Analyzing Social Networks

Analyzing Social Networks

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.

Author: Stephen P Borgatti

Publisher: SAGE Publications Limited

ISBN: 1526404109

Category: Social Science

Page: 384

View: 338

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 new 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.
Categories: Social Science

Analyzing Social Networks Using R

Analyzing Social Networks Using R

This approachable book introduces network research in R, walking you through every step of doing social network analysis.

Author: Stephen P. Borgatti

Publisher: Sage Publications Limited

ISBN: 1529722489

Category: Social Science

Page: 472

View: 658

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 a range of statistical models including QAP and ERGM, giving you the tools to approach different types of networks Provides a fully integrated discussion of digital data and networks like Twitter, sociolab and Amazon Offers digital resources like practice datasets and worked examples that help you get to grips with R software
Categories: Social Science

Mining and Analyzing Social Networks

Mining and Analyzing Social Networks

the second case of social media, it is people. There are many other manifestations of interconnected structures in the world where connection patterns can be described with networks. Examples of networks that exist in the real world ...

Author: I-Hsien Ting

Publisher: Springer Science & Business Media

ISBN: 9783642134210

Category: Computers

Page: 187

View: 848

Mining social networks has now becoming a very popular research area not only for data mining and web mining but also social network analysis. Data mining is a technique that has the ability to process and analyze large amount of data and by this to discover valuable information from the data. In recent year, due to the growth of social communications and social networking websites, data mining becomes a very important and powerful technique to process and analyze such large amount of data. Thus, this book will focus upon Mining and Analyzing social network. Some chapters in this book are extended from the papers that presented in MSNDS2009 (the First International Workshop on Mining Social Networks for Decision Support) and SNMABA2009 ((The International Workshop on Social Networks Mining and Analysis for Business Applications)). In addition, we also sent invitations to researchers that are famous in this research area to contribute for this book. The chapters of this book are introduced as follows: In chapter 1-Graph Model for Pattern Recognition in Text, Qin Wu et al. present a novel approach that uses a weighted directed multigraph for text pattern recognition. In the proposed methodology, a weighted directed multigraph model has been set up by using the distances between the keywords as the weights of arcs as well a keyword-frequency distance based algorithm has also been introduced. Case studies are also included in this chapter to show the performance is better than traditional means.
Categories: Computers

Analyzing Social Networks

Analyzing Social Networks

Bernard, H.R. and Killworth, P.D. (1977) Informant accuracy in social network data II. ... network flow. Social Networks, 27: 55–71. Borgatti, S.P. (2006a) E-Net Software for the Analysis of Ego-Network Data.

Author: Stephen P Borgatti

Publisher: SAGE

ISBN: 9781526418487

Category: Social Science

Page: 385

View: 724

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 new 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 edition is the perfect student-friendly introduction to social network analysis.
Categories: Social Science

Analyzing Social Networks Using R

Analyzing Social Networks Using R

American Journal of Sociology, 92: 1170–1182. Borgatti, S.P. (1994) Cultural domain analysis. Journal of Quantitative Anthropology, 4: 261–278. Borgatti, S.P. (2005) Centrality and network flow. Social Networks, 27: 55–71.

Author: Stephen P. Borgatti

Publisher: SAGE

ISBN: 9781529766585

Category: Reference

Page: 385

View: 668

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
Categories: Reference

Analyzing Social Media Networks with NodeXL

Analyzing Social Media Networks with NodeXL

Social network analysis of this data allowed Sampson to identify the future lines of division among the members of the network. The idea that members of a network can be grouped based on how densely they are connected is an important ...

Author: Derek Hansen

Publisher: Morgan Kaufmann

ISBN: 9780128177570

Category: Computers

Page: 248

View: 300

Analyzing Social Media Networks with NodeXL: Insights from a Connected World, Second Edition, provides readers with a thorough, practical and updated guide to NodeXL, the open-source social network analysis (SNA) plug-in for use with Excel. The book analyzes social media, provides a NodeXL tutorial, and presents network analysis case studies, all of which are revised to reflect the latest developments. Sections cover history and concepts, mapping and modeling, the detailed operation of NodeXL, and case studies, including e-mail, Twitter, Facebook, Flickr and YouTube. In addition, there are descriptions of each system and types of analysis for identifying people, documents, groups and events. This book is perfect for use as a course text in social network analysis or as a guide for practicing NodeXL users. Walks users through NodeXL while also explaining the theory and development behind each step Demonstrates how visual analytics research can be applied to SNA tools for the mass market Includes updated case studies from researchers who use NodeXL on popular networks like email, Facebook, Twitter, and Instagram Includes downloadable companion materials and online resources at https://www.smrfoundation.org/nodexl/teaching-with-nodexl/teaching-resources/
Categories: Computers

Social Network Analysis

Social Network Analysis

unique plague on social network studies using survey methods. ... CHAPTER 4 BASIC METHODS FOR ANALYZING NETWORKS This chapter discusses basic methods for analyzing social networks, giving equal attention to traditionally important ...

Author: David Knoke

Publisher: SAGE

ISBN: 9781412927499

Category: Social Science

Page: 145

View: 571

Providing a general overview of fundamental theoretical and methodological topics, with coverage in greater depth of selected issues, the text covers various issues in basic network concepts, data collection and network analytical methodology.
Categories: Social Science

Models and Methods in Social Network Analysis

Models and Methods in Social Network Analysis

Models and Methods in Social Network Analysis, first published in 2005, presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s.

Author: Peter J. Carrington

Publisher: Cambridge University Press

ISBN: 1139443437

Category: Social Science

Page: 354

View: 199

Models and Methods in Social Network Analysis, first published in 2005, 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.
Categories: Social Science

Social Network Analysis

Social Network Analysis

Covers methods for the analysis of social networks and applies them to examples.

Author: Stanley Wasserman

Publisher: Cambridge University Press

ISBN: 0521387078

Category: Social Science

Page: 852

View: 347

Covers methods for the analysis of social networks and applies them to examples.
Categories: Social Science

Applied Social Network Analysis With R Emerging Research and Opportunities

Applied Social Network Analysis With R  Emerging Research and Opportunities

Featuring research on topics such as network visualization, graph theory, and micro-dynamics, this book is ideally designed for researchers, practitioners, business professionals, managers, programmers, academicians, and students seeking ...

Author: Gençer, Mehmet

Publisher: IGI Global

ISBN: 9781799819141

Category: Computers

Page: 284

View: 811

Understanding the social relations within the fields of business and economics is vital for the promotion of success within a certain organization. Analytics and statistics have taken a prominent role in marketing and management practices as professionals are constantly searching for a competitive advantage. Converging these technological tools with traditional methods of business relations is a trending area of research. Applied Social Network Analysis With R: Emerging Research and Opportunities is an essential reference source that materializes and analyzes the issue of structure in terms of its effects on human societies and the state of the individuals in these communities. Even though the theme of the book is business-oriented, an approach underlining and strengthening the ties of this field of study with social sciences for further development is adopted throughout. Therefore, the knowledge presented is valid for analyzing not only the organization of the business world but also for the organization of any given community. Featuring research on topics such as network visualization, graph theory, and micro-dynamics, this book is ideally designed for researchers, practitioners, business professionals, managers, programmers, academicians, and students seeking coverage on analyzing social and business networks using modern methods of statistics, programming, and data sets.
Categories: Computers