Computational Social Science
Computational Social Science by R. Michael Alvarez, published by Cambridge University Press on March 10, 2016, is a comprehensive exploration of the evolving landscape of quantitative research in social sciences. This edition, comprising 327 pages, delves into the vast and complex data available to researchers today, highlighting the sophisticated tools and models that facilitate the analysis of patterns within this data. The book examines the extraordinary work being conducted in computational social science across academia, government, and the private sector.
Readers will find a detailed discussion on current trends, challenges, and new directions in the field. The text showcases innovative methodological tools developed by leading researchers, illustrating how these tools are applied to address various issues in social science and public policy. With a focus on research methodologies, this book serves as a valuable resource for those interested in the intersection of political science, social science, and computational methods.
Official synopsis Publisher
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.
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