Computational social science : discovery and prediction, R. Michael Alvarez

Resource Information

The instance Computational social science : discovery and prediction, R. Michael Alvarez represents a material embodiment of a distinct intellectual or artistic creation found in European University Institute.

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Label

Computational social science : discovery and prediction, R. Michael Alvarez

Title remainder

discovery and prediction

Statement of responsibility

R. Michael Alvarez

Instantiates

• Computational social science : discovery and prediction

Publication

• New York, NY, Cambridge University Press, 2016

Bibliography note

Includes bibliographical references and index

Carrier category

volume

Carrier category code

• nc

Carrier MARC source

rdacarrier.

Content category

text

Content type code

• txt

Content type MARC source

rdacontent.

Contents

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 12. Computational social science: towards a collaborative future Hanna Wallach

Control code

FIEb17833309

Dimensions

23 cm.

Extent

x, 327 pages

Isbn

9781107518414

Media category

unmediated

Media MARC source

rdamedia.

Media type code

• n

Record ID

u321651

System control number

(OCoLC)946546003