Computational Social Science

Herausgeber: Alvarez, R. Michael

• Broschiertes Buch

Produktbeschreibung

This book serves as an introduction to the field of computational social science for academics, students, and practitioners. It will also appeal to data scientists who wish to learn about innovations in the area, in particular those interested in how data analytics is applied to study social behavior.

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Produktdetails

• Analytical Methods for Social Research
• Verlag: Cambridge University Press
• Seitenzahl: 338
• Erscheinungstermin: 7. Juni 2017
• Englisch
• Abmessung: 229mm x 152mm x 19mm
• Gewicht: 494g
• ISBN-13: 9781107518414
• ISBN-10: 1107518415
• Artikelnr.: 43857277

Inhaltsangabe

Preface Gary King; Introduction R. Michael Alvarez; Part I. Computation
Social Science Tools: 1. The application of big data in surveys to the
study of public opinion, elections, and representation Christopher Warshaw;
2. Navigating the local modes of big data: the case of topic models
Margaret Roberts, Brandon Stewart and Dustin Tingley; 3. Generating
political event data in near real time: opportunities and challenges John
Beieler, Patrick T. Brandt, Andrew Halterman, Philip A. Schrodt and Erin M.
Simpson; 4. Network structure and social outcomes: network analysis for
social science Betsy Sinclair; 5. Ideological salience in multiple
dimensions Peter Foley; 6. Random forest applied to feature selection in
biomedical research Daniel Conn and Christina Ramirez; Part II. Computation
Social Science Applications: 7. Big data, social media, and protest:
foundations for a research agenda Joshua Tucker, Jonathan Nagler, Megan
Metzger, Pablo Barbera, Duncan Penfold-Brown, John Jost and Richard
Bonneau; 8. Measuring representational style in the House: the Tea Party,
Obama and legislators' changing expressed priorities Justin Grimmer; 9.
Using social marketing and data science to make government smarter Brian
Griepentrog, Sean Marsh, Sidney Carl Turner and Sarah Evans; 10. Using
machine algorithms to detect election fraud Ines Levin, Julia Pomares and
R. Michael Alvarez; 11. Centralized analysis of local data, with dollars
and lives on the line: lessons from the home radon experience Phillip N.
Price and Andrew Gelman; Conclusion. Computational social science: towards
a collaborative future Hanna Wallach.