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Lecture 1: Introduction
Introduction
to main problems about networks. Basic mathematic
concepts
Material:
Lecture
slides (pptx, pdf).
Introduction to Graph Theory (pptx,
pdf)
(slides from Social Media
Mining)
Lecture 2: Network Measurements
Degree
distributions. Measuring power-laws. Clustering
Coefficient, Effective Diameter, Bow-tie structure, Homophily.
Material:
Lecture
slides (pptx, pdf)
Lecture 3: Network Models
Erdos-Renyi
graphs. Configuration Model. Preferential Attachment.
Small-world models. Forrest-Fire model. Kronecker
graphs
Material:
- M. E. J.
Newman, The
structure and function of complex networks, SIAM
Reviews, 45(2): 167-256, 2003
- M. E.
J. Newman, Power
laws, Pareto distributions and Zipf's law, Contemporary
Physics.
- B. Bollobas, Mathematical
Results in Scale-Free random Graphs.
- D.J.
Watts. Networks,
Dynamics and Small-World Phenomenon, American
Journal of Sociology, Vol. 105, Number 2, 493-527,
1999
- Watts,
D. J. and S. H. Strogatz.
Collective dynamics of
'small-world' networks. Nature
393:440-42, 1998
- Michael
T. Gastner and M. E. J.
Newman, Optimal
design of spatial distribution networks, Phys.
Rev. E 74, 016117 (2006).
- J.
Leskovec, J. M. Kleinberg, C. Faloutsos. Graphs
over time: Densification laws, shrinking diameters
and possible explanations. TKDD 2007
- J.
Leskovec, D. Chakrabarti, J. M. Kleinberg, C.
Faloutsos. Kronecker
graphs: An approach to modeling networks.
Journal of Maching Learning, 2010.
Lecture
slides (pptx,
pdf)
Lecture 4: Community Detection
Communities
in Social Networks, Clustering, Betweeness,Modularity
Material:
Lecture
slides: (pptx, pdf)
Lecture 5: Graph Partitioning, Densest Subgraph
Graph
Partitioning, Spectral Clustering. The
Densest Subgraph problem.
Material:
Lecture
slides: (pptx, pdf)
Lecture 6: Link Analysis
Ranking, Absorbing Random Walks.
Web
search, PageRank, HITS. Random walks on
graphs. Absorbing Random Walks. Opinion diffusion.
Material:
Lecture
slides: (pptx, pdf)
Lecture 7: Link Prediction.
Link prediction and link
recommendations.
Material:
- David Liben-Nowell, Jon Kleinberg. The
Link Prediction Problem for Social Networks.
J. American Society for Information Science and
Technology.
- Ryan
Lichtenwalter, Jake T. Lussier Nitesh V. Chawla. New
perspectives and methods in link prediction,
KDD 2010.
- Glen
Jeh, Jenifer Widom. SimRank:
A measure for sturctural context similarity.
KDD 2002
- Tan, Steinbach, Kumar. Introduction to Data Mining (Chapter
4)
- P.Gupta,
A.Goel, J.Lin, A.Sharma, D.Wang, R.Zadeh.
WTF:The Who to Follow Service at Twitter,
WWW 2013
- R.Lempel,
S.Moran. SALSA:
The Stochastic Approach for Llink-Structure
Analysis. ACM Trans. Inf. Syst.19(2):131-160
(2001)
Lecture
slides: (pptx, pdf)
Lecture 8: Information
Cascades, Epidemics, Influence Maximization.
Game theoretic information
cascade. Models for epidemic spread. Selecting
influencers to maximize spread.
Material:
Lecture
slides: (pptx, pdf)
Lecture 9: Network Ties
Strong
and Weak ties. Strong Triadic Closure. Networks
with Positive and Negative ties. Structural
Balance.
Material:
Lecture slides: (pptx, pdf)
Lecture 10: Team Formation in Social Networks.
Recommendation systems
Team
formation in Social Networks. Recommendation
Systems and Social Recommendations.
Material:
- T. Lappas. K. Liu. E. Terzi, Finding
a team of experts in a social network. KDD
2009
- Michael D. Ekstrand, John T. Riedl, Joseph A. Konstan, Collaborative
Filtering Recommender Systems
- Mining Massive
Datasets (Chapters 9,11)
- Social Media
Mining (Chapter 9)
- Hao Ma, Dengyong Zhou, Chao Liu,
Michael R. Lyu, Irwin King, Recommender
Systems with Social Regularization, WSDM 2010
- David Kempe,
Structure
and Dynamics of Information in Networks Course
notes - Chapter 4
Lecture slides: (pptx, pdf)
Lecture 11: Mining Social
Content.
Using content from online social
networks and media to predict stock changes, track
earthquakes, and understand news cycles.
Material:
- Eduardo J.
Ruiz, Vaggelis Hristidis, Carlos Castillo,
Aristides Gionis, Alejandro Jaimes, Correlating
Financial Time Series with Micro-Blogging Activity,
WSDM 2012.
- Takeshi
Sakaki, Makoto Ozakaki, Yutaka Matsuo, Earthquake
shakes Twitter users: Real-time event detection by
social sensors, WWW 2010.
- Jure
Leskovek, Lars Backstorm, Jon Kleinberg, Meme-tracking
and the dynamics of the news cycle, KDD 2009
Lecture slides: (pptx, pdf)
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