• Dino Pedreschi Università di Pisa, Knowledge Discovery and Data Mining Lab pedre [at] di [dot] unipi [dot] it

Over the past decade there has been a growing public fascination with the complex “connectedness” of modern society. This connectedness is found in many contexts: in the rapid growth of the Internet and the Web, in the ease with which global communication now takes place, and in the ability of news and information as well as epidemics and financial crises to spread around the world with surprising speed and intensity. These are phenomena that involve networks and the aggregate behavior of groups of people; they are based on the links that connect us and the ways in which each of our decisions can have subtle consequences for the outcomes of everyone else.

This short course is an introduction to the analysis of complex networks, with a special focus on social networks and the Web - its structure and function, and how it can be exploited to search for information. Drawing on ideas from computing and information science, applied mathematics, economics and sociology, the course describes the emerging field of study that is growing at the interface of all these areas, addressing fundamental questions about how the social, economic, and technological worlds are connected.

1) Graph theory and social networks

• Graphs
• Social, information, biological and technological networks
• Strong and weak ties
• Networks in their surrounding context

2) The World Wide Web

• The structure of the Web
• Link analysis and Web search
• Web mining e sponsored search markets

3) Network dynamics

• Information cascades
• Power laws and rich-get-richer phenomena
• The small-world phenomenon
• Epidemics

• Slides (see Calendar).

• David Easley, Jon Kleinberg: Networks, Crowds, and Markets. http://www.cs.cornell.edu/home/kleinber/networks-book/

Reading:

• M. E. J. Newman: The structure and function of complex networks, SIAM Review, Vol. 45, p. 167-256, 2003. (download pdf)

• A.-L. Barabasi. Linked. PLUME, Penguin Group, 2002.

• Duncan J. Watts. Six Degrees: The Science of a Connected Age. Norton, New York, 2003.

• Anand Rajaraman, Jeffrey D. Ullman, Mining of Massive Datasets. http://infolab.stanford.edu/~ullman/pub/book.pdf