Cover is for reference only

Analyzing social networks using R /

"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...

Full description

Saved in:
Bibliographic Details
Main Authors: Borgatti, Stephen P.
Group Author: Everett, Martin G., 1955-; Johnson, Jeffrey C.; Agneessens, Filip
Published: SAGE,
Publisher Address: Los Angeles :
Publication Dates: [2022]
Literature type: Book
Language: English
Subjects:
Online social networks > Data processing.
R (Computer program language)
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"--Back cover.
Carrier Form: xviii, 359 pages : illustrations (some color), forms ; 24 cm
Bibliography: Includes bibliographical references (pages [341]-349) and index.
ISBN: 9781529722475
1529722470
9781529722482
1529722489
Index Number: HM742
CLC: TP312.8R
C912.3-39
Call Number: C912.3-39/B732
Contents: Introduction -- Mathematical foundations -- Research design -- Data collection -- Data management -- Multivariate techniques used in network analysis -- Visualization -- Local node-level measures -- Centrality -- Group-level measures -- Subgroups and community detection -- Equivalence -- Analyzing two-mode data -- Introduction to inferential statistics for complete networks -- ERGMs and SAOMs.

Related Book Recommendations