| Computational Social Science: Discovery and Prediction Contributor(s): Alvarez, R. Michael (Editor) |
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ISBN: 1107107881 ISBN-13: 9781107107885 Publisher: Cambridge University Press OUR PRICE: $122.55 Product Type: Hardcover - Other Formats Published: March 2016 |
| Additional Information |
| BISAC Categories: - Social Science | Research - Social Science | Methodology |
| Dewey: 300.285 |
| LCCN: 2015039154 |
| Series: Analytical Methods for Social Research |
| Physical Information: 0.95" H x 6" W x 9.38" (1.28 lbs) 312 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |
Contributor Bio(s): Alvarez, R. Michael: - R. Michael Alvarez is a Professor of Political Science at the California Institute of Technology. He is a Fellow of the Society for Political Methodology. He is the coeditor of Political Analysis and of the Cambridge University Press series, Analytical Methods for Social Science. He recently coauthored, with Lonna Rae Atkeson and Thad E. Hall, Evaluating Elections: A Handbook of Methods and Standards. He is also codirector of the Caltech/MIT Voting Technology Project. |
