Models and Algorithms for Online Crowd Systems
In the last years we have observed the emergence of a variety of systems where users communicate and collaborate online, explicitely or implicitely, producing knowledge and new services. Success stories include Wikipedia, Linux and the open source community, crowdsourcing services, online labor marketplaces, and social-media platforms, to name a few. This new paradigm, where users collaborate using the Internet for coordination, requires the development of new models and algorithms to capture, aggregate, and organize the contribution of humans. In this talk I will start with a high-level presentation of some of these systems and with some of the issues needed to be captured when trying to formally model them. In particular I will present models and algorithms for assigning users on crowdsourcing systems and of methods for distilling information from social-media and sensor networks. Furthermore, I will describe some current work on the network effect on the "wisdom fo the crowds." I will conclude with a discussion of challenges for future work.
Bio: Aristidis Anagnostopoulos is an assistant professor at the Department of Computer, Control, and Management Engineering (DIAG) at Sapienza University of Rome, since 2012. He obtained his Ph.D. from Brown University in 2006, afterwards he did a postdoc at Yahoo! Research in Silicon Valley and from 2010 to 2009 he was a Marie-Curie Fellow at DIAG. His main research interests include randomized and approximation algorithms and their applications on data mining, social networks, and web search.