Information and Influence Propagation in Social Networks

Wei Chen is a Senior Researcher in Microsoft Research Asia, Beijing, China. He is also an Adjunct Professor at Tsinghua University. He received Bachelor and Master of Engineering degrees from Tsinghua University, and a Ph.D. De gree from Cornell University. His research interests include computational and game theoretic aspects of social networks, algorithmic game theory, distributed computing, and fault tolerance. He won the William C. Carter Award in 2000 in the area of dependable computing for his dissertation research on failure de tection, and his co-authored paper on game-theoretic community detection won the best student paper award in ECML PKDD 2009. He has done a series of research work on social influence dynamics, and social influence maximization, which appeared in recent KDD, ICDM, SDM, WSDM, ICWSM, ICML and AAAI conferences. He is also active in the so cial network research community, including organizing an international workshop, guest-editing ACM TKDD special issue oncomputational aspects of social networks, and participating in pro gram committees of KDD, WWW, WSDM, etc. He is a member of Task Force on Big Data of Chinese Computer FederationCarlos Castillo is a Senior Scientist at the Qatar Computing Research Institute in Doha. He received his Ph.D. from the University of Chile (2004), and was a visiting scientist at Universitat Pompeu Fabra (2005) and Sapienza Univer sitá di Roma (2006) before working as a research scientist at Yahoo! Research (2006-2012). He has been influential in the areas of adversarial web search and web content quality and credibility. He has served in the PC or SPC of all ma jor conferences in his area (WWW, WSDM, SIGIR, KDD, CIKM, etc.), and co-organized the Adversarial Information Retrieval Workshop and Web Spam Challenge in 2007 and 2008, the ECML/PKDD Discovery Challenge in 2010 and the Web Quality Workshop from 2011–2013. His current research focuses in the application of web min ing methods to problems in the domainof on-line news and humanitarian crises.

• Acknowledgments.- Introduction.- Stochastic Diffusion Models.- Influence Maximization.- Extensions to Diffusion Modeling and Influence Maximization.- Learning Propagation Models.- Data and Software for Information/Influence: Propagation Research.- Conclusion and Challenges.- Bibliography.- Authors' Biographies.- Index.