentary (Familiar Shapes) and covered in popular press, including CNN, The Wall Street Journal, Wired, and New York Magazine. He did his Ph.D. in Computer Science from University of Maryland, College Park, and B.Tech. from Indian Institute of Technology, Kharagpur.

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