MARC details
| 000 -LEADER |
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| fixed length control field |
04375 a2200289 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20191031130920.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
180309b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781107518414 |
| 040 ## - CATALOGING SOURCE |
|---|
| Transcribing agency |
SPAB |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
eng |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
300.285 |
| Item number |
COM |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Relator code |
Edited by |
| Personal name |
Alvarez,R.michael |
| 9 (RLIN) |
19034 |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Computational social science: |
| Remainder of title |
discovery and prediction. / |
| Statement of responsibility, etc |
Edited by R. Michael Alvarez |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Name of publisher, distributor, etc |
Cambridge University Press, |
| Date of publication, distribution, etc |
2016. |
| Place of publication, distribution, etc |
New York: |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
x, 327 p. |
| 440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE |
|---|
| Title |
Analytical Methods for Social Research. |
| 9 (RLIN) |
12657 |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Quantitative research in social science research is changing rapidly. Researchers have vast and complex arrays of data with which to work: we have incredible tools to sift through the data and recognize patterns in that data; there are now many sophisticated models that we can use to make sense of those patterns; and we have extremely powerful computational systems that help us accomplish these tasks quickly. This book focuses on some of the extraordinary work being conducted in computational social science - in academia, government, and the private sector - while highlighting current trends, challenges, and new directions. Thus, Computational Social Science showcases the innovative methodological tools being developed and applied by leading researchers in this new field. The book shows how academics and the private sector are using many of these tools to solve problems in social science and public policy. |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Part 1. Computational social science tools. --<br/>1. The application of big data in surveys to the study of elections, public opinion, and representation / Christopher Warshaw --<br/>2. Navigating the local modes of big data : the case of topic models / Margaret E. Roberts, Brandon M. Stewart, and Dustin Tingley --<br/>3. Generating political event data in near real time : opportunities and challenges / John Beiler, Patrick T. Brandt, Andrew Halterman, Philip A. Schrodt, and Erin M. Simpson --<br/>4. Network structure and social outcomes : network analysis for social science / Betsy Sinclair --<br/>5. Ideological salience in multiple dimensions / Peter Foley --<br/>6. Random forests and fuzzy forests in biodemical research / Daniel Conn and Christina M. Ramirez --<br/>Part 2. Computational social science applications. --<br/>7. Big data, social media, and protest : foundations for a research agenda / Joshua A. Tucker, Jonathan Nagler, Megan MacDuffee Metzger, Pablo Barberá, Duncan Penfold-Brown, and Richard Bonneau --<br/>8. Measuring representational style in the House : the Tea Party, Obama, and legislators' changing expressed priorities / Justin Grimmer --<br/>9. Using social marketing and data science to make government smarter / Brian Griepentrog, Sean Marsh, Sidney Carl Turner, and Sarah Evans --<br/>10. Using machine learning algorithms to detect election fraud / Ines Levin, Julia Pomares, and R. Michael Alvarez --<br/>11. Centralized analysis of local data, with dollars and lives on the line : lession from the home radon experience / Phillip N. Price and Andrew Gelman --<br/>Conclusion: Computational social science : toward a collaborative future / Hanna Wallach |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
Quantitative research in social science research is changing rapidly. Researchers have vast and complex arrays of data with which to work: we have incredible tools to sift through the data and recognize patterns in that data; there are now many sophisticated models that we can use to make sense of those patterns; and we have extremely powerful computational systems that help us accomplish these tasks quickly. This book focuses on some of the extraordinary work being conducted in computational social science - in academia, government, and the private sector - while highlighting current trends, challenges, and new directions. Thus, Computational Social Science showcases the innovative methodological tools being developed and applied by leading researchers in this new field. The book shows how academics and the private sector are using many of these tools to solve problems in social science and public policy. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
RES |
| 9 (RLIN) |
12668 |
| 690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
|---|
| Topical term or geographic name as entry element |
Social sciences-Data processing. |
| 9 (RLIN) |
12658 |
| 690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
|---|
| Topical term or geographic name as entry element |
Social sciences-Mathematical models. |
| 9 (RLIN) |
12659 |
| 690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
|---|
| Topical term or geographic name as entry element |
Social sciences-Methodology. |
| 9 (RLIN) |
6771 |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Alvarez, R. Michael ed. |
| 9 (RLIN) |
12660 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Books |
