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

Ben Shneiderman is a professor in the Department of Computer Science, head of the Human-Computer Interaction Laboratory, and member of the Institutes for Advanced Computer Studies and Systems Research at the University of Maryland, College Park. He is the author and coauthor of many books, technical papers, and textbooks.

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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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Ben Shneiderman
Jennifer Golbeck

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.
Ben Shneiderman
Ben Shneiderman
Bill Ferster
Benjamin B. Bederson
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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