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====== CSCI5733 Social Computing ======
 [ [[:teaching:csci5733:discussions:2013|Discussion Forum]] | [[:teaching:csci5733:blogs:2013|Blogs]] ]
==== Breaking News ====

  * <hi #ffff00>**September 2, 2013**.</hi> The new semester begins.

==== Extra Credit Assignments ====

===== 20013-14 Term 1 =====


|  ^  Lecture I  ^  Lecture II  ^  Tutorial I  ^  Tutorial II  ^
^ Time    |  T2-4, 9:30 am - 12:30 pm  |    |  T9, 4:30 pm - 5:30 pm  |   |
^ Venue    |  NAH 8  |   |   LSK 308   |     |

<html><font color="red"> <b>The Golden Rule of CSCI5733: </b></font></html> No member of the CSCI5733 community shall take unfair advantage of any other member of the CSCI5733 community.

====== Course Description ======

This course introduces fundamental as well as applied computational techniques for collaborative and collective intelligence of group behaviours on the Internet. The course topics include, but are not limited to: web intelligence, web data mining, knowledge discovery on the web, web analytics, web information retrieval, learning to rank, ranking algorithms, relevance feedback, collaborative filtering, recommender systems, human/social computation, social games, opinion mining, sentiment analysis, models and theories about social networks, large graph and link-based algorithms, social marketing, monetization of the web, security/privacy issues related to web intelligence and social computing, etc.

===== Learning Objectives =====

===== Learning Outcomes =====


===== Learning Activities =====
  - Lectures
  - Tutorials
  - Web resources
  - Videos
  - Quizzes
  - Examinations
====== Personnel ======

| ^  Lecturer  ^  Tutor  ^ Tutor ^
^ Name |  [[:home|Irwin King]]  |  Baichuan Li  | Yuanyuan Man  |
^ Email |  king AT cse.cuhk.edu.hk  |  bcli AT cse.cuhk.edu.hk  |    |
^ Office   |  Rm 908  |   |   |
^ Telephone   |   3943 8398   |  | |
^ Office Hour(s)   | * M8, Monday 3:30 pm - 4:30 pm\\ \\ * T8, Tuesday 3:30 pm - 4:30 pm  |  | |

Note: This class will be taught in<html> <font color="red">English</font></html>. Homework assignments and examinations will be conducted in English.

====== Syllabus ======
The pdf files are created in Acrobat 6.0. Please obtain the correct version of the [[http://www.adobe.com/prodindex/acrobat/readstep.html#reader | Acrobat Reader]] from Adobe.

^  Week  ^  Date  ^  Topics  ^  Tutorials  ^  Homework & Events  ^  Resources   ^   
|  1  |   |   | | |  |
|  2  |   |   | | |  |
|  3  |   |   | | |  |
|  4  |   |   | | |  |
|  5  |   |   | | |  |
|  6  |   |   | | |  |
|  7  |   |   | | |  |
|  8  |   |   | | |  |
|  9  |   |   | | |  |
|  10  |   |   | | |  |
|  11  |   |   | | |  |
|  12  |   |   | | |  |

  * Web 2.0
    * Ajax, CSS, 
  * Social Media
    * blogs, microblogs, wikis, mashup, 

====== Class Project ======
===== Class Project Presentation Schedule =====
  * TBA

===== Class Project Presentation Requirements=====

====== Examination Matters ======


===== Examination Schedule =====
|              ^        Time           ^        Venue          ^    Notes    ^
^    Midterm Examination\\ TBA    |    TBA  |   TBA   |    TBA    |
^    Midterm Examination\\ TBA    |    TBA   |   TBA   |    TBA    |
^    Final Examination    |   TBA | TBA | TBA   |


  * [[http://rgsntl.rgs.cuhk.edu.hk/rws_prd_life/main1.asp|CUHK Registration and Examination]]



===== Written Midterm Matters =====
  - The midterm will test your knowledge of the materials.
  - Answer all questions using the answer booklet.  There will be more available at the venue if needed.
  - Write legibly.  Anything we cannot decipher will be considered incorrect.
  - One A4-sized cheat-sheet page.

====== Grade Assessment Scheme ======
^  Homework\\ Assignments  ^  Project Report  ^  Project Presentation  ^  Final Examination  ^
|  TBA  |  TBA  |  TBA  |  TBA  |

  -Assignments (TBA) 
    -Written assignments
    -Optional quizzes
  -Midterm Examination (TBA) 
  - Project (TBA)
    - Report (TBA)
    - Presentations (TBA)
  -Extra Credit (There is no penalty for not doing the extra credit problems. Extra credit will only help you in borderline cases.)

====== Required Background ======
  - Pre-requisites
    -- CSC 1110 or 1130 or its equivalent. (Not for students who have taken CSC 2520). 
====== Reference Books ======


====== FAQ ======

  - **Q: What is departmental guideline for plagiarism?**\\ A: If a student is found plagiarizing, his/her case will be reported to the Department Discipline Committee. If the case is proven after deliberation, the student will automatically fail the course in which he/she committed plagiarism. The definition of plagiarism includes copying of the whole or parts of written assignments, programming exercises, reports, quiz papers, mid-term examinations. The penalty will apply to both the one who copies the work and the one whose work is being copied, unless the latter can prove his/her work has been copied unwittingly. Furthermore, inclusion of others' works or results without citation in assignments and reports is also regarded as plagiarism with similar penalty to the offender. A student caught plagiarizing during tests or examinations will be reported to the Faculty Office and appropriate disciplinary authorities for further action, in addition to failing the course.

====== Resources ======

  -[[http://pajek.imfm.si/doku.php|Pajek, a network analysis and visualization program.]]
  -[[http://vlado.fmf.uni-lj.si/pub/networks/data/default.htm|Package for Large Network Analysis]]
  -[[http://www.analytictech.com/downloaduc6.htm|UCINET 6]]
  -[[http://www.analytictech.com/Netdraw/netdraw.htm|Netdraw]]
  -[[http://stat.gamma.rug.nl/stocnet/|StOCNET]]

===== Social Networks-Theory Graph Theory =====
  * http://www.cs.purdue.edu/homes/neville/courses/aaai08-tutorial.html \\
  * http://cs.stanford.edu/people/jure/icml09networks/ \\
  * http://www.ofcom.org.uk/advice/media_literacy/medlitpub/medlitpubrss/socialnetworking/report.pdf \\

===== Graph Mining =====
  * http://www.cs.cmu.edu/~deepay/mywww/papers/csur06.pdf \\
  * http://cs.stanford.edu/people/jure/talks/www08tutorial/ \\
  * http://www.xifengyan.net/tutorial/KDD08_graph_partI.pdf \\
  * http://www.xifengyan.net/tutorial/KDD08_graph_partII.pdf

===== Link Analysis===== 
  * http://analytics.ijs.si/events/Tutorial-TextMiningLinkAnalysis-KDD2007-SanJose-Aug2007/ \\
  * http://www.sigkdd.org/explorations/issues/7-2-2005-12/1-Getoor.pdf \\
  * http://www.ncjrs.gov/pdffiles1/nij/grants/219552.pdf \\
  * http://delab.csd.auth.gr/~dimitris/papers/ENVO07LARskm.pdf

===== Learning to Rank===== 
  * http://www2009.org/pdf/T7A-LEARNING%20TO%20RANK%20TUTORIAL.pdf\\
  * http://radlinski.org/papers/LearningToRank_NESCAI08.pdf\\
  * http://www.aclweb.org/anthology/P/P09/P09-5005.pdf\\
  * http://www.cse.iitb.ac.in/~soumen/doc/www2007/TutorialSlides.pdf

===== Recommender Systems===== 
  * http://en.wikipedia.org/wiki/Recommender_system
  * http://www.deitel.com/ResourceCenters/Web20/RecommenderSystems/RecommenderSystemsTutorialsandWebcasts/tabid/1313/Default.aspx
  * http://www.computer.org/portal/web/csdl/doi/10.1109/TKDE.2005.99
  * http://www.springerlink.com/content/n881136032u8k111/
  * http://www.csd.abdn.ac.uk/~jmasthof/Publications/WPRSIUI07.pdf

===== Q & A =====
  * http://lml.bas.bg/ranlp2005/tutorials/magnini.ppt \\
  * http://tcc.itc.it/research/textec/topics/question-answering/Tut-Prager.ppt \\
  * http://en.wikipedia.org/wiki/Question_answering \\
  * http://trec.nist.gov/pubs/trec9/papers/webclopedia.pdf \\
  * http://domino.watson.ibm.com/library/CyberDig.nsf/papers/D12791EAA13BB952852575A1004A055C/$File/rc24789.pdf \\
  * http://www.umiacs.umd.edu/~jimmylin/publications/Lin_Katz_EACL2003_tutorial.pdf \\
  * http://answers.yahoo.com/ \\
  * http://zhidao.baidu.com/ \\
  * http://wenda.tianya.cn/wenda/ \\
  * http://hk.knowledge.yahoo.com/ \\

===== Human Computation/Social Games  =====
  * http://www.gwap.com/gwap/ \\
  * http://www.cs.cmu.edu/~biglou/ \\

===== Opinion Mining/Sentiment Analysis  =====
  * http://www.cs.uic.edu/~liub/FBS/opinion-mining-sentiment-analysis.pdf \\
  * http://www.cs.cornell.edu/home/llee/omsa/omsa-published.pdf \\
  * http://www.cs.cmu.edu/~wcohen/10-802/sentiment-sep-4.ppt \\

===== Visualization =====
  -[[http://manyeyes.alphaworks.ibm.com/manyeyes/|Many Eyes Visualization]]

===== Programming =====
  -[[http://networkx.lanl.gov/|NetworkX, a Python package for complex networks]]
  -[[http://www.wolfram.com/|Mathematica from Wolfram]]
    -[[http://demonstrations.wolfram.com/|Wolfram Demonstrations]]

===== Midterm Evaluation Sign-up Sheet =====

===== Final Project Presentation Sign-up Sheet =====
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