Room: 2218 School of Education Building

Instructor: Mark Newman

Office: 322 West Hall

Office hours: Tuesday 1:30-3:30pm

Email: mejn@umich.edu

This course will introduce and develop the mathematical theory of networks, particularly social and technological networks, with applications to network-driven phenomena in the Internet, search engines, network resilience, epidemiology, and many other areas.

Topics to be covered will include experimental studies of social networks, the world wide web, information and biological networks; methods and computer algorithms for the analysis and interpretation of network data; graph theory; models of networks including random graphs and preferential attachment models; spectral methods and random matrix theory; maximum likelihood methods; percolation theory; network search.

Students should have studied calculus and linear algebra before taking the course, and should in particular be comfortable with the solution of linear differential equations and with the calculation and properties of eigenvalues and eigenvectors of matrices. In addition, a moderate portion of the course, perhaps two weeks, will deal with computer methods for analyzing networks. Some experience with computer programming will be a great help in understanding this part of the course.

There will be weekly graded problem sets, consisting of questions on both theory and applications. There will be three midterm exams but no final. The midterms will be in class at the usual time on September 29, November 3, and December 10.

There will be reading assignments for each lecture. The assignments are listed on the schedule below. Students are expected to do the reading for each lecture in a timely manner.

**Textbook (required):** *Networks: An Introduction*, M. E. J. Newman, Oxford University
Press, Oxford (2010)

In addition to this required text, a list of other useful books is given
below. **None of them is required**, but you may find them useful if
you want a second opinion or more detail on certain topics.

**General books on networks:**

- Reuven Cohen and Shlomo Havlin,
*Complex Networks: Structure, Robustness and Function*, Cambridge University Press, Cambridge (2010). Quite a short book, but it covers most of the topics of the course, at least to some extent, and some others that are not in the book by Newman. - S. N. Dorogovtsev,
*Lectures on Complex Networks*, Oxford University Press, Oxford (2010). Very short – genuinely a set of lecture notes, rather than a full text.

**Books on specific networky topics:**

- R. K. Ahuja, T. L. Magnanti, and J. B. Orlin,
*Network Flows: Theory, Algorithms, and Applications*, Prentice Hall, Upper Saddle River, NJ (1993) - A. Barrat, M. Barthelemy, and A. Vespignani,
*Dynamical Processes on Complex Networks*, Cambridge University Press, Cambridge (2008) - G. Caldarelli,
*Scale-Free Networks: Complex Webs in Nature and Technology*, Oxford University Press, Oxford (2007) - S. N. Dorogovtsev and J. F. F. Mendes,
*Evolution of Networks*, Oxford University Press, Oxford (2003) - A. Degenne and M. Forse,
*Introducing Social Networks*, Sage, London (1999) - D. Easley and J. Kleinberg,
*Networks, Crowds, and Markets*, Cambridge University Press, Cambridge (2010) - F. Harary,
*Graph Theory*, Perseus, Cambridge, MA (1995) - M. O. Jackson,
*Social and Economic Networks*, Princeton University Press, Princeton, NJ (2008) - C. D. Meyer,
*Matrix Analysis and Applied Linear Algebra*, SIAM, Philadelphia, PA (2000) - M. E. J. Newman, A.-L. Barabasi, and D. J. Watts,
*The Structure and Dynamics of Networks*, Princeton University Press (2006) - R. Pastor-Satorras and A. Vespignani,
*Evolution and Structure of the Internet*, Cambridge University Press, Cambridge (2007) - J. Scott,
*Social Network Analysis: A Handbook*, 2nd edition, Sage, London (2000) - S. Wasserman and K. Faust,
*Social Network Analysis*, Cambridge University Press, Cambridge (1994) - D. J. Watts,
*Six Degrees: The Science of a Connected Age*, Norton, New York (2003) - D. B. West,
*Introduction to Graph Theory*, Prentice Hall, Upper Saddle River, NJ (1996) - R. J. Wilson,
*Introduction to Graph Theory*, 4th edition, Addison-Wesley, Reading, MA (1997)

- Homework 1 - Mathematics of networks
- Homework 2 - Measures and metrics
- Homework 3 - Random graphs
- Homework 4 - The configuration model
- Homework 5 - Growing networks
- Homework 6 - Community structure and inference
- Homework 7 - EM algorithm and modularity

Date | Topic | Reading | On-line resources | Notes |
---|---|---|---|---|

Wednesday, Sept. 3 | Introduction | Chapter 1 | Info sheet | |

Monday, Sept. 8 | Classes of networks | Chapters 2 through 5 | ||

Wednesday, Sept. 10 | Basic mathematics of networks | 6.1-6.11 | Homework 1, Data set | Homework 1 handed out |

Monday, Sept. 15 | Centrality, transitivity, assortativity | Chapter 7 | ||

Wednesday, Sept. 17 | Network structure and degree distributions | 8.1-8.6 | Homework 2, Data set | Homework 1 due, Homework 2 handed out |

Monday, Sept. 22 | Computer algorithms 1 | Chapter 9 | ||

Wednesday, Sept. 24 | Computer algorithms 2 | 10.1-10.4 | Homework 2 due, no new homework this week | |

Monday, Sept. 29 | Midterm 1 | In class, usual time and place | ||

Wednesday, Oct. 1 | Random graphs 1 | 12.1-12.5 | Homework 3 | Homework 3 handed out, due Oct. 15 |

Monday, Oct. 6 | No class | |||

Wednesday, Oct. 8 | Random graphs 2 | 12.6-12.8 | ||

Monday, Oct. 13 | No class | Fall Break | ||

Wednesday, Oct. 15 | Configuration models 1 | 13.1-13.4 | Homework 4 | Homework 3 due, Homework 4 handed out |

Monday, Oct. 20 | Configuration models 2 | 13.5-13.8 | ||

Wednesday, Oct. 22 | Configuration models 3 | 13.9-13.11 | Homework 5 | Homework 4 due, Homework 5 handed out |

Monday, Oct. 27 | Generative models 1 | 14.1-14.2 | ||

Wednesday, Oct. 29 | Generative models 2 | 14.3-14.5 | Homework 5 due, no new homework this week | |

Monday, Nov. 3 | Midterm 2 | In class, usual time and place | ||

Wednesday, Nov. 5 | Partitioning and community structure | 11.2-11.8 | Homework 6 | Homework 6 handed out |

Monday, Nov. 10 | Maximum likelihood methods | |||

Wednesday, Nov. 12 | The expectation-maximization method | Homework 6 due, no new homework this week | ||

Monday, Nov. 17 | Spectral methods | |||

Wednesday, Nov. 19 | Random matrix theory 1 | Homework 7, Data set | Homework 7 handed out, due Dec. 3 | |

Monday, Nov. 24 | Random matrix theory 2 | |||

Wednesday, Nov. 26 | No class | Thanksgiving | ||

Monday, Dec. 1 | Percolation | Chapter 16 | ||

Wednesday, Dec. 3 | Epidemics on networks | 17.1-17.8 | Homework 7 due | |

Monday, Dec. 8 | Network search | Chapter 19 | ||

Wednesday, Dec. 10 | Midterm 3 | In class, usual time and place |

Mark Newman