Prof. Kyumin Lee from Utah State Univeristy will give the following talk. Those interested, please attend.
- Title: Combating Threats to the Quality of Information in Social Systems
- Speaker: Prof. Kyumin Lee (Utah State Univeristy)
- Time: 2014.6.24(Tue), 10am – 11am
- Venue: #1222, E2-1 Building
- Many large-scale social systems such as Web-based social networks, online social media sites and Web-scale crowdsourcing systems have been growing rapidly, enabling millions of human participants to generate, share and consume content on a massive scale. This reliance on users can lead to many positive effects, including large-scale growth in the size and content in the community, bottom-up discovery of “citizen-experts”, serendipitous discovery of new resources beyond the scope of the system designers, and new social-based information search and retrieval algorithms.
But the relative openness and reliance on users coupled with the widespread interest and growth of these social systems carries risks and raises growing concerns over the quality of information in these systems.
In this research, we focus on countering threats to the quality of information in self-managing social systems. Concretely, we identify three classes of threats to these systems: (i) content pollution by social spammers, (ii) coordinated campaigns for strategic manipulation, and (iii) threats to collective attention. To combat these threats, we propose three inter-related methods for detecting evidence of these threats, mitigating their impact, and improving the quality of information in social systems. We augment this three-fold defense with an exploration of their origins in “crowdturfing” — a sinister counterpart to the enormous positive opportunities of crowdsourcing.
Kyumin Lee’s primary research interests are in information quality and data analytics over large-scale networked information systems like the Web, social media systems, and other emerging distributed systems. His current work focuses on both a negative and a positive dimension. On one hand, he focuses on threats to these systems and designs methods to mitigate negative behaviors; on the other, he looks for positive opportunities to mine and analyze these systems for developing next generation algorithms and architectures that can empower decision makers. He received Google Faculty Research Award in 2013, Amazon Web Services in Research Grant and Research Catalyst Grant at Utah State University in 2014. He has published more than 30 peer-reviewed research papers in top journals and conferences such as TIST, SIGIR, WWW, CIKM and ICWSM. His work was introduced by the MIT Technology review and Wired. He received his Ph.D. from Texas A&M in 2013. He interned twice – once at IBM Research-Almaden and once at eBay Research Labs. He also worked for NHN as a software engineer.