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Statistical Network Analysis: Models, Issues, and New Directions

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Cover of 'Statistical Network Analysis: Models, Issues, and New Directions'

Table of Contents

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    Book Overview
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    Chapter 1 Structural Inference of Hierarchies in Networks
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    Chapter 2 Heider vs Simmel: Emergent Features in Dynamic Structures
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    Chapter 3 Joint Group and Topic Discovery from Relations and Text
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    Chapter 4 Statistical Models for Networks: A Brief Review of Some Recent Research
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    Chapter 5 Combining Stochastic Block Models and Mixed Membership for Statistical Network Analysis
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    Chapter 6 Exploratory Study of a New Model for Evolving Networks
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    Chapter 7 Statistical Network Analysis: Models, Issues, and New Directions
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    Chapter 8 A Simple Model for Complex Networks with Arbitrary Degree Distribution and Clustering
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    Chapter 9 Discrete Temporal Models of Social Networks
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    Chapter 10 Approximate Kalman Filters for Embedding Author-Word Co-occurrence Data over Time
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    Chapter 11 Discovering Functional Communities in Dynamical Networks
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    Chapter 12 Empirical Analysis of a Dynamic Social Network Built from PGP Keyrings
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    Chapter 13 A Brief Survey of Machine Learning Methods for Classification in Networked Data and an Application to Suspicion Scoring
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    Chapter 14 Age and Geographic Inferences of the LiveJournal Social Network
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    Chapter 15 Inferring Organizational Titles in Online Communication
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    Chapter 16 Learning Approximate MRFs from Large Transactional Data
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    Chapter 17 Panel Discussion
Attention for Chapter 2: Heider vs Simmel: Emergent Features in Dynamic Structures
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Citations

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Chapter title
Heider vs Simmel: Emergent Features in Dynamic Structures
Chapter number 2
Book title
Statistical Network Analysis: Models, Issues, and New Directions
Published by
Springer, Berlin, Heidelberg, January 2007
DOI 10.1007/978-3-540-73133-7_2
Book ISBNs
978-3-54-073132-0, 978-3-54-073133-7
Authors

David Krackhardt, Mark S. Handcock, Krackhardt, David, Handcock, Mark S.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 6%
United Kingdom 4 5%
France 2 3%
Netherlands 2 3%
Denmark 1 1%
Germany 1 1%
Unknown 65 81%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 36%
Researcher 12 15%
Professor > Associate Professor 11 14%
Student > Doctoral Student 5 6%
Other 4 5%
Other 16 20%
Unknown 3 4%
Readers by discipline Count As %
Social Sciences 28 35%
Business, Management and Accounting 19 24%
Computer Science 11 14%
Physics and Astronomy 3 4%
Engineering 3 4%
Other 11 14%
Unknown 5 6%