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Social network analysis (SNA) has become a major paradigm for social research in such areas as communication, organizations, and social mobility. It is used by researchers in a wide range of disciplines: like any mathematical approach to social research, social network analysis strips away the unique details of social situations to reveal, or model, the bare structural essentials. This work is dedicated specifically to the applications of social network analysis in diverse fields of scholarship

Semantic Network Analysis in Social Sciences introduces the fundamentals of semantic network analysis and its applications in the social sciences. Readers learn how to easily transform any given text into a visual network of words co-occurring together, a process that allows mapping the main themes appearing in the text and revealing its main narratives and biases. Semantic network analysis is particularly useful today with the increasing volumes of text-based information available. It is one of the developing, cutting-edge methods to organize, identify patterns and structures, and understand the meanings of our information society. The first chapters in this book offer step-by-step guidelines for conducting semantic network analysis, including choosing and preparing the text, selecting desired words, constructing the networks, and interpreting their meanings. Free software tools and code are also presented. The rest of the book displays state-of-the-art studies from around the world that apply this method to explore news, political speeches, social media content, and even to organize interview transcripts and literature reviews. Aimed at scholars with no previous knowledge in the field, this book can be used as a main or a supplementary textbook for general courses on research methods or network analysis courses, as well as a starting point to conduct your own content analysis of large texts.

Social Science Data Archives: A Historical Social Network Analysis

The main target of this book is to raise the awareness about social networking systems design, implementation, security requirements, and approaches. The book entails related issues including computing, engineering, security, management, and organization policy. It interprets the design, implementation and security threats in the social networks and offers some solutions in this concern. It clarifies the authentication concept between servers to identity users. Most of the models that focus on protecting users' information are also included. This book introduces the Human-Interactive Security Protocols (HISPs) efficiently. Presenting different types of the social networking systems including the internet and mobile devices is one of the main targets of this book. This book includes the social network performance evaluation metrics. It compares various models and approaches used in the design of the social networks. This book includes various applications for the use of the social networks in the healthcare, e-commerce, crisis management, and academic applications. The book provides an extensive background for the development of social network science and its challenges. This book discusses the social networks integration to offer online services, such as instant messaging, email, file sharing, transferring patients' medical reports/images, location-based recommendations and many other functions. This book provides users, designers, engineers and managers with the valuable knowledge to build a better secured information transfer over the social networks. The book gathers remarkable materials from an international experts' panel to guide the readers during the analysis, design, implementation and security achievement for the social network systems. In this book, theories, practical guidance, and challenges are included to inspire designers and researchers. The book guides the engineers, designers, and researchers to exploit the intrinsic design of the social network systems.

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.

Political science is fascinated with networks. This fascination builds on networks' descriptive appeal, and descriptions of networks play a prominent role in recent forays into network analysis. For some time, quantitative research has included node-level measures of network characteristics in standard regression models, thereby incorporating network concepts into familiar models. This approach represents an early advance for the literature but may (a) ignore fundamental theoretical contributions that can be found in a more structurally oriented network perspective, (b) focus attention on superficial aspects of networks as they feed into empirical work, and (c) present the network perspective as a slight tweak to standard models that assume complete independence of all relevant actors. We argue that network analysis is more than a tweak to the status quo ante; rather, it offers a means of addressing one of the holy grails of the social sciences: effectively analyzing the interdependence and flows of influence among individuals, groups, and institutions. Adapted from the source document.

"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"--

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