Suggested papers 
A list of suggested papers follows. I have grouped the papers by 
category to facilitate your search, but it is worth outlining 
that some papers could belong in more than one category.
 Stochastic graph models 
-   A geometric preferential attachment model of networks 
	
 A. Flaxman, A. Frieze, J. Vera  
	
-   Affiliation networks 
	S. Lattanzi and D. Sivakumar 
	
-   The Diameter of a Scale-free Random Graph  
	B. Bollobas, O. Riordan  
	
-   A General Model of Web Graphs 
	C. Cooper, A. Frieze  
-   First to Market is not Everything: an Analysis of Preferential Attachment with Fitness
	C. Borgs, J. Chayes, C. Daskalakis, S. Roch 
	
	
-   Estimating and Understanding Exponential Random Graph Models
 S. Chatterjee, P. Diaconis	  
	
-  Graph Evolution: Densification and Shrinking Diameter
    J. Leskovec, J. Kleinberg, C. Faloutsos   
	
-  Stochastic Kronecker graphs
    M. Mahdian, Y. Xu  
    
- A Random Graph Model for Power Law Graphs
    W. Aiello, F. Chung, L. Lu   
	-  The Diameter of Sparse Random Graphs
Fan Chung, Linyuan Lu  
-  Stochastic models for the web graph (ps)
    R. Kumar, P. Raghavan, S. Rajagopalan, D. Sivakumar, A. Tomkins, E. Upfal 
       
	   
	-  Models for the Compressible Web
	Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, Alessandro Panconesi, and Prabhakar Raghavan
 
	
-  The Diameter of random power law graphs
Linyuan Lu  
 Estimating models from network data
 
  
-  Winners don"t take all: Characterizing the competition for links on the Web
  Pennock, D. M., Flake, G. W., Lawrence, S., Glover, E. J., and Giles, C. L.   
  
  - Moment based estimation of stochastic Kronecker graph parameters 
  David F. Gleich and Art B. Owen  
  
  -   Kronecker graphs: An approach to modeling networks
  Jure Leskovec, Deepayan Chakrabarti, Jon Kleinberg, Christos Faloutsos, Zoubin Ghahramani  
  
 Strategic graph models 
 
   -  Anarchy is free in network creation
   R. Graham, L. Hamilton, A. Levavi, P.-S. Loh 
   
      
   - The Price of Anarchy in Network Creation Games
   E. Demaine, M. Hajiaghayi, H. Mahini, M. Zadimoghaddam 
   
   
   
   -  On a  network creation game
   A. Fabrikant, A. Luthra, E. Maneva,  C. Papadimitriou, and S. Shenker. 
 
   Check also these  
    
   
    
   
   -  A Strategic Model of Social and Economic Networks 
   M. Jackson, A. Wolinsky 
   
   
 Diffusion related (rumor spreading, cascades, network reconstruction etc.)
 
   
   -  Rumor Spreading in Social Networks.
   F. Chierichetti, S. Lattanzi and A. Panconesi 
 
    
   -  Trace Complexity of Network Inference
   B. Abrahao, F. Chierichetti, R. Kleinberg, and A. Panconesi
   
    
   -  Inferring Networks of Diffusion and Influence
   
   M. Gomez-Rodriguez, J. Leskovec, A. Krause	
   
     
   
    -  Modeling Information Propagation with Survival Theory
   
   Manuel Gomez Rodriguez, Jure Leskovec, Bernhard Schölkopf
   
     
   
   -  Spotting Culprits in Epidemics: How many and Which ones?
   B. A. Aditya, J. Vrekeen, C. Faloutsos 
 
    
   
   -  Rumors in a Network: Who's the Culprit?
   Devavrat Shah, Tauhid Zaman
    
   
    -  Information Cascade at Group Scale
   M. Eftekhar, Y. Ganjali, N. Koudas 
 
    
   
   - Randomized Rumor Spreading
   R. Karp, C. Schindelhauer, S. Shenker, B. Vöcking 
   
 Social learning
    
   -  Dynamics of information exchange in endogenous social networks 
   Daron Acemoglu, Kostas Bimpikis, Asuman Ozdaglar 
    
   
   
   -  Bayesian learning in social networks
   Daron Acemoglu, Munther Dahleh, Ilan Lobel, Asuman Ozdaglar 
   Check  this out too.
    
   
 Subgraphs 
 
   
   -  Counting Arbitrary Subgraphs in Data Streams 
      Daniel M. Kane, Kurt Mehlhorn, Thomas Sauerwald, and He Sun 
       
   -  Triangle counting in dynamic graph streams
      K. Kutzkov, R. Pagh   
   -  On the Streaming Complexity of Computing Local Clustering Coefficients
      K. Kutzkov, R. Pagh  
   -  Efficient Triangle Counting in Large Graphs via Degree-based Vertex Partitioning 
      Mihail N. Kolountzakis, Gary L. Miller, CET, Richard Peng
       
   -  Counting Triangles in Data Streams 	
      L. Buriol, G. Frahling, S. Leonardi, A. Marchetti-Spaccamela, C. Sohler 
   
   -  Subgraph Frequencies: Mapping the Empirical and Extremal Geography of Large Graph Collections
   J. Ugander, L. Backstrom, J. Kleinberg
   
    
   
   -  Counting Stars and Other Small Subgraphs in Sublinear Time
   Mira Gonen, Dana Ron, Yuval Shavitt 
	
   Check this nice talk on sublinear algorithms and property testing 
   here.
    
 
  Dense subgraphs and graph partitioning 
   -  A Local Algorithm for Finding Well-Connected Clusters
   Zeyuan A. Zhu, Silvio Lattanzi and Vahab Mirrokni
    
   -  Streaming Balanced Graph Partitioning for Random Graphs
   Isabelle Stanton   
   
   - Spectral Partitioning of Random Graphs
   Frank McSherry
    
   - Statistical Properties of Community Structure in Large Social and Information Networks
   Jure Leskovec, Kevin Lang, Anirban Dasgupta, Michael Mahoney 
    
   
   -  On finding dense subgraphs 
   Samir Khuller and Barna Saha
    
   -  Local Graph Partitioning using PageRank Vectors
   R. Andersen, F. Chung, K. Lang
  
    
   
   - Balanced label propagation for partitioning massive graphs
 Johan Ugander, Lars Backstrom 
  
  Evolutionary dynamics on graphs 
    
	- Evolutionary dynamics on graphs  and the Supplement 
   E. Lieberman, C. Hauert, M. Nowak
    
   
   - Natural models for evolution on networks. 
   G.B. Mertzios, S. Nikoletseas, C. Raptopoulos, P.G. Spirakis
    
   
   
      - Approximating fixation probabilities in the generalized Moran process 
J. Diaz, L.A. Goldberg, G.B. Mertzios, D. Richerby, M. Serna, and P.G. Spirakis    
   
    
   
 Learning
 
   
   -  Learning from labeled and unlabeled data on a directed graph 
    D. Zhou, J. Huang, B. Schoelkopf  
   
   -  Fitting a graph to vector data
   S. Daitch, J. Kelner, D. Spielman  
      -  Fast Random Walk with Restart and Its Applications 
   H. Tong, C. Faloutsos, J. Pan 
   
      -  Learning from labeled and  unlabeled data using graph mincuts
      A. Blum, S. Chawla 
   
      -  
	  The Fastest Mixing Markov Process on a Graph and a Connection to a Maximum Variance Unfolding Problem
	  
      J. Sun, S. Boyd, L. Xiao, and P. Diaconis 
	  
 
	  or/and a related NIPS paper 
	   Colored Maximum Variance Unfolding 
	  L. Song, A. Smola, K. Borgwardt, A. Gretton 
	   
   
 Various 
 
   -  On the Bias of Traceroute Sampling: or, Power-Law Degree 
   Distributions in Regular Graphs
 
   D. Achlioptas, A. Clauset, D. Kempe, C. Moore  
   
   -  Trading in Networks: Theory and Experiment
   S. Choi, A. Galeotti, S. Goyal
     
   
   
   -  The Network Origins of Large Economic Downturns
   D. Acemoglu, A. Ozdaglar, A. Tahbaz-Salehi   
  
   -  A Random Graph Model of Multi-Hospital Kidney Exchanges
   Panos Toulis, David Parkes 
    
   -  Suppressing cascades of load in interdependent networks 
   Charles D. Brummitt, Raissa M. D'Souza, and E. A. Leicht
    
   
   - Maximum Matchings in Random Bipartite Graphs and the Space Utilization of Cuckoo Hash Tables
   Alan Frieze, Pall Melsted 
   A nice overview of cuckoo hashing and related results is presented in this thesis  
   Random Bipartite Graphs and their Application to Cuckoo Hashing
   
 
   R. Kutzelnigg 
    
      
    -  The Spread of Evidence-Poor Medicine via Flawed Social-Network Analysis
   R. Lyons
   [Of course in order to be able to understand the critique you also need    to read the referred work of Christakis and Fowler] 
     
   
   
     
	
Note
 
You are not obliged to pick one of the aforementioned papers. You can choose a paper 
of your own preference as long as it is related to the content of the class. 
Some conferences and journals   where you can search for more papers follow. 
 
 
 
-  ACM Conference on Electronic Commerce (EC) 
 
-  KDD
 
-  WWW
 
-  WSDM
 
-  ESA 
 
-  ICALP 
 
-  SODA 
 
-  Random structures and algorithms (RSA)
 
-  Combinatorics, Probability and Computing (CPC)
 
-  Internet Mathematics