====== Syllabus ======


===== Week 1, 8/26, Introduction to Social Computing =====
==== Notes & Assignments ====
  - Read Chapter 1, "//Introduction: Hacking on Twitter Data//" in M. A. Russell, //Mining the Social Web: Analyzing Data from Facebook//, Twitter, LinkedIn, and Other Social Media Sites, 1st ed. O’Reilly Media, 2011.
  - Read Chapter 4, "//Twitter: Friends, Followers, and Setwise Operations//" in M. A. Russell, //Mining the Social Web: Analyzing Data from Facebook//, Twitter, LinkedIn, and Other Social Media Sites, 1st ed. O’Reilly Media, 2011.
  - Read Chapter 5, "//Twitter: The Tweet, the Whole Twee, and Nothing but the Tweet//" in M. A. Russell, //Mining the Social Web: Analyzing Data from Facebook//, Twitter, LinkedIn, and Other Social Media Sites, 1st ed. O’Reilly Media, 2011.
  - Read Chapters 3, 4, and 5 in [[http://www.analytictech.com/networks.pdf|Introduction to Social Network Methods]].
  - {{:info290-02-sna.pdf| Introductory Notes from class}}

==== Tutorials ====
  * [[http://www.acm.uiuc.edu/sigunix/workshops/crashpython/crashpython.pdf|A Crash Course on Python]]

==== Resources ====
  * [[http://www.python.org/getit/releases/2.6.6/|Python 2.6.6]]
  * [[https://bitbucket.org/pdubroy/pip/raw/tip/getpip.py|getpip.py]]
  * [[http://dubroy.com/blog/so-you-want-to-install-a-python-package/|Installing a Python package]]
  * [[https://dev.twitter.com/docs|Twitter API]]
  * [[https://dev.twitter.com/docs/twitter-libraries#python|Twitter libraries in Python]]
  * [[https://github.com/ptwobrussell/Mining-the-Social-Web|Github of examples]]
  * [[http://www.graphviz.org/|Graphviz]]


===== Week 2, 9/2/11, Social Network Theory =====
==== Notes & Assignments ====

  - Read Chapter 1, "//Introduction//" in D. J. Cook and L. B. Holder, //Mining Graph Data//, 1st ed. Wiley-Interscience, 2006.
  - Read Chapter 2, "//Graph Matching--Exact and Error-Tolerant Methods and The Automatic Learning of Edit Costs//" in D. J. Cook and L. B. Holder, //Mining Graph Data//, 1st ed. Wiley-Interscience, 2006.
  - Read Chapter 6 and 7 in [[http://www.analytictech.com/networks.pdf|Introduction to Social Network Methods]].
==== Tutorials ====
Please install the following before the class on 9/2/2011.

  * [[http://www.r-project.org/]]
    * Comes with a command line editor
  * R Editor: [[http://sciviews.org/_rgui/]]
    * Better editor than the default R's command line editor
  * JGR: [[http://www.rforge.net/JGR/]]
    * Has libraries for creating beautiful graphs (we will explore this in the second R tutorial)

==== Resources ====
  - [[http://www.analytictech.com/networks.pdf|Introduction to Social Network Methods]]
  - {{:info290-02-tutorial-r-part1.pptx|R-ppt (part1)}}

===== Week 3. 9/9/11, Graph Theory and Mining =====
==== Notes & Assignments ====
  - Read Chapter 4, "//Graph Patterns and the R-Mat Generator//" in D. J. Cook and L. B. Holder, //Mining Graph Data//, 1st ed. Wiley-Interscience, 2006.
  - Read Chapter 17, "//Social Network Analysis//" in D. J. Cook and L. B. Holder, //Mining Graph Data//, 1st ed. Wiley-Interscience, 2006.
  - Read Chapter 8, 9, and 10 in [[http://www.analytictech.com/networks.pdf|Introduction to Social Network Methods]].
  - Read Mary McGlohon, Jure Leskovec, Christos Faloutsos, Matthew Hurst and Natalie Glance, [[http://www.cs.cmu.edu/%7Echristos/PUBLICATIONS/icwsm07-blogs.pdf|Finding patterns in blog shapes and blog evolution]], Int. Conf. on Weblogs and Social Media Boulder, CO, USA, March 26-28, 2007.
  - Read Deepayan Chakrabarti and Christos Faloutsos, [[http://www.cs.cmu.edu/~deepay/mywww/papers/csur06.pdf|Graph mining: Laws, generators, and algorithms]], ACM Computing Surveys (CSUR) 38,1, Article No. 2 (2006).
  - Read Andrei Broder, Ravi Kumar, Farzin Maghoul, Prabhakar Raghavan, Sridhar Ra- jagopalan, Raymie Stata, Andrew Tomkins, and Janet Wiener. [[http://www.cis.upenn.edu/~mkearns/teaching/NetworkedLife/broder.pdf|Graph structure in the Web]]. In Proc. 9th International World Wide Web Conference, pages 309–320, 2000.
  - Read M. E. J. Newman, “[[http://physwww.mcmaster.ca/~higgsp/756/NewmanSIAMreview.pdf|The Structure and Function of Complex Networks]],” SIAM Review, vol. 45, no. 2, p. 167, 2003.
  - Read Chapter 1 in Charu C. Aggarwal and Haixun Wang, [[http://charuaggarwal.net/gtoc.pdf|Managing and Mining Graph Data]], 1st ed. Kluwer Academic Publishers.

==== Tutorials ====
==== Resources ====
===== Week 4, 9/16/11, Link Analysis, Community Detection =====
===== Week 5, 9/23/11, Project Discussion =====
===== Week 6, 9/30/11, Learning and Learning to Rank =====
==== Resources ====
  * [[http://www.amazon.com/Pattern-Recognition-Learning-Information-Statistics/dp/0387310738|Recommended book to dig deeper on machine learning]]
===== Week 7, 10/7/11, Sentiment Analysis and Opinion Mining =====
==== Notes & Assignments ====
==== Tutorials ====
==== Resources ====
  * [[http://www.cs.cornell.edu/home/llee/opinion-mining-sentiment-analysis-survey.html|Bo-Pang: Sentiment analysis survey.]]
===== Week 8, 10/14/11, Recommender Systems =====
==== Notes & Assignments ====
==== Tutorials ====
==== Resources ====
===== Week 9, 10/21/11, Social Media in Education =====
===== Week 10, 10/28/11, Human Computation/Crowdsourcing =====
==== Notes & Assignments ====
==== Tutorials ====
==== Resources ====
===== Week 11, 11/4/11, FaceBook =====
===== Week 12, 11/11/11, Public Holiday =====
===== Week 13, 11/18/11, Q&A, cQA, and DeepQA =====
==== Notes & Assignments ====
==== Tutorials ====
==== Resources ====
===== Week 14, 11/25/11, Public Holiday =====
===== Week 15, 12/2/11, Social Monetization =====
===== Week 16, 12/9/11, Wrap-up/Presentations =====

====== Data Sources ======

  * [[http://snap.stanford.edu/data/|SNAP]]

====== R ======
  * [[http://www.r-project.org/|The R Project for Statistical Computing]]
  * [[http://www.statmethods.net/index.html|Quick-R]]
  * [[http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/installation-notes.html|R Commander Installation]]