[CSEE Talk] talk: Hu on Understanding Social Spammers, Noon Tue 2/24, ITE325, UMBC

[Tim Finin]

                            CSEE Colloquium

        Understanding Social Spammers: A Data Mining Perspective

                              Xia "Ben" Hu
                    Computer Science and Engineering
                        Arizona State University

                  12:00-1:00 Tuesday, 24 February 2015

With the growing popularity of social media, social spamming has
become rampant on all platforms. Many (fake) accounts, known as social
spammers, are employed to overwhelm legitimate users with unwanted
information. Social spammers are unique due to their coordinated
efforts to launch attacks such as distributing ads to generate sales,
disseminating pornography and viruses, executing phishing attacks, or
simply sabotaging a system's reputation. In this talk, I will
introduce a novel and systematic analysis of social spammers from a
data mining perspective to tackle the challenges raised by social
media data for spammer detection. Specifically, I will formally define
the problem of social spammer detection and discuss the unique
properties of social media data that make this problem challenging. By
analyzing the two most important types of information, network and
content information, I will introduce a unified framework by
collectively using heterogeneous information in social media. To
tackle the labeling bottleneck in social media, I will show how we can
take advantage of the existing information about spam in email, SMS,
and on the web for spammer detection in microblogging. I will also
present a solution for efficient online processing to handle
fast-evolving social spammers.

Xia Hu is a Ph.D. candidate in Computer Science and Engineering at
Arizona State University, supervised by Professor Huan Liu. His
research interests include data mining, machine learning, social
network analysis, 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 for the Best Paper Shortlist in WSDM'13. He is the
recipient of IEEE "Atluri Award" Scholarship, 2014 ASU's President's
Award for Innovation, and Faculty Emeriti Fellowship. He has served on
program committees for several major conferences such as WWW, 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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