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Analyzing Social Networks
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...
Analyzing Social Networks
Designed to walk beginners through core aspects of collecting, visualizing, analyzing, and interpreting social network data, this book will get you up-to-speed on the theory and skills you need to conduct social network analysis. Using simple language and equations, the authors provide expert, clear insight into every step of the research process -- including basic maths principles -- without making assumptions about what you know. With a particular focus on NetDraw and UCINET, the book introduces relevant software tools step-by-step in an easy to follow way. In addition to the fundamentals of network analysis and the research process, this new edition focuses on: Digital data and social networks like Twitter Statistical models to use in SNA, like QAP and ERGM The structure and centrality of networks Methods for cohesive subgroups/community detection Supported by new chapter exercises, a glossary, and a fully updated companion website, this edition is the perfect student-friendly introduction to social network analysis.
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 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
Models and Methods in Social Network Analysis
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.
Network Analysis
‘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.
Empowering Knowledge Workers
Empowering Knowledge Workers describes the work of managers, decision makers, executives, doctors, lawyers, campaign managers, emergency responders, strategists, and many others who have to think for a living. These are people who figure out what needs to be done, at the same time that they do it, and a new approach to support this kind of worker presents the logical starting point for understanding how to take advantage of ACM.
Network Analysis
A comprehensive yet accessible introduction to the theory, methods, and application of social network analysis.
Gentlemen Bankers
This account of the Morgan family’s social and economic circles and Wall Street’s unspoken rules “greatly enriches our understanding of the entire era.” —The Wall Street Journal Gentlemen Bankers investigates the social and economic circles of one of America’s most renowned and influential financiers to uncover how the Morgan family’s power and prestige stemmed from its unique position within a network of local and international relationships. At the turn of the twentieth century, private banking was a personal enterprise in which business relationships were a statement of identity and reputation. In an era when ethnic and religious differences were pronounced and anti-Semitism...
Knowledge, Power, and Networks
In the past decades, the world has watched the rise of China as an economic and military power and the emergence of Chinese transnational elites. What may seem like an entirely new phenomenon marks the revival of a trend initiated at the end of the Qing. The redistribution of power, wealth and knowledge among the newly formed elites matured during the Republican period. This volume demonstrates both the difficulty and the value of re-thinking the elites in modern China. It establishes that the study of the dynamic tensions within the elite and among elite groups in this epochal era is within reach if we are prepared to embrace forms of historical inquiry that integrate the abundant and even limitless historical resources, and to engage with the rich repertoire of digital techniques/instruments available and question our previous research paradigms. This renewed approach brings historical research closer to an integrative data-rich history of modern China.
Exploring Big Historical Data: The Historian's Macroscope
The Digital Humanities have arrived at a moment when digital Big Data is becoming more readily available, opening exciting new avenues of inquiry but also new challenges. This pioneering book describes and demonstrates the ways these data can be explored to construct cultural heritage knowledge, for research and in teaching and learning. It helps humanities scholars to grasp Big Data in order to do their work, whether that means understanding the underlying algorithms at work in search engines, or designing and using their own tools to process large amounts of information.Demonstrating what digital tools have to offer and also what 'digital' does to how we understand the past, the authors in...
