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Relationships and the pattern of relationships have a large and varied influence on both individual and group action. The fundamental distinction of social network analysis research is that relationships are of paramount importance in explaining behavior. Because of this, social network analysis offers many exciting tools and techniques for research and practice in a wide variety of medical and public health situations including organizational improvements, understanding risk behaviors, coordinating coalitions, and the delivery of health care services. This book provides an introduction to the major theories, methods, models, and findings of social network analysis research and application. In three sections, it presents a comprehensive overview of the topic; first in a survey of its historical and theoretical foundations, then in practical descriptions of the variety of methods currently in use, and finally in a discussion of its specific applications for behavior change in a public health context. Throughout, the text has been kept clear, concise, and comprehensible, with short mathematical formulas for some key indicators or concepts. Researchers and students alike will find it an invaluable resource for understanding and implementing social network analysis in their own practice.
The scientific study of networks - computer, social, and biological - has received an enormous amount of interest in recent years. However, the network approach has been applied to the field of animal behaviour relatively late compared to many other biological disciplines. Understanding social network structure is of great importance for biologists since the structural characteristics of any network will affect its constituent members and influence a range of diverse behaviours. These include finding and choosing a sexual partner, developing and maintaining cooperative relationships, and engaging in foraging and anti-predator behavior. This novel text provides an overview of the insights that network analysis has provided into major biological processes, and how it has enhanced our understanding of the social organisation of several important taxonomic groups. It brings together researchers from a wide range of disciplines with the aim of providing both an overview of the power of the network approach for understanding patterns and process in animal populations, as well as outlining how current methodological constraints and challenges can be overcome. Animal Social Networks is principally aimed at graduate level students and researchers in the fields of ecology, zoology, animal behaviour, and evolutionary biology but will also be of interest to social scientists.
Understanding Social Networks explains the big ideas that underlie social networks, covering fundamental concepts then discussing networks and their core themes in increasing order of complexity.
Dark networks are the illegal and covert networks (e.g, insurgents, jihadi groups, or drug cartels) that security and intelligence analysts must track and identify to be able to disrupt and dismantle them. This text explains how this can be done by using the Social Network Analysis (SNA) method. Written in an accessible manner, it provides an introduction to SNA, presenting tools and concepts, and showing how SNA can inform the crafting of a wide array of strategies for the tracking and disrupting of dark networks.
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 book addresses the issue of interdisciplinary understanding of collaboration on the topic of social network studies. Researchers and practitioners from various disciplines including sociology, computer science, socio-psychology, public health, complex systems, and management science have worked largely independently, each with quite different principles, terminologies, theories. and methodologies. The book aims to fill the gap among these disciplines with a number of the latest interdisciplinary collaboration studies.
We live in a world that is paradoxically both small and vast; each of us is embedded in local communities and yet we are only a few 'links' away from anyone else in the world. This engaging book represents these interdependencies' positive and negative consequences, their multiple effects and the ways in which a local occurrence in one part of the world can directly affect the rest. Then it demonstrates precisely how these interactions and relationships form. This is a book for the social network novice learning how to study, think about and analyse social networks; the intermediate user, not yet familiar with some of the newer developments in the field; and the teacher looking for a range of exercises, as well as an up-to-date historical account of the field. It is divided into three clear sections: 1. historical & Background Concepts 2. Levels of Analysis 3. Advances, Extensions and Conclusions The book provides a full overview of the field - historical origins, common theoretical perspectives and frameworks; traditional and current analytical procedures and fundamental mathematical equations needed to get a foothold in the field. Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.
This volume is directed toward researchers and health professionals with an interest in the interstices of social networks and health. It consists of original papers that address critical themes in health-related social network research and disease prevention.
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.
This book is open access under a CC BY-NC 3.0 IGO license. This book comprehensively covers topics in knowledge management and competence in strategy development, management techniques, collaboration mechanisms, knowledge sharing and learning, as well as knowledge capture and storage. Presented in accessible “chunks,” it includes more than 120 topics that are essential to high-performance organizations. The extensive use of quotes by respected experts juxtaposed with relevant research to counterpoint or lend weight to key concepts; “cheat sheets” that simplify access and reference to individual articles; as well as the grouping of many of these topics under recurrent themes make this book unique. In addition, it provides scalable tried-and-tested tools, method and approaches for improved organizational effectiveness. The research included is particularly useful to knowledge workers engaged in executive leadership; research, analysis and advice; and corporate management and administration. It is a valuable resource for those working in the public, private and third sectors, both in industrialized and developing countries.