691T: Computational Social Network Analysis
Fall 2003: Schedule of Readings

September | October | November | December

Course Page

September 12: Introduction

Watts, D. and S. Strogatz (1998). Collective dynamics of 'small-world' networks. Nature 393:440-42. online. (passed out and read in class)

September 19: (No class)

September 26: Overview, history and introduction to networks

Watt, D. (2003). Six Degrees: The Science of a Connected Age. Norton. online purchase. (first half).

Hayes, B. (2000). Graph theory in practice: Parts I & II. American Scientist. January-February/March-April. online (pt. 1) online (pt. 2)

Kleinberg, J., S.R. Kumar, P. Raghavan, S. Rajagopalan, A. Tomkins (1999). The Web as a graph: Measurements, models and methods. Invited survey at the International Conference on Combinatorics and Computing. online

Additional:

Kleinberg, J., and S. Lawrence (2001). The structure of the Web. Science 294: 1849. online

October 3: Power laws and hierarchical structure

Faloutsos, Michalis, Petros Faloutsos and Christos Faloutsos (1999). On power-law relationships of the Internet. Topology, SIGCOMM. online

Barabasi, A.-L. and Reka Albert (1999). Emergence of scaling in random networks. Science 286: 509-512. online

Chen, Q., H. Chang, R. Govindan, S. Jamin, S. Shenker, and W. Willinger (2002). The Origin of Power Laws in Internet Topologies Revisited. In Proceedings of IEEE INFOCOM '02. online

Optional:

Jeong, G., Kim, K. Classification of Scale Free Networks, Proc. Natl. Acad. Sci. USA 99:12583-12588, 2002 online

Ravasz, Erzsebet, and Albert-Laszlo Barabasi (in press). Hierarchical organization in complex networks. Physical Review E. online

Additional:

Anukool Lakhina, John Byers, Mark Crovella, and Peng Xie (2003). Sampling biases in IP topology measurements. Proceedings of IEEE Infocom 2003. online

Bu, T. and D. Towsley (2002). On distinguishing between Internet power law topology generators. In Proceedings of INFOCOM. online

Newman, M. E. J., D. J. Watts, and S. H. Strogatz (2002). Random graph models of social networks. Proceedings of the National Academy of Sciences USA, 99, 2566-2572. online

October 10: General network structure and dynamics

Strogatz, S. (2001). Exploring complex networks. Nature 410: 268-276. online

Barabasi, A.L., H. Jeong, Z. Neda, E. Ravasz, A. Schubert, and T. Vicsek (2002). Evolution of the social network of scientific collaborations. Physica A 311: 590-614. online

Albert, R. H. Jeong and A. Barabasi (2000). Error and attack tolerance of complex networks. Nature 406. online

Optional:

Newman, M. Who is the best connected scientist? A study of scientific coauthorship networks. Phys. Rev. E 64 (2001). online.

October 17: Algorithms (descriptive)

Tyler, J., D. Wilkinson, B. Huberman (2003). Email as spectroscopy: Automated discovery of community structure within organizations. online

Christopher R. Palmer, Phillip B. Gibbons and Christos Faloutsos, ANF: A Fast and Scalable Tool for Data Mining in Massive Graphs, The eighth ACM SIGKDD Internal Conference on Knowlege Discovery and Data Mining, 2002. online

Seary, A, W. Richards. (2003). Spectral Methods for Analyzing and Visualizing Networks: An Introduction. In Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers. R. Breiger, K. Carley, and P. Pattison, Editors. Committee on Human Factors, National Research Council. Washington, DC: National Academy Press. online

Optional:

Mihail, M., C. Gkantsidis, and E. Zegura. (2003). Spectral analysis of Internet topologies. In Proceedings of Infocom 2003. online.

White, S., P. Smyth. (2003). Algorithms for Discovering Relative Importance In Graphs. Proceedings of Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. online.

October 24: Algorithms (search and spread of influence)

Kleinberg, J (2000). The small world phenomenon: An algorithmic perspective. In Proceedings of the 32nd ACM Symposium on Theory of Computing. online

Watts, D. J., P. S. Dodds, and M. E. J. Newman (2002). Identity and search in social networks. Science 296: 1302-1305. online

Domingos, P. and M. Richardson (2001). Mining the network value of customers. Proceedings of the Seventh International Conference on Knowledge Discovery and Data Mining. San Francisco, CA: ACM Press. pp. 57-66. online

Kempe, D., J. Kleinberg, E. Tardos (2003). Maximizing the spread of influence through a social network. Proc. 9th ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining. online

Optional:

Watts, D. J (2002). A simple model of global cascades on random networks. Proceedings of the National Academy of Sciences USA 99, 5766-5771. online

October 31: Models I

Anderson, C. S. Wasserman and B. Crouch (1999). A p* primer: Logit models for social networks. Social Networks 21:37-66.

Handcock, M. (2002). Degeneracy and inference for social network models. online

Additional:

Wasserman, S. and P. Pattison (1996). Logit models and logistic regression for social networks: An introduction to Markov graphs and p*. Psychometrika 61:401-425.

November 7: Models II

Hoff, P. (2003). Random effects models for network data. In Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers. R. Breiger, K. Carley, and P. Pattison, Editors. Comittee on Human Factors, National Research Council. Washington, DC: National Academy Press. online

Strauss, D. and M. Ikeda (1990). Pseduolikelihood estimation for social networks. Journal of the ASA 85:204-212.

Snijders, T.A.B. (2002). Markov Chain Monte Carlo Estimation of Exponential Random Graph Models. Journal of Social Structure vol. 3 no. 2 online

November 14: Models III

Nowicki, Krzysztof, and Snijders, Tom A.B, Estimation and prediction for stochastic blockstructures. Journal of the American Statistical Association, 96 (2001), 1077-1087. online

Borgatti, S. P., & Everett, M. G. 1989. The class of all regular equivalences: Algebraic structure and computation. Social Networks, 11: 65-88.online

November 21: Applications

[TBA]

Watt, D. (2003). Six Degrees: The Science of a Connected Age. Norton. online purchase. (second half).

November 28: (No class)

December 5: Project presentations (held in room 142 Computer Science Building)

December 12: Project presentations (held in room 142 Computer Science Building)

December 16: (No class)