tutorial

Texts

1. Networks, Crowds and Markets: Reasoning About a Highly Connected World. David Easley and Jon Kleinberg. Cambridge University Press.
2. Networks: An Introduction. Mark Newman. Oxford University Press. 2010.
3. The Craft of Research (Third Edition). Wayne Booth, Gregory Colomb, and Joseph Williams. University Of Chicago Press. 2008.

Other Course Materials

• Course overview
• Bibliography
• Reading Questions

Assignments

• Nothing yet.

Schedule

• For Thursday Sept 8, read the introductory chapters of Newman and Easley & Kleinberg.

Course Notes from 2008

• Lecture 1: Introductory examples and questions. [One slide per page] [Four slides per page]
• Lecture 2: Basic network properties. [One slide per page] [Four slides per page]
• Lecture 3: Erdos-Renyi model. [One slide per page] [Four slides per page]
• Lecture 4: Watts-Strogatz model. [One slide per page] [Four slides per page]
• Lecture 5: Introduction to Preferential Attachment. [One slide per page] [Four slides per page]
• Lectures 6-8: Probabilities and Stochastic Processes, Power Laws and Long Tails . [One slide per page] [Four slides per page] (Updated 7 Oct. 2008.)
• Lectures 9-11: Community Discovery and Higher-Order Structures [One slide per page] [Four slides per page] (Updated 28 Oct. 2008.)

More information about the 2008 course can be found on betweenness, the class blog.

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Network structures are ubiquitous in the world around us: communication networks, transportation networks, networks of friends and acquaintances, and biological networks, to name just a few. In this tutorial students will learn about the mathematical similarities and abstractions that under-lie these examples. Additional examples may be drawn from molecular biology (gene regulation and protein interaction networks), economics (trading networks, relations among firms, and strategic interactions on networks), computer science (computer networks and the world wide web), and ecology (food webs), depending on students' interests. The last decade has seen an explosion of work in the theory and applications of networks to an enormously wide range of problems. Students who successfully complete this tutorial will: gain a broad introduction to recent work in this field; understand the strengths and weaknesses of network approaches; and be able to apply networks and network analysis in a variety of settings. In addition to learning about networks, a central goal of this tutorial is for students to gain skills necessary for research in the mathematical, natural, and social sciences. This includes conceptualizing and framing a research question, conducing a literature review, presenting results in a professional-style research talk, and writing up results in a style appropriate for publication.

In the first part of the course, we will focus on empirical descriptions of network structure, including algorithms for discovering communities or clusters. We will then turn our attention to dynamics of networks: how do networks form and grow, and how are these growth rules related to global structure? Finally, as time permits we will consider dynamics of processes that occur on networks.

Evaluation will be based on participation in seminar-style class meetings, several short problem sets, and a project on a topic of the student's choosing.

Advanced. *QR*

Pre-requisites: Calculus II, Statistics. Linear Algebra and some programming experience is recommended.

Enrollment by permission of instructor.