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Perspectives on Social Network Research covers the proceedings of the Mathematical Social Science Board's Advanced Research Symposium on Social Networks held at Dartmouth College, Hanover, New Hampshire, on September 18-21, 1975. This symposium was organized to survey research on social networks as well as review and criticize major research thrusts involving network studies of social behavior. The book covers topics such as the Davis/Holland/Leinhardt studies, structural sociometry, network analysis of the diffusion of innovations, and the deterministic models of social networks. Also covered are topics such as structural control models for group processes, social clusters and opinion clusters, equilibrating processes in social networks, and estimation of population totals by use of snowball samples. The text is recommended for sociologists, anthropologists, and psychologists, especially those who would like to know more about social network and are currently engaged in research in that particular field.
Social Network Analysis and Education: Theory, Methods & Applications provides an introduction to the theories, methods, and applications that constitute the social network perspective. Unlike more general texts, this applied title is designed for those current and aspiring educational researchers learning how to study, conceptualize, and analyze social networks. Brian V. Carolan's main intent is to encourage you to consider the social network perspective in light of your emerging research interests and evaluate how well this perspective illuminates the social complexities surrounding educational phenomena. Relying on diverse examples drawn from the educational research literature, this book makes explicit how the theories and methods associated with social network analysis can be used to better describe and explain the social complexities surrounding varied educational phenomena.
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.
Social network analysis has transformed the study of organizations over the past 30 years.
The present work is intended to assist academics, researchers and proponents of online learning and teaching. Academics will be able to share the findings presented in this book, and the Social Networking and Education Model (SNEM), with their students (i.e. Masters and PhD). It is envisaged that this book will assist researchers and anyone interested in online learning to understand the opportunities and risks associated with the use of Social Networking in the education sector, and assist them to implement SN by means of the new SNEM model. The reader will benefit from our examinations of the risks and opportunities associated with the use of Social Networking in the education sector in various regions around the world: Asia-Pacific, Europe, Mediterranean, America, Middle East and the Caribbean. In addition, a Social Networking and Education Model (SNEM) will be developed to promote and implement Social Networking in the education sector.
Mixed Methods Social Network Analysis brings together diverse perspectives from 42 international experts on how to design, implement, and evaluate mixed methods social network analysis (MMSNA). There is an increased recognition that social networks can be important catalysts for change and transformation. This edited book from leading experts in mixed methods and social network analysis describes how researchers can conceptualize, develop, mix, and intersect diverse approaches, concepts, and tools. In doing so, they can improve their understanding and insights into the complex change processes in social networks. Section 1 includes eight chapters that reflect on "Why should we do MMSNA?", providing a clear map of MMSNA research to date and why to consider MMSNA. In Section 2 the remaining 11 chapters are dedicated to the question "How do I do MMSNA?", illustrating how concentric circles, learning analytics, qualitative structured approaches, relational event modeling, and other approaches can empower researchers. This book shows that mixing qualitative and quantitative approaches to social network analysis can empower people to understand the complexities of change in networks and relations between people. It shows how mixed analysis can be applied to a wide range of data generated by diverse global communities: American school children, Belgian teachers, Dutch medical professionals, Finnish consultants, French school children, and Swedish right-wing social media users, amongst others. It will be of great interest to researchers and postgraduate students in education and social sciences and mixed methods scholars.
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.
Social network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory, statistics, machine learning and data mining. This work covers frontier studies on social network analysis and mining from different perspectives such as social network sites, financial data, e-mails, forums, academic research funds, XML technology, blog content, community detection and clique finding, prediction of user’s- behavior, privacy in social network analysis, mobility from spatio-temporal point of view, agent technology and political parties in parliament. These topics will be of interest to researchers and practitioners from different disciplines including, but not limited to, social sciences and engineering.
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 engages the interface between the development of human lives and social relational networks. It focuses on the integration of two subfields of sociology/social science--the life course and social networks. Research practitioners studying social networks typically focus on social structure or social organization, ignoring the complex lives of the people in those networks. At the same time, life course researchers tend to focus on individual lives without necessarily studying the contexts of social relationships in which lives are embedded and “linked” to one another through social networks. These patterns are changing and this book creates an audience of researchers who will better integrate the two subfields. It covers the role of social networks across the life span, from childhood and adolescence, to midlife, through old age.