Social and Technological Network Analysis (2010-2011):
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:
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.
- 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).
- Discussion of possible future research ideas in the area.
- D. Liben-Nowell, J. Kleinberg. The Link Prediction Problem for
Social Networks. Proc. CIKM, 2003.
- D. Liben-Nowell, J. Novak, R. Kumar, P. Raghavan, A. Tomkins. Geographic routing
in social networks. Proc. Natl. Acad. Sci., 102, 2005.
- R. Kumar, J. Novak, A. Tomkins. Structure and evolution of online social
networks. In Proc. KDD, 2006.
- J. Leskovec, L. Adamic, B. Huberman. The Dynamics of Viral
Marketing. TWEB, 2007.
- J. Leskovec, E. Horvitz. Worldwide Buzz: Planetary-Scale Views on an Instant-Messaging
Network. Proc. International WWW Conference, 2008.
- M. Cha, A. Mislove, K. P. Gummadi. A measurement-driven analysis of
information propagation in the flickr social network. In Proc. WWW, 2008.
- J. Kunegis, A. Lommatzsch, C. Bauckhage. The Slashdot Zoo: Mining a social
network with negative edges. In Proc. WWW, 2009.
- M.E.J. Newman. The first-mover advantage in scientific publication. European
Physics Letters 86, 68001, 2009.
- L. Backstrom, E. Sun, C. Marlow. Find Me If You Can: Improving Geographical
Prediction with Social and Spatial Proximity. In Proc. WWW, 2010.
- M. Cha, H. Haddadi, F. Benevenuto, K.P. Gummadi. Measuring user influence in
Twitter: The million follower fallacy. In Proc. ICWSM, 2010.
- A. Goyal, F. Bonchi, L.V.S. Lakshmanan. Learning influence probabilities in
social networks. In Proc. WSDM, 2010.
- H. Kwak, C. Lee, H. Park, S. Moon. What is Twitter, a social network or a news
media? In Proc. WWW, 2010.
- J. Leskovec, D. Huttenlocher, J. Kleinberg. Predicting Positive and Negative
Links in Online Social Networks. In Proc. WWW, 2010.
- 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.
- Amazon: co-purchase product network and all product
information. (262,111 nodes and 1,234,877 directed edges)
- extraction of network communities and analysis of their
homogeneity with respect to product categories;
- analysis of potential correlations between network node metrics and
- prediction model for product sales given network properties and
- 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)
- investigation of power-law network structure evolution over time with a generative
- analysis of the first-mover advantage for scientific publications;
- analysis/design of ranking algorithms to facilitate search among
- Epinions: trust and distrust signed social network among users on
Epinions.com. (131,828 nodes and 841,372 directed edges)
- analysis of the structure of the social network arising from
positive, negative and aggregated edges, with an investigation
of the correlations among them;
- analysis of social triangles and verification of structural balance
theory ("the enemy of my enemy is my friend");
- prediction models of the sign of a social link.
- 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)
- analysis and comparison of the social network among Facebook users
and the network arising from their explicit interactions;
- prediction models of interaction between users;
- 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.