Analyzing Social Media Networks with NodeXL: Insights from a Connected World

Morgan Kaufmann
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Analyzing Social Media Networks with NodeXL offers backgrounds in information studies, computer science, and sociology. This book is divided into three parts: analyzing social media, NodeXL tutorial, and social-media network analysis case studies.

Part I provides background in the history and concepts of social media and social networks. Also included here is social network analysis, which flows from measuring, to mapping, and modeling collections of connections. The next part focuses on the detailed operation of the free and open-source NodeXL extension of Microsoft Excel, which is used in all exercises throughout this book. In the final part, each chapter presents one form of social media, such as e-mail, Twitter, Facebook, Flickr, and Youtube. In addition, there are descriptions of each system, the nature of networks when people interact, and types of analysis for identifying people, documents, groups, and events.

  • Walks you through NodeXL, while explaining the theory and development behind each step, providing takeaways that can apply to any SNA
  • Demonstrates how visual analytics research can be applied to SNA tools for the mass market
  • Includes case studies from researchers who use NodeXL on popular networks like email, Facebook, Twitter, and wikis
  • Download companion materials and resources at https://nodexl.codeplex.com/documentation
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About the author

Derek L. Hansen is an associate professor in the Information Technology program at Brigham Young University. Prior to that he was at the University of Maryland’s iSchool where he directed the Center for the Advanced Study of Communities and Information and was a member of the Human Computer Interaction Lab. Dr. Hansen completed his PhD from the University of Michigan’s School of Information where he was an NSF-funded interdisciplinary STIET Fellow focused on understanding and designing effective online socio-technical systems. Dr. Hansen’s research and teaching focuses on understanding and designing social technologies, tools, and games for the public good. He has received over $2 million in grants (as a PI or co-PI) to help develop and test novel technical interventions with interdisciplinary collaborators including educational Alternate Reality Games (AGOG, DUST, The Tessera), Playable Case Studies (Microcore), Citizen Science games (Floracaching, Odd Leaf Out), and exercise games (Fitplay Games, various pervasive play games). He has also worked with the Social Media Research Foundation and Human Computer Interaction Lab (HCIL) to develop and evaluate NodeXL, a free network analysis and visualization tool that runs in Microsoft Excel and is designed to help community analysts make sense of the mass of data available via social media tools such as Twitter, Facebook, and email.

Ben Shneiderman is a professor in the Department of Computer Science and founding director of the Human-Computer Interaction Laboratory at the University of Maryland. He was elected as a Fellow of the Association for Computing (ACM) in 1997, a Fellow of the American Association for the Advancement of Science (AAAS) in 2001, and a Fellow of the National Academy of Inventors (NAI) in 2015. He is a past recipient of the ACM SIGCHI Lifetime Achievement Award. Dr. Shneiderman is the author and coauthor of many books, technical papers, and textbooks.

Marc Smith is a sociologist specializing in the social organization of online communities and computer mediated interaction. He founded and managed the Community Technologies Group at Microsoft Research in Redmond, Washington and led the development of social media reporting and analysis tools for Telligent Systems. Smith leads the Connected Action consulting group and lives and works in Silicon Valley, California. He is a co-founder of the Social Media Research Foundation which is dedicated to Open Tools, Open Data, and Open Scholarship related to social media.

Smith’s research focuses on computer-mediated collective action: the ways group dynamics change when they take place in and through social cyberspaces. Smith’s goal is to visualize these social cyberspaces, mapping and measuring their structure, dynamics and life cycles. At Microsoft, he developed the “Netscan web application and data mining engine that allows researchers studying Usenet newsgroups and related repositories of threaded conversations to get reports on the rates of posting, posters, crossposting, thread length and frequency distributions of activity. Smith applied this work to the development of a generalized community analysis platform for Telligent, providing a web based system for groups of all sizes to discuss and publish their material to the web and analyze the emergent trends that result. Dr. Smith is an adjunct faculty at the College of Information Studies at the University of Maryland and a Distinguished Visiting Scholar at the Media-X Program at Stanford University.

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Additional Information

Publisher
Morgan Kaufmann
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Published on
Sep 14, 2010
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Pages
304
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ISBN
9780123822307
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Language
English
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Genres
Computers / Internet / General
Computers / Networking / General
Computers / Programming Languages / General
Computers / Social Aspects / Human-Computer Interaction
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Content Protection
This content is DRM protected.
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Available on Android devices
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Analyzing the Social Web

provides a framework for the analysis of public data currently available and being generated by social networks and social media, like Facebook, Twitter, and Foursquare. Access and analysis of this public data about people and their connections to one another allows for new applications of traditional social network analysis techniques that let us identify things like who are the most important or influential people in a network, how things will spread through the network, and the nature of peoples' relationships. Analyzing the Social Web introduces you to these techniques, shows you their application to many different types of social media, and discusses how social media can be used as a tool for interacting with the online public. Presents interactive social applications on the web, and the types of analysis that are currently conducted in the study of social media. Covers the basics of network structures for beginners, including measuring methods for describing nodes, edges, and parts of the network. Discusses the major categories of social media applications or phenomena and shows how the techniques presented can be applied to analyze and understand the underlying data. Provides an introduction to information visualization, particularly network visualization techniques, and methods for using them to identify interesting features in a network, generate hypotheses for analysis, and recognize patterns of behavior. Includes a supporting website with lecture slides, exercises, and downloadable social network data sets that can be used can be used to apply the techniques presented in the book.
Since the beginning of the computer age, researchers from many disciplines have sought to facilitate people's use of computers and to provide ways for scientists to make sense of the immense quantities of data coming out of them. One gainful result of these efforts has been the field of information visualization, whose technology is increasingly applied in scientific research, digital libraries, data mining, financial data analysis, market studies, manufacturing production control, and data discovery.

This book collects 38 of the key papers on information visualization from a leading and prominent research lab, the University of Maryland’s Human-Computer Interaction Lab (HCIL). Celebrating HCIL’s 20th anniversary, this book presents a coherent body of work from a respected community that has had many success stories with its research and commercial spin-offs.

Each chapter contains an introduction specifically written for this volume by two leading HCI researchers, to describe the connections among those papers and reveal HCIL’s individual approach to developing innovations.

*Presents key ideas, novel interfaces, and major applications of information visualization tools, embedded in inspirational prototypes.

*Techniques can be widely applied in scientific research, digital libraries, data mining, financial data analysis, business market studies, manufacturing production control, drug discovery, and genomic studies.

*Provides an "insider" view to the scientific process and evolution of innovation, as told by the researchers themselves.

*This work comes from the prominent and high profile University of Maryland's Human Computer Interaction Lab
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