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Lecture
1: Introduction Introduction to main problems about networks.
Basic mathematic concepts Material: ˇ
Networks,
Crowds, and Markets (chapters 1,2) ˇ
The structure and function
of complex networks (by M. E. Newman) Lecture
2: Network Measurements Degree distributions. Measuring power-laws.
Clustering Coefficient, Bow-tie structure, Homophily. Strong and Weak ties. Material:
ˇ
Networks,
Crowds, and Markets (chapter 3) Lecture slides (Part
1, Part 2) Lecture
3: Strong and Weak ties Strong and Weak ties. Bridges. Measurements in
real networks Material: ˇ
Networks,
Crowds, and Markets (chapter 3) Lecture
4: Network Models Erdos-Renyi graphs. Configuration Model. Preferential
Attachment. Small-world models. Forrest-Fire model. Material: ˇ
M. E. J. Newman, The structure and function
of complex networks, SIAM
Reviews, 45(2): 167-256, 2003 ˇ
M. E. J. Newman, Power laws, Pareto
distributions and Zipf's law, Contemporary
Physics. ˇ
B. Bollobas,
Mathematical
Results in Scale-Free random Graphs. ˇ
D.J.
Watts. Networks,
Dynamics and Small-World Phenomenon, American Journal of Sociology, Vol.
105, Number 2, 493-527, 1999 ˇ
Watts,
D. J. and S. H. Strogatz. Collective dynamics of 'small-world' networks. Nature 393:440-42, 1998 ˇ
Michael T. Gastner
and M. E. J. Newman, Optimal
design of spatial distribution networks, Phys. Rev. E 74,
016117 (2006). Lecture
5: Strong and Weak Ties, Betweeness, Affiliation
networks Strong and weak ties, Betweeness
computation and clustering. Affiliation networks. Material: ˇ
Networks,
Crowds, and Markets (Chapters 3 and 4) ˇ
Mining Massive Datasets
version 1.1 (Chapter 10) Lecture slides (Part
1, Part 2) Lecture
6: Navigation in a small world Algorithm for searching in a small world network Material: ˇ
Networks,
Crowds, and Markets (chapter 20) Lecture
7: Positive and Negative ties Positive and Negative ties, Structural Balance Material: ˇ
Networks,
Crowds, and Markets (chapter 5) Lecture
8: Information Cascades, Epidemics, Influence Maximization. Game theoretic information cascade. Models for
epidemic spread. Selecting influencers to maximize spread. Material: ˇ
Networks,
Crowds, and Markets (chapters 19, 21) ˇ
D. Kempe,
J. Kleinberg, E. Tardos. Maximizing the
Spread of Influence through a Social Network. Proc.
9th ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, 2003. Lecture slides (Part
A, Part B, Part C) Lecture
9: Link Analysis. Label propagation via Absorbing Random Walks. HITS algorithm, PageRank algorithm. Absorbing
Random Walks, Label propagation Material: ˇ
Networks,
Crowds, and Markets (chapter 14) ˇ
P. G. Doyle, J. L. Snell. Random Walks
and Electrical Networks. ˇ
D.
Bindel, J. Kleinberg, S. Oren. How Bad is Forming Your Own Opinion? Proc. 52nd IEEE
Symposium on Foundations of Computer Science, 2011. Lecture slides (Part
A, Part B) Lecture
10: Link Prediction Predicting future or missing links Material: ˇ
David Liben-Nowell, Jon Kleinberg. The Link
Prediction Problem for Social Networks. J. American Society for
Information Science and Technology. ˇ
Aaron Clauset,Cristopher Moore, M. E.
J. Newman. Hierarchical
structure and the prediction of missing links in networks. Nature 2008 Lecture
11: Privacy in Social Networks Privacy attacks. Releasing anonymized
social networks Material: ˇ
L.
Backstrom, C. Dwork, J.
Kleinberg. Wherefore
Art Thou R3579X? Anonymized Social Networks, Hidden
Patterns, and Structural Steganography. Proc. 16th Intl. World Wide Web Conference,
2007. ˇ
Kun
Liu, Evimaria Terzi: Towards
identity anonymization on graphs, ACM
International Conference on Management of Data (SIGMOD) 2008. ˇ
Michael
Hay, Gerome Miklau, David Jensen, Donald F. Towsley, Philipp Weis: Resisting
structural re-identification in anonymized social
networks. PVLDB 1(1): 102-114 (2008), also in VLDB J. 19(6): 797-823
(2010) ˇ
Bin
Zhou, Jian Pei: Preserving
Privacy in Social Networks Against Neighborhood
Attacks. ICDE 2008: 506-515 ˇ
Lei Zou, Lei Chen, M. Tamer Özsu: K-Automorphism: A General Framework For Privacy Preserving
Network Publication. PVLDB 2(1): 946-957 (2009) ˇ
Elena Zheleva, Lise Getoor: To
join or not to join: the illusion of privacy in social networks with mixed
public and private user profiles. WWW 2009: 531-540 ˇ
Arvind
Narayanan, Vitaly Shmatikov:
De-anonymizing
Social Networks. IEEE Symposium on Security and Privacy 2009: 173-187 |