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Author: Peter J. Carrington Publisher: ISBN: 9780521809597 Category : Psychology Languages : en Pages : 328
Book Description
Models and Methods in Social Network Analysis presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s. Intended as a complement to Wasserman and Faust's Social Network Analysis: Methods and Applications, it is a collection of articles by leading methodologists reviewing advances in their particular areas of network methods. Reviewed are advances in network measurement, network sampling, the analysis of centrality, positional analysis or blockmodelling, the analysis of diffusion through networks, the analysis of affiliation or 'two-mode' networks, the theory of random graphs, dependence graphs, exponential families of random graphs, the analysis of longitudinal network data, graphical techniques for exploring network data, and software for the analysis of social networks.
Author: Peter J. Carrington Publisher: ISBN: 9780521809597 Category : Psychology Languages : en Pages : 328
Book Description
Models and Methods in Social Network Analysis presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s. Intended as a complement to Wasserman and Faust's Social Network Analysis: Methods and Applications, it is a collection of articles by leading methodologists reviewing advances in their particular areas of network methods. Reviewed are advances in network measurement, network sampling, the analysis of centrality, positional analysis or blockmodelling, the analysis of diffusion through networks, the analysis of affiliation or 'two-mode' networks, the theory of random graphs, dependence graphs, exponential families of random graphs, the analysis of longitudinal network data, graphical techniques for exploring network data, and software for the analysis of social networks.
Author: Mohammad Gouse Galety Publisher: John Wiley & Sons ISBN: 1119836735 Category : Technology & Engineering Languages : en Pages : 260
Book Description
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.
Author: S. K. Bhatnagar Publisher: Prentice Hall ISBN: Category : Business & Economics Languages : en Pages : 280
Book Description
This book deals with various techniques that use basic concepts of preparation and analysis of networks for planning, scheduling and control of Projects.
Author: Wouter van Atteveldt Publisher: ISBN: Category : Social Science Languages : en Pages : 256
Book Description
This books describes a number of techniques that have been developed to facilitate Semantic Network Analysis. It describes techniques to automatically extract networks using co-occurrence, grammatical analysis, and sentiment analysis using machine learning. Additionally, it describes techniques to represent the extracted semantic networks and background knowledge about the actors and issues in the network, using Semantic Web techniques to deal with multiple issue categorisations and political roles and functions that shift over time. It shows how this combined network of message content and background knowledge can be queried and visualized to make it easy to answer a variety of research questions. Finally, this book describes the AmCAT infrastructure and iNet coding program for that have been developed to facilitate managing large automatic and manual content analysis projects.
Author: Katharina A. Zweig Publisher: Springer Science & Business Media ISBN: 3709107415 Category : Computers Languages : en Pages : 535
Book Description
This book presents a perspective of network analysis as a tool to find and quantify significant structures in the interaction patterns between different types of entities. Moreover, network analysis provides the basic means to relate these structures to properties of the entities. It has proven itself to be useful for the analysis of biological and social networks, but also for networks describing complex systems in economy, psychology, geography, and various other fields. Today, network analysis packages in the open-source platform R and other open-source software projects enable scientists from all fields to quickly apply network analytic methods to their data sets. Altogether, these applications offer such a wealth of network analytic methods that it can be overwhelming for someone just entering this field. This book provides a road map through this jungle of network analytic methods, offers advice on how to pick the best method for a given network analytic project, and how to avoid common pitfalls. It introduces the methods which are most often used to analyze complex networks, e.g., different global network measures, types of random graph models, centrality indices, and networks motifs. In addition to introducing these methods, the central focus is on network analysis literacy – the competence to decide when to use which of these methods for which type of question. Furthermore, the book intends to increase the reader's competence to read original literature on network analysis by providing a glossary and intensive translation of formal notation and mathematical symbols in everyday speech. Different aspects of network analysis literacy – understanding formal definitions, programming tasks, or the analysis of structural measures and their interpretation – are deepened in various exercises with provided solutions. This text is an excellent, if not the best starting point for all scientists who want to harness the power of network analysis for their field of expertise.
Author: Stephen P. Borgatti Publisher: SAGE ISBN: 1529765757 Category : Social Science Languages : en Pages : 332
Book Description
This approachable book introduces network research in R, walking you through every step of doing social network analysis. Drawing together research design, data collection and data analysis, it explains the core concepts of network analysis in a non-technical way. The book balances an easy to follow explanation of the theoretical and statistical foundations underpinning network analysis with practical guidance on key steps like data management, preparation and visualisation. With clarity and expert insight, it: • Discusses measures and techniques for analyzing social network data, including digital media • Explains a range of statistical models including QAP and ERGM, giving you the tools to approach different types of networks • Offers digital resources like practice datasets and worked examples that help you get to grips with R software
Author: Krishna Raj P.M. Publisher: Springer ISBN: 3319967460 Category : Computers Languages : en Pages : 329
Book Description
This book focuses on social network analysis from a computational perspective, introducing readers to the fundamental aspects of network theory by discussing the various metrics used to measure the social network. It covers different forms of graphs and their analysis using techniques like filtering, clustering and rule mining, as well as important theories like small world phenomenon. It also presents methods for identifying influential nodes in the network and information dissemination models. Further, it uses examples to explain the tools for visualising large-scale networks, and explores emerging topics like big data and deep learning in the context of social network analysis. With the Internet becoming part of our everyday lives, social networking tools are used as the primary means of communication. And as the volume and speed of such data is increasing rapidly, there is a need to apply computational techniques to interpret and understand it. Moreover, relationships in molecular structures, co-authors in scientific journals, and developers in a software community can also be understood better by visualising them as networks. This book brings together the theory and practice of social network analysis and includes mathematical concepts, computational techniques and examples from the real world to offer readers an overview of this domain.
Author: Douglas Luke Publisher: Springer ISBN: 3319238833 Category : Mathematics Languages : en Pages : 238
Book Description
Presenting a comprehensive resource for the mastery of network analysis in R, the goal of Network Analysis with R is to introduce modern network analysis techniques in R to social, physical, and health scientists. The mathematical foundations of network analysis are emphasized in an accessible way and readers are guided through the basic steps of network studies: network conceptualization, data collection and management, network description, visualization, and building and testing statistical models of networks. As with all of the books in the Use R! series, each chapter contains extensive R code and detailed visualizations of datasets. Appendices will describe the R network packages and the datasets used in the book. An R package developed specifically for the book, available to readers on GitHub, contains relevant code and real-world network datasets as well.
Author: Stanley Wasserman Publisher: Cambridge University Press ISBN: 9780521387071 Category : Social Science Languages : en Pages : 852
Book Description
Social network analysis is used widely in the social and behavioral sciences, as well as in economics, marketing, and industrial engineering. The social network perspective focuses on relationships among social entities and is an important addition to standard social and behavioral research, which is primarily concerned with attributes of the social units. Social Network Analysis: Methods and Applications reviews and discusses methods for the analysis of social networks with a focus on applications of these methods to many substantive examples. It is a reference book that can be used by those who want a comprehensive review of network methods, or by researchers who have gathered network data and want to find the most appropriate method by which to analyze it. It is also intended for use as a textbook as it is the first book to provide comprehensive coverage of the methodology and applications of the field.
Author: Peter J. Carrington
Author: Peter J. Carrington
Author: Mohammad Gouse Galety
Author: S. K. Bhatnagar
Author: Wouter van Atteveldt
Author: Katharina A. Zweig
Author: Stephen P. Borgatti
Author: Krishna Raj P.M.
Author: John Scott
Author: Douglas Luke
Author: Stanley Wasserman