The course meets MW 9-10:25am in Annenberg 105.
We will often have "makeup'' and "bonus'' lectures on Friday 9-10:25am in Annenberg 105.
Note: The first lecture is Jan 6. There will not be a lecture on Jan 4.
The course will be managed using Piazza. All communication will happen and all materials will be posted through http://piazza.com/caltech/winter2017/cmscsee144. Email Adam if you have problems enrolling yourself at the site.
Social networks, the web, and the internet are an essential parts of our lives and we all depend on them every day, but do you really know what makes them work? This course studies the "big" ideas behind our networked lives. Things like, what do networks actually look like (and why do they all look so similar)? How do search engines work? Why to memes spread the way they do? How does web advertising work? For all these questions and more, the course will provide a mixture of both mathematical analysis and hands-on labs.This course can be combined with CS/EE 145 and CS 142 or CS/EE 143 to satisfy the project requirement for CS undergraduate degree, but CS/EE 143 and CS 141a are not required prerequisites. The course assumes students are comfortable with graph theory, probability, and basic programming.
Adam Wierman, email@example.com
Networks, Crowds, and Markets: Reasoning About a Highly Connected World,
by David Easley and Jon Kleinberg.
This book is quite reasonably priced, but there is also a pre-publication pdf available here. I think the book is excellent, so I highly recommend you buy a copy and read it cover-to-cover. We will not be going through it in order, but I will point to the relevant parts of the book for each lecture. Additionally, I will post course notes and supplementary papers on this site at the end of each class.
This is only a tentative outline of the topics we will discuss and will likely change as the term goes by. But, I put it up to give you an idea of where we're going. The course is basically organized as a collection of topics that I think are important and interesting and which provide a modern perspective on our networked lives.
Introduction to the class
Part I: Understanding Network structure
Part II. The impact of network structure
Part III. Network economics
Homeworks will be assigned every 1-2 weeks. Many of the problems will be challenging, so please start immediately and please come to office hours to discuss the problems! The assignments will represent a mixture of theory (proofs) and practice (coding). I assume that you can code and use Matlab/Mathematica and Python.
We have several mini-projects during the course: one related to pagerank (rankmaniac), one related to epidemics/pandemics (pandemaniac), and one related to computational advertising (clickmaniac). The projects change year to year, but the winners are immortalized here:
the rankmaniacs were: Hikmet Yildiz, Fariborz Salehi, Oguzhan Teke
the pandemaniacs were: Hikmet Yildiz, Fariborz Salehi, Oguzhan Teke
the clickmaniacs were: Jaden Geller, Mimi Jiao, Alex Ryan
the rankmaniacs were: Cody Han, Lu Li, Linqi Guo
the pandemaniacs were: Brad Chattergoon, Michael Malek, Sharjeel Aziz, Ronnel Boettcher
the clickmaniacs were: Daniel Wang, Jerry Zhang, Eric Pelz
the rankmaniacs were: Ryan Batterman, Joseph Choi, and Kevin Yang
the pandemaniacs were: Kun Huang, Shupin Mao, Danlei Yang
the clickmaniacs were: Alex Cioc, David Foor
the rankmaniacs were: Benjamin Cosman, Matthew Dughi, Suzannah Fraker, Yuchen Lin
the clickmaniacs were: Eduardo Gonzalez, Li Gu, Josie Kishi, Jesse Salomon
the rankmaniacs were: Michael Burd, Michael Hirshleifer, Ramya Vinayak
the clickmaniacs were: Kevin Lo, Nathan Watson, Mikhail Sushkov, Stasja Stanisic
the rankmaniacs were: Giordon Stark, Jamie Jackson
the clickmaniacs were: Dai Wei, Doris Xin, Wenqi Yao
the rankmaniacs were: Daniel Erenrich, Chis Kennelly, Andy Matuschak
the clickmaniacs were: Jonathan Krause, Manuel Lagang