The Science of Societal and Institutional Networks
- Prof. Mihaela van der Schaar (Email)
- Engineers have studied networks for a long time, originally as infrastructure (e.g. communication networks, energy networks, transportation networks) and only have turned to the study of networks of individuals (e.g. social networks, expert networks), networks of firms/institutions, networks of cities etc. However, the focus of these studies has been on the statistical analysis of such networks -- ignoring how networks form/evolve, the impact of network formation/evolution on the functioning of networks, and the (social) value of. My work focuses precisely these latter issues.
At the heart of my work is a powerful -- but usable -- general framework for understanding and guiding endogenous network formation that allows for heterogeneous agents, imperfect information, and creation, dissemination and consumption of a variety of services and content. I consider the behavior of a group of self-interested and strategic agents (either individuals or institutions) who may create and maintain links to other agents, and produce and disseminate information. Agents and information are heterogeneous. I prove that the typical network that emerges from the self-interested behavior of agents displays a core-periphery structure, with a smaller number of agents at the core (center) of the network and a larger number of agents at the periphery (edges) of the network. Agents in the core link to and communicate with many other agents; agents in the periphery mostly link to and communicate with agents in the core. Because agents' strategic choices incorporate both link formation and information production, the number of agents who produce information and the total amount of information produced both grow with the size of the network. (Thus the celebrated "law of the few" of Bala & Goyal is purely an artifact of their over-simplified/unrealistic model.)
This framework and results provide one of the first systematic theories in the emerging area of network science, and a new way to think about how networks form and evolve, as well as practical advice and tools for designers and planners who create, guide and manage networks of various different kinds, and for regulators who oversee such networks. Most importantly, this framework and these results are consistent with and provide a lens for understanding the extensive empirical literature.
This work has been featured in two recent OpEd pieces in the New York Times as part of a potential solution for building a safer Internet.
Highlighted Publications (For a complete list, please click here.)
- Prof. van der Schaar's talk at Oxford Summer School in Economic Networks [Link]
Y. Song and M. van der Schaar, "Repeated Network Games with Dominant Actions and Individual Rationality,"
IEEE Transactions on Network Science and Engineering, 2018.
S. Zhang and M. van der Schaar, " Reputational Learning and Network Dynamics,"
Submitted, 2016. [Link]
A. Alaa, K. Ahuja, M. van der Schaar, " A Micro-foundation of Social Capital in Evolving Social Networks,"
IEEE Transactions on Network Science and Engineering, 2017. [Link]
Y. Song and M. van der Schaar, " Dynamic Network Formation with Foresighted Agents,"
Submitted, 2016. [Link]
S. Zhang and M. van der Schaar, " From Acquaintances to Friends: Homophily and Learning in Networks,"
2017 JSAC Game Theory for Networks special issue., 2017. [Link]
K. Ahuja, M. van der Schaar and W. R. Zame, " Individualism, Collectivism and Economic Outcomes: A Theory and Some Evidence,"
Submitted, 2017. [Link]
Y. Xiao, F. Dorfler and M. van der Schaar, " Incentive Design in Peer Review: Rating and Repeated Endogenous Matching,"
IEEE Transactions on Network Science and Engineering, 2016. [Link]
A. Alaa, K. Ahuja, M. van der Schaar, " Self-organizing Networks of Information Gathering Cognitive Agents,"
IEEE Transactions on Cognitive Communications and Networking - Inaugural issue (invited paper), vol. 1, no. 1, pp. 100-112, Nov. 2015. [Link]
Y. Song and M. van der Schaar, "Dynamic Network Formation with Incomplete Information,"
Economic Theory, vol. 59, no. 2, pp. 301-331, 2015. [Link]
L. Canzian, K. Zhao, G. C. Wong, M. van der Schaar, "A Dynamic Network Formation Model for Understanding Bacterial Self-Organization into Micro-Colonies,"
IEEE Transactions on Molecular, Biological, and Multi-Scale Communications, vol. 1, no. 1, pp. 76 - 89, 2015. [Link]
C. Tekin and M. van der Schaar, "Distributed Online Learning via Cooperative Contextual Bandits,"
IEEE Trans. Signal Process., vol. 63, no. 14, pp. 3700-3714, 2015. [Link]
Y. Xiao and M. van der Schaar, "Socially-Optimal Design of Service Exchange Platforms with Imperfect Monitoring,"
ACM Transactions on Economics and Computation, vol. 3, no. 4, Jul. 2015. [Link]
C. Tekin, O. Atan and M. van der Schaar, "Discover the Expert: Context-Adaptive Expert Selection for Medical Diagnosis,"
IEEE Transactions on Emerging Topics in Computing, vol. 3, no. 2, pp. 220-234, June. 2015. [Link]
J. Xu and M. van der Schaar, "Efficient Working and Shirking in Networks,"
IEEE JSAC Bonus Issue for Emerging Technologies, vol. 33, no. 4, pp. 651-662, April 2015. [Link]
J. Xu, C. Tekin, S. Zhang and M. van der Schaar, "Distributed Multi-Agent Online Learning Based on Global Feedback,"
IEEE Trans. Signal Process. vol. 63, no. 9, Feb 2015. [Link]
Y. Zhang and
M. van der Schaar, "Strategic Networks: Information Dissemination and Link
Formation Among Self-interested Agents,"
in IEEE J. Sel. Areas Commun. - Special issue on Network Science,
vol. 31, no. 6, pp. 1115-1123, June 2013.
M. van der Schaar, J. Xu and W. Zame, " Efficient Online Exchange via Fiat Money,"
Economic Theory, vol. 54, no. 2, pp. 211-248, Oct. 2013. [Link]
Y. Zhang and M. van der Schaar,
"Information Production and Link Formation in
Social Computing Systems,” in IEEE J. Sel.
Areas Commun. – Special issue on Economics of
Communication Networks and Systems, vol. 30, no. 10, pp. 2136-2145,
J. Park and M. van der Schaar, " A Game Theoretic
Analysis of Incentives in Content Production and Sharing over Peer-to-Peer
Networks, Among Self-interested Agents,"
in IEEE J. Sel. Topics Signal Process.,
vol. 4, no. 4, pp. 704-717, Aug. 2010. [Link]