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Data Mining for Social Network Data

Overview of attention for book
Cover of 'Data Mining for Social Network Data'

Table of Contents

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    Book Overview
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    Chapter 1 Social Network Data Mining: Research Questions, Techniques, and Applications
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    Chapter 2 Automatic Expansion of a Social Network Using Sentiment Analysis
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    Chapter 3 Automatic Mapping of Social Networks of Actors from Text Corpora: Time Series Analysis
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    Chapter 4 A Social Network-Based Recommender System (SNRS)
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    Chapter 5 Network Analysis of US Air Transportation Network
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    Chapter 6 Identifying High-Status Nodes in Knowledge Networks
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    Chapter 7 Modularity for Bipartite Networks
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    Chapter 8 ONDOCS: Ordering Nodes to Detect Overlapping Community Structure
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    Chapter 9 Framework for Fast Identification of Community Structures in Large-Scale Social Networks
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    Chapter 10 Geographically Organized Small Communities and the Hardness of Clustering Social Networks
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    Chapter 11 Integrating Genetic Algorithms and Fuzzy Logic for Web Structure Optimization
Attention for Chapter 9: Framework for Fast Identification of Community Structures in Large-Scale Social Networks
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Citations

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Summary Dimensions citations
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Chapter title
Framework for Fast Identification of Community Structures in Large-Scale Social Networks
Chapter number 9
Book title
Data Mining for Social Network Data
Published by
Springer, Boston, MA, January 2010
DOI 10.1007/978-1-4419-6287-4_9
Book ISBNs
978-1-4419-6286-7, 978-1-4419-6287-4
Authors

Yutaka I. Leon-Suematsu, Kikuo Yuta

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 25%
Student > Bachelor 1 25%
Student > Master 1 25%
Unknown 1 25%
Readers by discipline Count As %
Computer Science 2 50%
Social Sciences 1 25%
Unknown 1 25%

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