Books

'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 a range of statistical models including QAP and ERGM, giving you the tools to approach different types of networks. Provides a fully integrated discussion of digital data and networks like Twitter, sociolab and Amazon. Offers digital resources like practice datasets and worked examples that help you get to grips with R software.'

'Social network analysis is used widely in the social and behavioral sciences, as well as in economics, marketing, and industrial engineering. The social network perspective focuses on relationships among social entities and is an important addition to standard social and behavioral research, which is primarily concerned with attributes of the social units. Social Network Analysis: Methods and Applications reviews and discusses methods for the analysis of social networks with a focus on applications of these methods to many substantive examples. It is a reference book that can be used by those who want a comprehensive review of network methods, or by researchers who have gathered network data and want to find the most appropriate method by which to analyze it. It is also intended for use as a textbook as it is the first book to provide comprehensive coverage of the methodology and applications of the field..'

´`Social networks fundamentally shape our lives. Networks channel the ways that information, emotions, and diseases flow through populations. Networks reflect differences in power and status in settings ranging from small peer groups to international relations across the globe. Network tools even provide insights into the ways that concepts, ideas and other socially generated contents shape culture and meaning. As such, the rich and diverse field of social network analysis has emerged as a central tool across the social sciences. This Handbook provides an overview of the theory, methods, and substantive contributions of this field. The thirty-three chapters move through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. The Handbook includes chapters on data collection and visualization, theoretical innovations, links between networks and computational social science, and how social network analysis has contributed substantively across numerous fields. As networks are everywhere in social life, the field is inherently interdisciplinary and this Handbook includes contributions from leading scholars in sociology, archaeology, economics, statistics, and information science among others.`

´Ideas about social structure and social networks are very old. People have always believed that biological and social links among individuals are important. But it wasn't until the early 1930s that systematic research that explored the patterning of social ties linking individuals emerged. And it emerged, not once, but several times in several different social science fields and in several places. This book reviews these developments and explores the social processes that wove all these "schools" of network analysis together into a single coherent approach.

´Snijders and Bosker's book is an applied, authoritative and accessible introduction to the topic, providing readers with a clear conceptual and practical understanding of all the main issues involved in designing multilevel studies and conducting multilevel analysis. This book provides step-by-step coverage of: multilevel theories, ecological fallacies, the hierarchical linear model,  testing and model specification, heteroscedasticity, study designs, longitudinal data, multivariate multilevel models, and discrete dependent variables. There are also new chapters on: missing data, multilevel modeling and survey weights, Bayesian and MCMC estimation and latent-class models.'

'Social networks are ubiquitous. The science of networks has shaped how researchers and society understand the spread of disease, the precursors of loneliness, the rise of protest movements, the causes of social inequality, the influence of social media, and much more. Egocentric analysis conceives of each individual, or ego, as embedded in a personal network of alters, a community partially of their creation and nearly unique to them, whose composition and structure have consequences. This volume is dedicated to understanding the history, present, and future of egocentric social network analysis. The text brings together the most important, classic articles foundational to the field with new perspectives to form a comprehensive volume ideal for courses in network analysis. The collection examines where the field of egocentric research has been, what it has uncovered, and where it is headed.'

'Written at an introductory level, and featuring engaging case examples, this book reviews the theory and practice of personal and egocentric network research. This approach offers powerful tools for capturing the impact of overlapping, changing social relationships and contexts on individuals' attitudes and behavior. The authors provide solid guidance on the formulation of research questions; research design; data collection, including decisions about survey modes and sampling frames; the measurement of network composition and structure, including the use of name generators; and statistical modeling, from basic regression techniques to more advanced multilevel and dynamic models. Ethical issues in personal network research are addressed. User-friendly features include boxes on major published studies, end-of-chapter suggestions for further reading, and an appendix describing the main software programs used in the field.'

'The ego-net approach to social network analysis, which takes discrete individual actors and their contacts as its starting point, is one of the most widely used approaches in the field. This is the first textbook to take readers through each stage of ego-net research, from conception, through research design and data gathering to analysis. It starts with the basics, assuming no prior knowledge of social network analysis, but then moves on to introduce cutting-edge innovations, covering both new statistical approaches to ego-net analysis and the most recent thinking on mixing methods (quantitative and qualitative) to achieve depth and rigour. It is an absolute must for anybody wishing to explore the importance of networks.'

´Egocentric network analysis is used widely across the social sciences, especially in anthropology, political science, economics, and sociology, and is increasingly being employed in communications, informatics, and business and marketing studies. Egocentric network analysis requires a unique set of data collection and analysis skills that overlap only minimally with other network methodologies. However, until now there has been no single reference for conceptualizing, collecting, and analyzing egocentric social network data. This comprehensive guide to study design, data collection, and analysis brings together the state of knowledge with the most effective research tools to guide newcomers to this field. It is illustrated with many engaging examples and graphics and assumes no prior knowledge. Covering the entire research process in a logical sequence, from conceptualizing research questions to interpreting findings, this volume provides a solid foundation for researchers at any stage of their career to learn and apply ego network methods.

'How do we interact with people in our everyday life? Who are the people we are connected to? What are the consequences of overlapping social circles and how people deal with the potential emerging conflicts? What are the structural and cultural mechanisms that regulate social worlds? Network science is a scientific approach to the study of network dependencies and associations which tries to answer these and many other questions. This book explores the underlying mechanisms that regulate social life as they are produced, reproduced, modified, and abandoned in the spatial and temporal patterns of interactions. The mixed methods approach, that combines formal network analysis with qualitative materials and statistical tools, shows the importance of contextualising structural mechanisms in their social and cultural environment, and allows overcoming the traditional methodological boundaries that shape the field of social sciences.'

'This edited volume demonstrates the potential of mixed-methods designs for the research of social networks and the utilization of social networks for other research. Mixing methods applies to the combination and integration of qualitative and quantitative methods. In social network research, mixing methods also applies to the combination of structural and actor-oriented approaches. The volume provides readers with methodological concepts to guide mixed-methods network studies with precise research designs and methods to investigate social networks of various sorts. Each chapter describes the research design used and discusses the strengths of the methods for that particular field and for specific outcomes.'

' [...] Are you struggling to design your social network research? Are you looking for a book that covers more than social network analysis?

If so, this is the book for you! With straightforward guidance on research design and data collection, as well as social network analysis, this book takes you from start to finish through the whole process of doing network research. Open the book and you'll find practical, 'how to' advice and worked examples relevant to PhD students and researchers from across the social and behavioural sciences. [...]'

' [...] This book aims at providing the first access to all these tools. It is intended as an "Atlas" because its interest is not in making you a specialist in using any of these techniques. Rather, after reading this book, you will have a general understanding of the existence and the mechanics of all these approaches. You can use such an understanding as the starting point of your own career in the field of network science. This has been, so far, an interdisciplinary endeavour. The founding fathers of this field come from many different backgrounds: mathematics, sociology, computer science, physics, history, digital humanities, and more. This Atlas is charting your path to be something different from all of that: a pure network scientist.'

' [...] Thanks for stopping by. If you’re like me, you can’t help but bookmark every R-related programming book you find in the hopes that one day you, or someone you know, might find it useful.

Hopefully this is the only bookmark you’ll need in future ;).

When I initially released this collection in late August 2020, it contained about 100 books that I’d been collecting over the previous two years. Since then I’ve found a few more and there have been contributions from many people. The collection now stands at over 300 books.

Most of these are free. Some are paid but usually quite affordable. [...]'

' A comprehensive introduction to social network analysis that hones in on basic centrality measures, social links, subgroup analysis, data sources, and more. Written by military, industry, and business professionals, this book introduces readers to social network analysis, the new and emerging topic that has recently become of significant use for industry, management, law enforcement, and military practitioners to identify vulnerabilities and opportunities in collaborative networked organizations.