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EXPLORATORY SOCIAL NETWORK ANALYSIS W/ PAJEK 2E De Nooy mathematics research LN
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eBay-Artikelnr.:405939871020
Artikelmerkmale
- Artikelzustand
- Neuwertig
- Hinweise des Verkäufers
- Country of Origin
- United States
- Book Title
- Exploratory Social Network Analysis with Pajek (Structural
- ISBN-10
- 0521174805
- Educational Level
- Adult & Further Education
- Personalized
- No
- Level
- Advanced
- ISBN
- 9780521174800
Über dieses Produkt
Product Identifiers
Publisher
Cambridge University Press
ISBN-10
0521174805
ISBN-13
9780521174800
eBay Product ID (ePID)
109069641
Product Key Features
Number of Pages
442 Pages
Publication Name
Exploratory Social Network Analysis with Pajek
Language
English
Publication Year
2011
Subject
General, Research
Features
Revised
Type
Textbook
Subject Area
Social Science
Series
Structural Analysis in the Social Sciences Ser.
Format
Trade Paperback
Dimensions
Item Height
1 in
Item Weight
21.2 Oz
Item Length
9 in
Item Width
6.1 in
Additional Product Features
Edition Number
2
Intended Audience
Scholarly & Professional
LCCN
2011-015985
Dewey Edition
23
Series Volume Number
Series Number 27
Illustrated
Yes
Dewey Decimal
302.307
Table Of Content
Part I. Fundamentals: 1. Looking for social structure; 2. Attributes and relations; Part II. Cohesion: 3. Cohesive subgroups; 4. Sentiments and friendship; 5. Affiliations; Part III. Brokerage: 6. Center and periphery; 7. Brokers and bridges; 8. Diffusion; Part IV. Ranking: 9. Prestige; 10. Ranking; 11. Genealogies and citations; Part V. Roles: 12. Blockmodels; 13. Random graph models; Appendix 1. Getting started with Pajek; Appendix 2. Exporting visualizations; Appendix 3. Shortcut key combinations.
Edition Description
Revised edition
Synopsis
This is an extensively revised and expanded second edition of the successful textbook on social network analysis integrating theory, applications, and network analysis using Pajek. The main structural concepts and their applications in social research are introduced with exercises. Pajek software and data sets are available so readers can learn network analysis through application and case studies. Readers will have the knowledge, skill, and tools to apply social network analysis across the social sciences, from anthropology and sociology to business administration and history. This second edition has a new chapter on random network models, for example, scale-free and small-world networks and Monte Carlo simulation; discussion of multiple relations, islands, and matrix multiplication; new structural indices such as eigenvector centrality, degree distribution, and clustering coefficients; new visualization options that include circular layout for partitions and drawing a network geographically as a 3D surface; and using Unicode labels. This new edition also includes instructions on exporting data from Pajek to R software. It offers updated descriptions and screen shots for working with Pajek (version 2.03)., An extensively revised and expanded second edition of the successful textbook on social network analysis integrating theory, applications and network analysis using Pajek. This edition features a new chapter, instructions on exporting data from Pajek to R software, and updated descriptions and screen shots for working with Pajek (version 2.03)., An extensively revised and expanded second edition of the successful textbook on social network analysis integrating theory, applications and network analysis using Pajek. The main structural concepts and their applications in social research are introduced with exercises. Pajek software and data sets are available so readers can learn network analysis through application and case studies. Readers will have the knowledge, skill and tools to apply social network analysis across the social sciences, from anthropology and sociology to business administration and history. This second edition has a new chapter on random network models, for example, scale-free and small-world networks and Monte Carlo simulation; discussion of multiple relations, islands and matrix multiplication; new structural indices such as eigenvector centrality, degree distribution and clustering coefficients; new visualization options that include circular layout for partitions and drawing a network geographically as a 3D surface; and using Unicode labels.
LC Classification Number
HM741.N66 2011
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