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Written by a stellar team of experts, Analyzing Social Networks is a practical book on how to collect, visualize, analyze and interpret social network data with a particular emphasis on the use of the software tools UCINET and Netdraw. The book includes a clear and detailed introduction to the fundamental concepts of network analyses, including centrality, subgroups, equivalence and network structure, as well as cross-cutting chapters that helpfully show how to apply network concepts to different kinds of networks. Written using simple language and notation with few equations, this book masterfully covers the research process, including: · The initial design stage · Data collection and man...
‘Network’ is a heavily overloaded term, so that ‘network analysis’ means different things to different people. Specific forms of network analysis are used in the study of diverse structures such as the Internet, interlocking directorates, transportation systems, epidemic spreading, metabolic pathways, the Web graph, electrical circuits, project plans, and so on. There is, however, a broad methodological foundation which is quickly becoming a prerequisite for researchers and practitioners working with network models. From a computer science perspective, network analysis is applied graph theory. Unlike standard graph theory books, the content of this book is organized according to methods for specific levels of analysis (element, group, network) rather than abstract concepts like paths, matchings, or spanning subgraphs. Its topics therefore range from vertex centrality to graph clustering and the evolution of scale-free networks. In 15 coherent chapters, this monograph-like tutorial book introduces and surveys the concepts and methods that drive network analysis, and is thus the first book to do so from a methodological perspective independent of specific application areas.
Models and Methods in Social Network Analysis presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s. Intended as a complement to Wasserman and Faust's Social Network Analysis: Methods and Applications, it is a collection of articles by leading methodologists reviewing advances in their particular areas of network methods. Reviewed are advances in network measurement, network sampling, the analysis of centrality, positional analysis or blockmodelling, the analysis of diffusion through networks, the analysis of affiliation or 'two-mode' networks, the theory of random graphs, dependence graphs, exponential families of random graphs, the analysis of longitudinal network data, graphical techniques for exploring network data, and software for the analysis of social networks.
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
Models and Methods in Social Network Analysis, first published in 2005, presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s. Intended as a complement to Wasserman and Faust's Social Network Analysis: Methods and Applications, it is a collection of articles by leading methodologists reviewing advances in their particular areas of network methods. Reviewed are advances in network measurement, network sampling, the analysis of centrality, positional analysis or blockmodelling, the analysis of diffusion through networks, the analysis of affiliation or 'two-mode' networks, the theory of random graphs, dependence graphs, exponential families of random graphs, the analysis of longitudinal network data, graphical techniques for exploring network data, and software for the analysis of social networks.
It's not what you know, it's who you know. Or so the adage goes. Professor Matthew Jackson, world-leading researcher into social and economic networks, shows us why this is far truer than we'd like to believe. Based on his ground-breaking research, The Human Network reveals how our relationships in school, university, work and society have extraordinary implications throughout our lives and demonstrates that by understanding and taking advantage of these networks, we can boost our happiness, success and influence. But there are also wider lessons to be learnt. Drawing on concepts from economics, mathematics, sociology, and anthropology, Jackson reveals how the science of networks gives us a bold new framework to understand human interaction writ large - from banking crashes and viral marketing to racism and the spread of disease. Filled with counter-intuitive ideas that will enliven any dinner party - e.g. how can our popularity in school affect us for the rest of our lives? - The Human Network is a "big ideas" book that no one can afford to miss.
This excellent new volume in the series from the Society for Economic Anthropology focuses on the role of labor in world economies. Contributors offer a range of case studies illustrating labor processes in both western and nonwestern societies. Individual sections include discussions on household labor, firms and corporatations, and state and transnational conditions. This book will be a valuable resource for scholars, students, and interested readers of international economics, anthropology, development issues, labor studies, and sociology.
William Burnside was one of the three most important algebraists who were involved in the transformation of group theory from its nineteenth-century origins to a deep twentieth-century subject. Building on work of earlier mathematicians, they were able to develop sophisticated tools for solving difficult problems. All of Burnside's papers are reproduced here, organized chronologically and with a detailed bibliography. Walter Feit has contributed a foreword, and a collection of introductory essays are included to provide a commentary on Burnside's work and set it in perspective along with a modern biography that draws on archive material.
An in-depth, comprehensive and practical guide to egocentric network analysis, focusing on fundamental theoretical, research design, and analytic issues.
A venture into the art and science of measuring religion in everyday life In an era of rapid technological advances, the measures and methods used to generate data about religion have undergone remarkably little change. Faithful Measures pushes the study of religion into the 21st century by evaluating new and existing measures of religion and introducing new methods for tapping into religious behaviors and beliefs. This book offers a global and innovative approach, with chapters on the intersection of religion and new technology, such as smart phone apps, Google Ngrams, crowdsourcing data, and Amazon buying networks. It also shows how old methods can be improved by using new technology to create online surveys with experimental designs and by developing new ways of mining data from existing information. Chapter contributors thoroughly explain how to employ these new techniques, and offer fresh insights into understanding the complex topic of religion in modern life. Beyond its quantitative contributions, Faithful Measures will be an invaluable resource for inspiring a new wave of creativity and exploration in our connected world.