Multilevel Network Analysis for the Social Sciences

Multilevel Network Analysis for the Social Sciences

Author: Emmanuel Lazega

Publisher: Springer

Published: 2015-12-16

Total Pages: 373

ISBN-13: 3319245201

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This volume provides new insights into the functioning of organizational, managerial and market societies. Multilevel analysis and social network analysis are described and the authors show how they can be combined in developing the theory, methods and empirical applications of the social sciences. This book maps out the development of multilevel reasoning and shows how it can explain behavior, through two different ways of contextualizing it. First, by identifying levels of influence on behavior and different aggregations of actors and behavior, and complex interactions between context and behavior. Second, by identifying different levels as truly different systems of agency: such levels of agency can be examined separately and jointly since the link between them is affiliation of members of one level to collective actors at the superior level. It is by combining these approaches that this work offers new insights. New case studies and datasets that explore new avenues of theorizing and new applications of methodology are presented. This book will be useful as a reference work for all social scientists, economists and historians who use network analyses and multilevel statistical analyses. Philosophers interested in the philosophy of science or epistemology will also find this book valuable. ​


The Sage Handbook of Social Network Analysis

The Sage Handbook of Social Network Analysis

Author: John McLevey

Publisher: SAGE Publications Limited

Published: 2023-10-01

Total Pages: 951

ISBN-13: 152961466X

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This new edition of The Sage Handbook of Social Network Analysis builds on the success of its predecessor, offering a comprehensive overview of social network analysis produced by leading international scholars in the field. Brand new chapters provide both significant updates to topics covered in the first edition, as well as discussing cutting edge topics that have developed since, including new chapters on: · General issues such as social categories and computational social science; · Applications in contexts such as environmental policy, gender, ethnicity, cognition and social media and digital networks; · Concepts and methods such as centrality, blockmodeling, multilevel network analysis, spatial analysis, data collection, and beyond. By providing authoritative accounts of the history, theories and methodology of various disciplines and topics, the second edition of The SAGE Handbook of Social Network Analysis is designed to provide a state-of-the-art presentation of classic and contemporary views, and to lay the foundations for the further development of the area. PART 1: GENERAL ISSUES PART 2: APPLICATIONS PART 3: CONCEPTS AND METHODS


Egocentric Network Analysis

Egocentric Network Analysis

Author: Brea L. Perry

Publisher: Structural Analysis in the Soc

Published: 2018-03-22

Total Pages: 371

ISBN-13: 110713143X

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An in-depth, comprehensive and practical guide to egocentric network analysis, focusing on fundamental theoretical, research design, and analytic issues.


Social Network Analysis

Social Network Analysis

Author: David Knoke

Publisher: SAGE Publications

Published: 2019-12-02

Total Pages: 214

ISBN-13: 1506389309

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David Knoke and Song Yang's Social Network Analysis, Third Edition provides a concise introduction to the concepts and tools of social network analysis. The authors convey key material while at the same time minimizing technical complexities. The examples are simple: sets of 5 or 6 entities such as individuals, positions in a hierarchy, political offices, and nation-states, and the relations between them include friendship, communication, supervision, donations, and trade. The new edition reflects developments and changes in practice over the past decade. The authors also describe important recent developments in network analysis, especially in the fifth chapter. Exponential random graph models (ERGMs) are a prime example: when the second edition was published, P* models were the recommended approach for this, but they have been replaced by ERGMs. Finally, throughout the volume, the authors comment on the challenges and opportunities offered by internet and social media data.


Network Analysis

Network Analysis

Author: Craig M. Rawlings

Publisher: Cambridge University Press

Published: 2023-09-30

Total Pages: 477

ISBN-13: 1009453947

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For both students and professionals seeking to understand the burgeoning field of network analysis, our text offers a comprehensive overview that integrates theory, method, and cutting-edge application with R (a free platform that is becoming the standard for the field).


Social Network Analysis

Social Network Analysis

Author: Mohammad Gouse Galety

Publisher: John Wiley & Sons

Published: 2022-04-28

Total Pages: 260

ISBN-13: 1119836735

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SOCIAL NETWORK ANALYSIS As social media dominates our lives in increasing intensity, the need for developers to understand the theory and applications is ongoing as well. This book serves that purpose. Social network analysis is the solicitation of network science on social networks, and social occurrences are denoted and premeditated by data on coinciding pairs as the entities of opinion. The book features: Social network analysis from a computational perspective using python to show the significance of fundamental facets of network theory and the various metrics used to measure the social network. An understanding of network analysis and motivations to model phenomena as networks. Real-world networks established with human-related data frequently display social properties, i.e., patterns in the graph from which human behavioral patterns can be analyzed and extracted. Exemplifies information cascades that spread through an underlying social network to achieve widespread adoption. Network analysis that offers an appreciation method to health systems and services to illustrate, diagnose, and analyze networks in health systems. The social web has developed a significant social and interactive data source that pays exceptional attention to social science and humanities research. The benefits of artificial intelligence enable social media platforms to meet an increasing number of users and yield the biggest marketplace, thus helping social networking analysis distribute better customer understanding and aiding marketers to target the right customers. Audience The book will interest computer scientists, AI researchers, IT and software engineers, mathematicians.


Challenges in Social Network Research

Challenges in Social Network Research

Author: Giancarlo Ragozini

Publisher: Springer Nature

Published: 2019-12-06

Total Pages: 245

ISBN-13: 3030314634

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The book includes both invited and contributed chapters dealing with advanced methods and theoretical development for the analysis of social networks and applications in numerous disciplines. Some authors explore new trends related to network measures, multilevel networks and clustering on networks, while other contributions deepen the relationship among statistical methods for data mining and social network analysis. Along with the new methodological developments, the book offers interesting applications to a wide set of fields, ranging from the organizational and economic studies, collaboration and innovation, to the less usual field of poetry. In addition, the case studies are related to local context, showing how the substantive reasoning is fundamental in social network analysis. The list of authors includes both top scholars in the field of social networks and promising young researchers. All chapters passed a double blind review process followed by the guest editors. This edited volume will appeal to students, researchers and professionals.


Inferential Network Analysis

Inferential Network Analysis

Author: Skyler J. Cranmer

Publisher: Cambridge University Press

Published: 2020-11-19

Total Pages: 317

ISBN-13: 1107158125

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Pioneering introduction of unprecedented breadth and scope to inferential and statistical methods for network analysis.


The Oxford Handbook of Social Networks

The Oxford Handbook of Social Networks

Author: Ryan Light

Publisher: Oxford University Press

Published: 2020-11-20

Total Pages: 768

ISBN-13: 0190251778

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While some social scientists may argue that we have always been networked, the increased visibility of networks today across economic, political, and social domains can hardly be disputed. Social networks fundamentally shape our lives and social network analysis has become a vibrant, interdisciplinary field of research. In The Oxford Handbook of Social Networks, Ryan Light and James Moody have gathered forty leading scholars in sociology, archaeology, economics, statistics, and information science, among others, to provide an overview of the theory, methods, and contributions in the field of social networks. Each of the thirty-three chapters in this Handbook moves through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. They cover both a succinct background to, and future directions for, distinctive approaches to analyzing social networks. The first section of the volume consists of theoretical and methodological approaches to social networks, such as visualization and network analysis, statistical approaches to networks, and network dynamics. Chapters in the second section outline how network perspectives have contributed substantively across numerous fields, including public health, political analysis, and organizational studies. Despite the rapid spread of interest in social network analysis, few volumes capture the state-of-the-art theory, methods, and substantive contributions featured in this volume. This Handbook therefore offers a valuable resource for graduate students and faculty new to networks looking to learn new approaches, scholars interested in an overview of the field, and network analysts looking to expand their skills or substantive areas of research.