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A guide for using computational text analysis to learn about the
social world From social media posts and text messages to digital
government documents and archives, researchers are bombarded with a
deluge of text reflecting the social world. This textual data gives
unprecedented insights into fundamental questions in the social
sciences, humanities, and industry. Meanwhile new machine learning
tools are rapidly transforming the way science and business are
conducted. Text as Data shows how to combine new sources of data,
machine learning tools, and social science research design to
develop and evaluate new insights. Text as Data is organized around
the core tasks in research projects using text-representation,
discovery, measurement, prediction, and causal inference. The
authors offer a sequential, iterative, and inductive approach to
research design. Each research task is presented complete with
real-world applications, example methods, and a distinct style of
task-focused research. Bridging many divides-computer science and
social science, the qualitative and the quantitative, and industry
and academia-Text as Data is an ideal resource for anyone wanting
to analyze large collections of text in an era when data is
abundant and computation is cheap, but the enduring challenges of
social science remain. Overview of how to use text as data Research
design for a world of data deluge Examples from across the social
sciences and industry
A guide for using computational text analysis to learn about the
social world From social media posts and text messages to digital
government documents and archives, researchers are bombarded with a
deluge of text reflecting the social world. This textual data gives
unprecedented insights into fundamental questions in the social
sciences, humanities, and industry. Meanwhile new machine learning
tools are rapidly transforming the way science and business are
conducted. Text as Data shows how to combine new sources of data,
machine learning tools, and social science research design to
develop and evaluate new insights. Text as Data is organized around
the core tasks in research projects using text-representation,
discovery, measurement, prediction, and causal inference. The
authors offer a sequential, iterative, and inductive approach to
research design. Each research task is presented complete with
real-world applications, example methods, and a distinct style of
task-focused research. Bridging many divides-computer science and
social science, the qualitative and the quantitative, and industry
and academia-Text as Data is an ideal resource for anyone wanting
to analyze large collections of text in an era when data is
abundant and computation is cheap, but the enduring challenges of
social science remain. Overview of how to use text as data Research
design for a world of data deluge Examples from across the social
sciences and industry
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