Network Modeling (Winter 2014/2015)
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Social network analysis, i.e., the joint analysis of actors and relations among them, rapidly gains importance in many scientific and commercial applications. Examples range from studies of organizational and communication networks over to the analysis of Web-based user interaction. Statistical approaches in social network analysis are applied to model, estimate, and predict social interaction and behavior based on empirical data. In this course you will learn mathematical and methodological foundations for modeling social networks. In the first part we treat models for time-independent networks and in the second part we model the evolution of networks over time. This course is part of a set of three related lectures offered by the Algorithmics group: Network Analysis, Network Dynamics, and Network Modeling. Note that these courses can be taken independently of each other and in any order. Prerequisites Good knowledge of basic mathematical concepts, as well as strong mathematical soft skills, i.e., the ability to understand and work with mathematical definitions, theorems, and proofs. |
Schedule
| Lecture (Viviana Amati & Jürgen Lerner) | Wed 13:30-15:00 in P 603 |
| Tutorial | Wed 17:00-18:30 in P 603 |
| Exams (oral) | 11 February and 15 April 2015 (by individual appointment) |
Exercises
Most documents are only locally accessible - see possibilities for remote access.| no. | online | due | tutorial | download |
|---|---|---|---|---|
| 0 | 22 October 2014 | - | 29 October 2014 | Sheet 0 |
| 1 | 29 October 2014 | 03 November 2014 | 05 November 2014 | Sheet 1 |
| 2 | 05 November 2014 | 11 November 2014 | 12 November 2014 | Sheet 2 |
| 3 | 12 November 2014 | 18 November 2014 | 19 November 2014 | Sheet 3 |
| 4 | 19 November 2014 | 25 November 2014 | 26 November 2014 | Sheet 4 |
| 5 | 26 November 2014 | 02 December 2014 | 03 December 2014 | Sheet 5 |
| 6 | 03 December 2014 | 09 December 2014 | 10 December 2014 | Sheet 6 |
| 7 | 10 December 2014 | 16 December 2014 | 17 December 2014 | Sheet 7 |
| 8 | 17 December 2014 | 07 January 2015 | 07 January 2015 | Sheet 8 |
| 9 | 07 January 2015 | 13 January 2015 | 14 January 2015 | Sheet 9 |
| 10 | 14 January 2015 | 20 January 2015 | 21 January 2015 | Sheet 10 |
| 11 | 21 January 2015 | 27 January 2015 | 28 January 2015 | Sheet 11 |
| 12 | 28 January 2015 | 03 February 2015 | 04 February 2015 | Sheet 12 |
Solutions of selected exercises
- Solution for Assignment 1, Task 3.
- Slides related to Assignment 8.
Material
Most documents are only locally accessible - see possibilities for remote access.Data
- Data can be downloaded here
Slides
- Static Network Models last updated: December 16, 2014.
- Stochastic actor-oriented models last updated: February 04, 2015.
- Temporal Exponential Random Graph Models last updated: December 16, 2014.
Software
Literature
Lecture topics
- Batagelj, Brandes: Efficient Generation of Large Random Networks. Physical Review E 71, 036113, 2005.
- Lusher, Koskinen, and Robins: Exponential Random Graph Models for Social Networks. Cambridge Univ. Press, 2013.
- Robins, Pattison, Kalish, and Lusher: An introduction to exponential random graph (p*) models for social networks. Social Networks 29(2):173-191, 2007. (local copy)
- Snijders, van de Bunt, and Steglich: Introduction to stochastic actor-based models for network dynamics. Social Networks 32(1):44-60, 2010. (local copy)
- Snijders, Koskinen, and Schweinberger: Maximum Likelihood Estimation for Social Network Dynamics. Annals of Applied Statistics 4(2):567-588, 2010. (local copy)
- Steglich, Snijders, and Pearson: Dynamic Networks and Behavior: Separating Selection from Influence. Sociological Methodology 40(1):329-393, 2010. (local copy)
- Hanneke, Fu, and Xing: Discrete temporal models of social networks. Electronic Journal of Statistics 4:585-605, 2010. (local copy)
- Krivitsky and Handcock: A separable model for dynamic networks. Journal of the Royal Statistical Society: Series B 76(1):29-46, 2014. (local copy)
- Hunter and Handcock: Inference in Curved Exponential Family Models for Networks. Journal of Computational and Graphical Statistics 15(3):565-583, 2006. (local copy)
- Hunter: Curved exponential family models for social networks. Social Networks 29(2):216-230, 2007. (local copy)
- Morris, Handcock, and Hunter: Specification of Exponential-Family Random Graph Models: Terms and Computational Aspects. Journal of Statistical Software 24(4), 2008. (local copy)
Background and further reading
- Lazer, Pentland, Adamic, Aral, Barabási, Brewer, Christakis, Contractor, Fowler, Gutmann, Jebara, King, Macy, Roy, Van Alstyne: Computational Social Science. Science 323(5915), 721-723, 2009.
- Marina Hennig, Ulrik Brandes, Jürgen Pfeffer and Ines Mergel: Studying Social Networks. Campus-Verlag, 2012.
- Brandes, Erlebach (Eds.): Network Analysis. LNCS 3418, Springer, 2005.
- Wasserman, Faust: Social Network Analysis. Cambridge Univ. Press, 1994.