Mark Newman

Mark Newman
Paul Dirac Collegiate Professor of Physics
Department of Physics and Center for the Study of Complex Systems
University of Michigan

External Faculty
Santa Fe Institute

Publications and presentations

Networks: An Introduction

My book Networks: An Introduction was published recently by Oxford University Press. Information about it is here . The Amazon page is also a good place to look for info.

Courses

Physics 411, Computational Physics, Winter 2013
Complex Systems 535, Network Theory, Fall 2012
Physics 411, Computational Physics, Winter 2012
Complex Systems 535, Network Theory, Fall 2011
Physics 411, Computational Physics, Winter 2011
Complex Systems 535, Network Theory, Fall 2010
Physics 390, Introduction to Modern Physics, Winter 2010
Complex Systems 535, Network Theory, Fall 2009
Physics 390, Introduction to Modern Physics, Winter 2008
Complex Systems 511, Theory of Complex Systems, Fall 2007
Physics 406, Statistical and Thermal Physics, Winter 2007
Complex Systems 899, Theory of Complex Systems, Winter 2006
Complex Systems 535, Network Theory, Winter 2005
Physics 406, Statistical and Thermal Physics, Fall 2004
Complex Systems 535, Network Theory, Winter 2004
Physics 406, Statistical and Thermal Physics, Fall 2003
Physics 406, Statistical and Thermal Physics, Fall 2002

Research group

Group members:
- Brian Ball
- Travis Martin
- Maria Riolo
- Xiao Zhang
Former group members:
- Dr Michael Gastner, Imperial College, London
- Professor Michelle Girvan, University of Maryland
- Dr. Gourab Ghoshal, Harvard University
- Dr. Petter Holme, Umeå University
- Dr. Brian Karrer, Facebook Corporation
- Dr Elizabeth Leicht, Oxford University
- Professor Juyong Park, KAIST, Seoul
- Bethany Percha, Stanford University

Research

Our research is on the structure and function of networks, particularly social and information networks, which are studied using a combination of empirical methods, analysis, and computer simulation. Among other things, we have investigated scientific coauthorship networks, citation networks, email networks, friendship networks, epidemiological contact networks, and animal social networks; we've studied fundamental network properties such as degree distributions, centrality measures, assortative mixing, vertex similarity, and community structure, and made analytic or computer models of disease propagation, friendship formation, the spread of computer viruses, the Internet, and network navigation algorithms. A selection of representative publications is given below; a complete publication list is here.

Selected publications:

The structure of scientific collaboration networks, M. E. J. Newman, Proc. Natl. Acad. Sci. USA 98, 404-409 (2001).
Random graphs with arbitrary degree distributions and their applications, M. E. J. Newman, S. H. Strogatz, and D. J. Watts, Phys. Rev. E 64, 026118 (2001).
Assortative mixing in networks, M. E. J. Newman, Phys. Rev. Lett. 89, 208701 (2002).
The structure and function of complex networks, M. E. J. Newman, SIAM Review 45, 167-256 (2003).
Modularity and community structure in networks, M. E. J. Newman, Proc. Natl. Acad. Sci. USA 103, 8577-8582 (2006).
Hierarchical structure and the prediction of missing links in networks, A. Clauset, C. Moore, and M. E. J. Newman, Nature 453, 98–101 (2008).
Power-law distributions in empirical data, Aaron Clauset, Cosma Rohilla Shalizi, and M. E. J. Newman, SIAM Review 51, 661-703 (2009).
Random graphs with clustering, M. E. J. Newman, Phys. Rev. Lett. 103, 058701 (2009).

Other information

With Daniel Dorling and Anna Barford, we have a new book of maps available, The Atlas of the Real World, containing 366 cartograms showing all kinds of different features of the world today. Details here.

Our recent work on density-equalizing map projections appeared on the cover of the Proceedings of the National Academy of Sciences.

If you are looking for maps of the US election results, click here.

Some information on computational physics with the Python programming language is here.
The Worldmapper Project collection of cartograms is here.
A collection of network data sets from various sources is here. Data sets include the Zachary karate club and US college football networks that have been widely used as tests for community structure algorithms, and a number of coauthorship networks.
Information and code for the degree-corrected block model is here.
Information and code for the link prediction algorithm is here.
Information and code for maximum likelihood fits to power-law distributions is here.
Information and code for the fast community structure algorithm is here.
Information and code for the cartogram algorithm is here.
Information and code for the percolation algorithm is here.
If you are looking for the summary tables of collaboration indices from my 2001 paper on coauthorships, they are here.

Contact details:

I am not the only professor called Mark Newman at the University of Michigan. I'm the physicist who works on networks. There is another Mark Newman in the UM School of Information who works on human-computer interaction.

Here are my contact details:

Department of Physics
University of Michigan
Randall Laboratory
450 Church Street
Ann Arbor, MI 48109-1040

Phone: (734) 764-4437
Fax: (734) 764-6843
Email: mejn@umich.edu

Last modified: April 15, 2013

Mark Newman, Department of Physics, University of Michigan