Social Networking and Community Behavior Modeling: Qualitative and Quantitative Measures provides a clear and consolidated view of current social network models. This work explores new methods for modeling, characterizing, and constructing social networks. Chapters contained in this book study critical security issues confronting social networking, the emergence of new mobile social networking devices and applications, network robustness, and how social networks impact the business aspects of organizations.

This open access book applies insights from the network perspective in health research to explain the reproduction of health inequalities. It discusses the extant literature in this field that strongly correlates differences in social status with health behaviours and outcomes, and add to this literature by providing a coherent theoretical explanation for the causes of these health inequalities. It also shows that much research is needed on the precise factors and the social and socio-psychological mechanisms that are at play in creating and cementing social inequalities in health behaviours. While social support and social relations have received considerable attention within social and behavioural science research on health inequalities, this book considers the whole network of interpersonal relations, structures and influence mechanisms. This is the perspective of the social network analytical approach which has recently gained much attention in health research. The chapters of this book cover state-of-the-art research, open research questions, and perspectives for future research. The book provides network analyses on health inequalities from the perspective of sociology, psychology, and public health and is of interest to a wide range of scholars, students and practitioners trying to understand how health inequalities are reproduced across generations.

Complete proceedings of the 2nd European Conference on Social Media Porto Portugal Published by Academic Conferences and Publishing International Limited

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 Second 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 text is the perfect student-friendly introduction to social network analysis.

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.

Data mining continues to be an emerging interdisciplinary field that offers the ability to extract information from an existing data set and translate that knowledge for end-users into an understandable way. Data Mining: Concepts, Methodologies, Tools, and Applications is a comprehensive collection of research on the latest advancements and developments of data mining and how it fits into the current technological world.

With higher education turning towards data analytics as the next big advance in technology, it is important to look at how information is gathered and visualized for accurate comprehension, analysis, and decision-making. Packaging Digital Information for Enhanced Learning and Analysis: Data Visualization, Spatialization, and Multidimensionality brings together effective practices for the end-to-end capture and web based presentation of information for comprehension, analysis, and decision-making. This publication is beneficial for educators, trainers, instructional designers, web designers, and graduate students interested in improving analytical tools.