Analyzing social networks using R
Material type:
TextPublication details: London Sage Publications Ltd. 2022 Description: xviii, 359 pISBN: 9781529722475Subject(s): R (Computer program language)DDC classification: 006.754 Summary: This approachable book introduces network research in R, walking you through every step of doing social network analysis. Drawing together research design, data collection and data analysis, it explains the core concepts of network analysis in a non-technical way.
The book balances an easy to follow explanation of the theoretical and statistical foundations underpinning network analysis with practical guidance on key steps like data management, preparation and visualisation. With clarity and expert insight, it:
• Discusses measures and techniques for analyzing social network data, including digital media
• Explains a range of statistical models including QAP and ERGM, giving you the tools to approach different types of networks
• Offers digital resources like practice datasets and worked examples that help you get to grips with R software
| Item type | Current library | Collection | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|
Book
|
Indian Institute of Management LRC General Stacks | IT & Decisions Sciences | 006.754 BOR (Browse shelf(Opens below)) | Available | 004636 |
Table of content
Chapter 1: Introduction Chapter 2: Mathematical Foundations Chapter 3: Research Design Chapter 4: Data Collection Chapter 5: Data Management Chapter 6: Multivariate Techniques Used in Network Analysis Chapter 7: Visualization Chapter 8: Local Node-Level Measures Chapter 9: Centrality Chapter 10: Group-level measures Chapter 11: Subgroups and community detection Chapter 12: Equivalence Chapter 13: Analyzing Two-mode Data Chapter 14: Introduction to Inferential Statistics for Complete Networks Chapter 15: ERGMs and SAOMs
This approachable book introduces network research in R, walking you through every step of doing social network analysis. Drawing together research design, data collection and data analysis, it explains the core concepts of network analysis in a non-technical way.
The book balances an easy to follow explanation of the theoretical and statistical foundations underpinning network analysis with practical guidance on key steps like data management, preparation and visualisation. With clarity and expert insight, it:
• Discusses measures and techniques for analyzing social network data, including digital media
• Explains a range of statistical models including QAP and ERGM, giving you the tools to approach different types of networks
• Offers digital resources like practice datasets and worked examples that help you get to grips with R software
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