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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; and 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.
Jennifer Golbeck Ph.D Is an Associate Professor in the College of Information Studies and Director of the Human-Computer Interaction Lab at the University of Maryland, College Park. Her research interests include social network and social media analysis, recommender systems, trust on the web, human computer interaction and and how to use social relationships to improve the way people interact with information. She was named as one of IEEE Intelligent System's "Top Ten to Watch", is a Research Fellow in the Web Science Research Initiative and is a sought after speaker on social media
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- ID: 9780124055315
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