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Jennifer Golbeck - Analyzing the Social Web, Häftad

Häftad, Engelska, 2013

Analyzing the Social Web

Av Jennifer Golbeck

649 kr

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Beskrivning
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
Produktinformation
  • Utgivningsdatum: 2013-04-18
  • Mått: 191 x 235 x 14 mm
  • Vikt: 510 g
  • Format: Häftad
  • Språk: Engelska
  • Antal sidor: 290
  • Förlag: Elsevier Science
  • ISBN: 9780124055315
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Mer information

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

Recensioner i media

"This…aims to integrate a number of approaches to social network analysis that have been proposed in a variety of disciplines, such as mathematics, computer science, sociology, and biology, to develop a unified framework…this is a nice introductory textbook for social network analysis, with lots of examples and use cases and a clear explanation of the basic concepts and techniques used in this field." --ComputingReviews.com, November 27, 2013"Techniques from the natural sciences, social sciences, computer science and mathematics are used to describe and visualize social relationships and quantify connectedness. The utility of such analysis is then explored through case studies, pointing out both the potential malicious use of publicly shared information and pro-social uses of network analysis to combat online dangers." --Reference and Research Book News, October 2013"…it is a carefully crafted explanation of the subject, made readable through the use of interesting and sometimes entertaining examples of applications to the social web…The book will be of interest to those seeking a largely non-mathematical introduction to network analysis, whether for application to the social web or not." --BCS.org, September 2013"This is the first book that empowers students from across the disciplines to delve into the secrets of social networks. It is a pedagogic masterpiece in which Jen Golbeck demonstrates her research talent and dedication to teaching." --Jennifer J. Preece, Professor and Dean, College of Information Studies, University of Maryland

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