Statistical Network Analysis: Models, Issues, and New Directions

1. Front Matter

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2. Invited Presentations

   1. Structural Inference of Hierarchies in Networks

      • Aaron Clauset, Cristopher Moore, Mark E. J. Newman

      Pages 1-13

   2. Heider vs Simmel: Emergent Features in Dynamic Structures

      • David Krackhardt, Mark S. Handcock

      Pages 14-27

   3. Joint Group and Topic Discovery from Relations and Text

      • Andrew McCallum, Xuerui Wang, Natasha Mohanty

      Pages 28-44

   4. Statistical Models for Networks: A Brief Review of Some Recent Research

      • Stanley Wasserman, Garry Robins, Douglas Steinley

      Pages 45-56

3. Other Presentations

   1. Combining Stochastic Block Models and Mixed Membership for Statistical Network Analysis

      • Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Eric P. Xing

      Pages 57-74

   2. Exploratory Study of a New Model for Evolving Networks

      • Anna Goldenberg, Alice Zheng

      Pages 75-89

   3. A Latent Space Model for Rank Data

      • Isobel Claire Gormley, Thomas Brendan Murphy

      Pages 90-102

   4. A Simple Model for Complex Networks with Arbitrary Degree Distribution and Clustering

      • Mark S. Handcock, Martina Morris

      Pages 103-114

   5. Discrete Temporal Models of Social Networks

      • Steve Hanneke, Eric P. Xing

      Pages 115-125

   6. Approximate Kalman Filters for Embedding Author-Word Co-occurrence Data over Time

      • Purnamrita Sarkar, Sajid M. Siddiqi, Geoffrey J. Gordon

      Pages 126-139

   7. Discovering Functional Communities in Dynamical Networks

      • Cosma Rohilla Shalizi, Marcelo F. Camperi, Kristina Lisa Klinkner

      Pages 140-157

   8. Empirical Analysis of a Dynamic Social Network Built from PGP Keyrings

      • Robert H. Warren, Dana Wilkinson, Mike Warnecke

      Pages 158-171

4. Extended Abstracts

   1. A Brief Survey of Machine Learning Methods for Classification in Networked Data and an Application to Suspicion Scoring

      • Sofus Attila Macskassy, Foster Provost

      Pages 172-175

   2. Age and Geographic Inferences of the LiveJournal Social Network

      • Ian MacKinnon, Robert H. Warren

      Pages 176-178

   3. Inferring Organizational Titles in Online Communication

      • Galileo Mark S. Namata Jr., Lise Getoor, Christopher P. Diehl

      Pages 179-181

   4. Learning Approximate MRFs from Large Transactional Data

      • Chao Wang, Srinivasan Parthasarathy

      Pages 182-185

5. Panel Discussion

   1. Panel Discussion

      • David M. Blei

      Pages 186-194

6. Back Matter

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This volume was prepared to share with a larger audience the exciting ideas and work presented at an ICML 2006 workshop of the same title. Network models have a long history. Sociologists and statisticians made major advances in the 1970s and 1980s, culminating in part with a number of substantial databases and the class of exponential random graph models and related methods in the early 1990s. Physicists and computer scientists came to this domain cons- erably later, but they enriched the array of models and approaches and began to tackle much larger networks and more complex forms of data. Our goal in organ- ing the workshop was to encourage a dialog among people coming from di?erent disciplinary perspectives and with di?erent methods, models, and tools. Both the workshop and the editing of the proceedings was a truly colla- rative e?ort on behalf of all six editors, but three in particular deserve special recognition. Anna Goldenberg and Alice Zheng were the driving force behind the entire enterprise and Edo Airoldi assisted on a number of the more important arrangements.

• Online
• calculus
• distributed networks
• dynamical networks
• evolving networks
• genetic algorithms
• graph drawing
• machine learning
• modeling
• network analysis
• network computing
• network hierarchies
• network modeling
• organization
• self-organizing systems
• algorithm analysis and problem complexity

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