Prabhakar Raghavan

Monday, Aug. 22 - 8:30-10am - Crystal Ballrom

We propose a notion of incentive networks, modeling online settings in which multiple participants in a network help each other find information. Within this general setting, we study query incentive networks, a natural abstraction of question-answering systems with rewards for finding answers. We analyze strategic behavior in such networks and under a simple model of networks, show that the Nash equilibrium for participants' strategies exhibits an unexpected threshold phenomenon. (Joint work with Jon Kleinberg.)

Gian Fulgoni

Tuesday, Aug. 23 - 8:30-10am - Crystal Ballrom

The Internet takes behavioral consumer research to a new level by providing the ability to passively and continuously monitor the complete online behavior of millions of consumers in an opt-in, privacy protected manner. Imagine the analytical possibilities if every site visited, every page viewed, content seen, transaction conducted ..... all of this granularity in behavior --- was continuously captured with explicit consumer permission for millions of consumers and privacy was protected. What unique insights could one gain into consumers' behavior, their interests, passions and lifestyles? What behavior could be predicted? What commercial applications would be possible?

Gian Fulgoni, Chairman and co-founder of comScore Networks, will discuss how comScore built its global database of 5 million Internet users and review some of the commercial and academic applications that the database has created.

Albert-L�szl� Barab�si

Wednesday, Aug. 24 - 9:30-10:30am - Regency C+D

Networks with complex topology describe systems as diverse as the cell, the World Wide Web or the society. The emergence of most networks is driven by self-organizing processes that are governed by simple but generic laws. The analysis of the cellular network of various organisms shows that cells and complex man-made networks, such as the Internet or the world wide web, and many social and collaboration networks share the same large-scale topology. I will show that the scale-free topology of these complex webs have important consequences on their robustness against failures and attacks, with implications on drug design, the Internet's ability to survive attacks and failures, and the ability of ideas and innovations to spread on the network.