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Social and Technological Network Analysis (2010-2011): Course Assessment

Course Assessment Help from Salvatore Scellato

1 - Research paper report

Every student will prepare one report (of approximately 1,500 words) on one assigned research paper. The report is worth 40% of the final mark. The report will contain two parts of about 750 words each:

  1. Critical analysis of the papers including, possibly, comparisons and references to other material presented in the course or found by the student and comments on how solid the result obtained are (e.g., comments on the evaluation methods or on the analysis applied can be included).
  2. Discussion of possible future research ideas in the area.
This is a selection of mainly recent research papers on social and technological networks. Choose any still available paper and e-mail your choice to cm542.
  1. D. Liben-Nowell, J. Kleinberg. The Link Prediction Problem for Social Networks. Proc. CIKM, 2003.
  2. D. Liben-Nowell, J. Novak, R. Kumar, P. Raghavan, A. Tomkins. Geographic routing in social networks. Proc. Natl. Acad. Sci., 102, 2005.
  3. R. Kumar, J. Novak, A. Tomkins. Structure and evolution of online social networks. In Proc. KDD, 2006.
  4. J. Leskovec, L. Adamic, B. Huberman. The Dynamics of Viral Marketing. TWEB, 2007.
  5. J. Leskovec, E. Horvitz. Worldwide Buzz: Planetary-Scale Views on an Instant-Messaging Network. Proc. International WWW Conference, 2008.
  6. M. Cha, A. Mislove, K. P. Gummadi. A measurement-driven analysis of information propagation in the flickr social network. In Proc. WWW, 2008.
  7. J. Kunegis, A. Lommatzsch, C. Bauckhage. The Slashdot Zoo: Mining a social network with negative edges. In Proc. WWW, 2009.
  8. M.E.J. Newman. The first-mover advantage in scientific publication. European Physics Letters 86, 68001, 2009.
  9. L. Backstrom, E. Sun, C. Marlow. Find Me If You Can: Improving Geographical Prediction with Social and Spatial Proximity. In Proc. WWW, 2010.
  10. M. Cha, H. Haddadi, F. Benevenuto, K.P. Gummadi. Measuring user influence in Twitter: The million follower fallacy. In Proc. ICWSM, 2010.
  11. A. Goyal, F. Bonchi, L.V.S. Lakshmanan. Learning influence probabilities in social networks. In Proc. WSDM, 2010.
  12. H. Kwak, C. Lee, H. Park, S. Moon. What is Twitter, a social network or a news media? In Proc. WWW, 2010.
  13. J. Leskovec, D. Huttenlocher, J. Kleinberg. Predicting Positive and Negative Links in Online Social Networks. In Proc. WWW, 2010.
  14. J. Leskovec, D. Huttenlocher, J. Kleinberg. Signed Networks in Social Media. In Proc. CHI, 2010.

Deadline: noon on 14th February 2011. Please email a PDF to cm542 and hand in hard copy.

2 - Projects

Every student will complete a project which consists of analysis of an assigned dataset according to some indicated network measures using NetworkX: the analysis should be reported in a document of about 1,500 words where the results are commented and justified. This will be worth 60% of the final mark. Each student will be assigned one of the following networks and is encouraged to choose among the ideas outlined under his/her network.


  1. Amazon: co-purchase product network and all product information. (262,111 nodes and 1,234,877 directed edges)
    Project ideas:
    1. extraction of network communities and analysis of their homogeneity with respect to product categories;
    2. analysis of potential correlations between network node metrics and product sales/reviews;
    3. prediction model for product sales given network properties and product characteristics.
  2. HEP-PH: citation graph among papers in high-energy physics with temporal publication data of each paper. (34,546 nodes and 421,578 directed edges)
    Project ideas:
    1. investigation of power-law network structure evolution over time with a generative model;
    2. analysis of the first-mover advantage for scientific publications;
    3. analysis/design of ranking algorithms to facilitate search among publications.
  3. Epinions: trust and distrust signed social network among users on Epinions.com. (131,828 nodes and 841,372 directed edges)
    Project ideas:
    1. analysis of the structure of the social network arising from positive, negative and aggregated edges, with an investigation of the correlations among them;
    2. analysis of social triangles and verification of structural balance theory ("the enemy of my enemy is my friend");
    3. prediction models of the sign of a social link.
  4. Facebook: friendship connections within one regional network and information about interaction events between users, such as likes, comments and the like. (657,681 nodes and 1,302,764 undirected edges)
    Project ideas:
    1. analysis and comparison of the social network among Facebook users and the network arising from their explicit interactions;
    2. prediction models of interaction between users;
    3. analysis of user activity as a function of ego-network properties.

Deadline: 18th March 2011. Please email a PDF to cm542 and hand in a hard copy.