Analyzing the Social Web

Erscheinungsjahr 2013
ISBN: 978-0-12-405531-5
Verlag: Elsevier Science & Technology

Buch, Englisch, 290 Seiten, Format (B × H): 189 mm x 233 mm, Gewicht: 518 g

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.

Zielgruppe

<p>Researchers, academics, practitioners, and students in HCI, user experience design, data Information analysts, information and data warehouse and systems engineers.</p>

Autoren/Hrsg.

Golbeck, Jennifer

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Social Media, Semantic Web, Web 2.0

Inhaltsverzeichnis

1. Introduction 2. Nodes, Edges, and Network Measures 3. Network Structure and Measures 4. Network Visualization 5. Tie Strength 6. Trust 7. Understanding Structure Through User Attributes and Behavior 8. Building Networks 9. Propagation in Networks 10. Community-Maintained Resources 11. Location-Based Social Interaction 12. Social Information Filtering 13. Social Media in the Public Sector 14. Business Use of Social Media 15. Privacy 16. Case Study: Social Network Strategies for Surviving the Zombie Apocalypse

Über Autor(innen)

Golbeck, Jennifer
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