Xia Hu      Xia Hu

Ph.D. Candidate, Computer Science and Engineering
Arizona State University
"Understanding Social Spammers: A Data Mining Perspective”
Monday, December 8, 4:00 PM
Packard Lab, Room 466

Abstract:   With the growing popularity of social media, social spamming has become rampant in the platforms. Many (fake) accounts, known as social spammers, are employed to overwhelm other users with unwanted information in social media. The social spammers are a special kind of spammers who coordinate among themselves to launch various attacks such as spreading ads to generate sales, disseminating pornography, viruses, phishing, or simply sabotaging a system's reputation. In this talk, to tackle the challenges raised in social media data for spammer detection, I will introduce a novel and systematic analysis of social spammers from data mining perspective. Specifically, I will first formally define the problem of social spammer detection and discuss the unique properties of social media data with its challenges. By analyzing the properties of two most important types of information, i.e., social network and content information, I will introduce a unified framework by collectively use heterogeneous information in social media. To tackle the labeling bottleneck in social media, I will show how we can take advantage of the existing resources, e.g., emails, SMS and the web, for spammer detection in microblogging. Finally, a solution for efficient online processing will be discussed to handle the fast-evolving social spammers.

Bio:  Xia Hu is a Ph.D. candidate of Computer Science and Engineering at Arizona State University. His research interests are in data mining, social network analysis, machine learning, etc. As a result of his research work, he has published nearly 40 papers in several major academic venues, including WWW, SIGIR, KDD, WSDM, IJCAI, AAAI, CIKM, SDM, etc. One of his papers was selected in the Best Paper Shortlist in WSDM'13. He is the recipient of the 2014 ASU’s President’s Award for Innovation, and Faculty Emeriti Fellowship. He has served on program committees for several major conferences such as IJCAI, SDM and ICWSM, and reviewed for multiple journals, including IEEE TKDE, ACM TOIS and Neurocomputing. His research attracts wide range of external government and industry sponsors, including NSF, ONR, AFOSR, Yahoo!, and Microsoft.

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