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====== Topics in Social Computing ======

==== Breaking News ====

==== Extra Credit Assignments ====
===== 2011-12 Term 1 =====

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|  ^  Lecture I  ^  Lecture II  ^  Tutorial I  ^  Tutorial II  ^
^ Time    |  TBA  |  TBA   |  TBA  |  TBA  |
^ Venue    |   TBA  |  TBA  |  TBA   |  TBA   |

;#;

<html><font color="red"> <b>The Golden Rule of XXXX: </b></font></html> No member of the XXXX community shall take unfair advantage of any other member of the XXXX 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 emphasis of the course is on data mining and knowledge discovery of social interactions, signals and data that are the byproduct of social media services such as search engines, social network sites, blogs, micro-blogs, wikis, etc.  The course topics include, but are not limited to: web data mining, knowledge discovery on the web, web analytics, web information retrieval, ranking algorithms, recommender systems, human computation, models and theories about social networks, large graph and link-based algorithms, social marketing, monetization of the web, security/privacy issues related to social computing, etc.

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

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


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

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| ^  Lecturer  ^  Tutor  ^  Tutor ^
^  Name  |  [[:home|Irwin King]]  |    |    |
^  Email  |  irwinking AT gmail.com  |  | |
^  Office   |  TBA  |  | |
^  Telephone   |  TBA  |  | |
^  Office Hour(s)   |  TBA  | |  |

;#;
====== 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  |  7/9  |  Introduction to Web Intelligence and Social Computing\\ Web 2.0\\ \\ [[http://www.cse.cuhk.edu.hk/~king/csc4170/PDF/CSC4170-01-Introduction.pdf|01-Introduction.pdf]]  |  Tutorial on Python  | |  [[http://www.cse.cuhk.edu.hk/~king/PUB/podcasts/Tim%20O'Reilly%20on%20Web%202.0.mp3|Tim O'Reilly on Web 2.0, The Economist, 20/3/2009]]  |
|  2  |  14/9  |  Introduction to Web Intelligence and Social Computing  |   {{:teaching:csc4170:web-crawler.ppt|Regular Expressions Web Crawler}}   | |   [[http://www.analytictech.com/networks.pdf|Introduction to Social Networks]]  |
|  3  |  21/9  |  Social Networks-Theory\\  Graph Theory\\ \\  [[http://www.cse.cuhk.edu.hk/~king/csc4170/PDF/CSC4170-02-SNA-02.pdf|02-SNA-02.pdf]] <hi #ffff00>NEW!</hi>    |  {{:teaching:csc4170:graph_visualization.ppt|Graph Visualization}}  |  [[http://www.cse.cuhk.edu.hk/~king/csc4170/PDF/hw1_09.pdf|HW #1]]\\  (<hi yellow>Due on or before 6:30 pm, Friday, 2 October, 2009</hi>)\\   {{:teaching:csc4170:csc4170-asgn1-noname1207.xls|grading-asgn1}}  |  [[http://si.umich.edu/~rfrost/courses/SI110/readings/In_Out_and_Beyond/Granovetter.pdf|SWT Theory]]  |
|  4  |  28/9  |  Graph Mining \\ \\  [[http://www.cse.cuhk.edu.hk/~king/csc4170/PDF/CSC4170-03-GraphMining-01.pdf|03-GraphMining-01.pdf]]  |  Graph Mining Algorithms\\  {{:teaching:csc4170:hits.ppt|}}  |   |  [[http://demonstrations.wolfram.com/SamplesOfRandomGraphs/|Generating Random Graphs]]\\  [[http://www.geocities.com/dharwadker/clique/|The Clique Algorithm]]  |
|  5  |  5/10  |  Link Analysis\\   \\  [[http://www.cse.cuhk.edu.hk/~king/csc4170/PDF/CSC4170-04-LinkAnalysis-01.pdf|04-LinkAnalysis-01.pdf]] <hi #ffff00>NEW!</hi>    |  PageRank, HITS, etc.  |  [[http://www.cse.cuhk.edu.hk/~king/csc4170/PDF/hw2_09.pdf|HW #2]]\\ {{:teaching:csc4170:hw2_sampleanswer.pdf|hw2 sample answer}}\\ {{:teaching:csc4170:csc4170-asgn2-noname1207.xls|grading-asgn2}}\\ {{:teaching:csc4170:programming1_09.pdf|HW Programming #1}} {{:teaching:csc4170:newprogramming1_testcases.rar|HW Programming #1 Testcases}} \\ \\ (<hi yellow>Due on or before 6:30 pm, Monday, 19 October, 2009</hi>)\\ {{:teaching:csc4170:csc4170-programming-noname1207.xls|grading-programming}}  |   [[http://nlp.stanford.edu/IR-book/|Introduction to Information Retrieval]]  |
|  6  |  12/10  |  Learning to Rank\\  \\  [[http://www.cse.cuhk.edu.hk/~king/csc4170/PDF/CSC4170-05-Learning2Rank-02.pdf|05-Learning2Rank-02.pdf]] <hi #ffff00>NEW!</hi>\\   |  {{:teaching:csc4170:pagerank.ppt|PageRank}}  |    {{:teaching:csc4170:project_09.pdf|Project Specification}} \\ {{:teaching:csc4170:ml-data_0.zip|Movie Dataset}}  \\    | |
|  7  |  19/10  |  Recommender Systems I  \\  \\  [[http://www.cse.cuhk.edu.hk/~king/csc4170/PDF/CSC4170-06-Recommender-01.pdf|06-Recommender-01.pdf]]   |  {{:teaching:csc4170:evaluation.ppt|Evaluation Methods}}  |    | |
|  8  |  26/10  |  Recommender Systems II\\ Query Expansion\\  \\  [[http://www.cse.cuhk.edu.hk/~king/PUB/CIKM2008-QuerySuggestion.pdf|CIKM2008 Query Suggestion]]  |  {{:teaching:csc4170:deng_entropybiasedmodel_sigir_talk.ppt|QF/IQF}}  |  {{:teaching:csc4170:hw3_09R.pdf|HW #3}}\\ (<hi yellow>Due: Monday,23 November,18:30</hi>)  | |
|  9  |  2/11  |  Human Computation/Social Games\\ \\  [[http://www.cse.cuhk.edu.hk/~king/csc4170/PDF/CSC4170-07-HumanComputation-01.pdf|07-HumanComputation-01.pdf]] <hi #ffff00>NEW!</hi>  | {{:teaching:csc4170:humancomputation.ppt|}} | |  Guest Speaker  |
|  10  |  9/11  |  Crowdsourcing  |  {{:teaching:csc4170:languagemodel.ppt|language model}}  | | |
|  11  |  16/11  |  Q&A\\ Virtual Communities\\ \\ [[http://www.cse.cuhk.edu.hk/~king/csc4170/PDF/CSC4170-08-QandA.pdf|CSC4170-08-QandA.pdf]]    |  Wikis, Blogs, etc.  |  {{:teaching:csc4170:hw4_09.pdf|HW #4}}\\ (<hi yellow>Due: Friday, 4 December 4, 2009, 18:30</hi>)\\  {{:teaching:csc4170:csc4170-asgn4-noname1208.xls|gradings asgn4}}\\ {{:teaching:csc4170:hw4_sampleanswer.pdf|hw4 sample answer}}  | |
|  12  |  23/11  |  Privacy and Security of Information\\ Education, Policy\\  \\ [[http://www.cse.cuhk.edu.hk/~king/csc4170/PDF/CSC4170-09-Security.pdf|09-Security.pdf]]\\  <hi #ffff00>NEW!</hi>   | | |  |
|  13  |  30/11  |  TBA  | | |   |
|  14  |  7/12  |  TBA  | | |   |
|  15  |  14/12  |  Wrap Up\\ \\  Project Presentations  | | |  [[http://edutechwiki.unige.ch/en/EduTech_Wiki:Books/Social_computing_in_education|EduTech on Social Computing in Education]]  |

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

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

/*
  - For each group, the total time for the presentation is 15 minutes, including 12 minutes for the talk and 3 minutes for Q&A. The presentation will follow the order above. Since this class will last until the end of all the presentations, if the time is not suitable for you, you can tell us to change your order. \\
  - In the presentation, there is no demo part. The demo part is an independent process divided into two sub-sections. The first section will be hold in tutorial time on Dec. 1st. In this section, all the groups should demo your program to the two tutors. The tutors will guide you to revise your program. The second section will be hold on Wednesday, Dec. 16th. In this section, Prof. King will check your program before the final submission of your codes. \\
  - For groups implementing graphical algorithms, you should explain one algorithm as detailed as you can in the presentation. You should give an example with the structure of nodes, values, and your calculations. You also need to analyze the complexity of your algorithms and test whether your algorithms can be applied in large graphs. For other groups, you should focus on three aspects including the motivation of your idea, the detailed algorithms, and the justification of your methods comparing to naive methods through experiments.
*/

====== Examination Matters ======
===== Examination Schedule =====

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|              ^        Time           ^        Venue          ^    Notes    ^
^    Midterm Examination    |    TBA  |   TBA   |    TBA    |
^    Final Examination    |   TBA  |    TBA   |    TBA  |

;#;

===== 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.

====== Grade Assessment Scheme ======
^  Homework\\ Assignments  ^  Project Report  ^  Project Presentation  ^  Final Examination  ^
|  20%  |  20%  |  10%  |  50%  |

  -Assignments (20%) 
    -Written assignment 
    -Optional quizzes
  - Project (30%)
    - Report (20%)
    - Presentation (10%)
  -Final Examination (50%) 
  -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 ======


====== Book Sources ======
  - **Academic & Professional Book Centre**, 1H Cheong Ming Bldg., 80-86 Argyle St., Kowloon, 2398-2191, 2391-7430 (fax) 
  - **Caves Books (H. K.)**, 4B Ferry St., G/F., Yaumatei, Kowloon, 2780-0987, 2771-2298 
  - **Man Yuen Book Company**, 45 Parkes street, Jordan Road, Kowloon, Hong Kong, 2366-0594. Not very large, Asian edition books, fair price, wide range, some 10% discount.
  - **Swindon Book Co. Ltd**, 13-15 Lock Road, Tsim Sha Tsiu, Kowloon, 2366-8001.  One of the largest book stores in Hong Kong, exchange rate is not favorable.
  - **Hongkong Book Centre**, 522-7064.  A branch of the Swindon book shop.

====== 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.
  - **Q: What is ACM ICPC?** \\ A: Association of Computer Machinery International Collegiate Programming Contest. Teams from CUHK have done quite well in the previous years. More information on the CSE's programming team can be found at http://www.cse.cuhk.edu.hk/~acmprog.
  - **Q: What are some of the common mistakes made in online and real-time contest?**\\ A: There are a few common mistakes. Please check out [[http://www.acm.org/crossroads/xrds7-5/contests.html|this site]] for more information.
====== Resources ======

  - [[http://networkx.lanl.gov/|NetworkX]]
  -[[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]]
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