Leseprobe
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Text as Data
Margaret E. Roberts, Brandon M. Stewart, Justin Grimmer
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Sozialwissenschaften, Recht, Wirtschaft / Methoden der empirischen und qualitativen Sozialforschung
Beschreibung
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
Kundenbewertungen
Cross-validation (statistics), Secularization, National security, Intellectual history, Political science, Latent Dirichlet allocation, Cluster analysis, Concept, Critique, Philosophy of science, High- and low-level, Machine learning, Electoral reform, Face validity, Internet censorship, Text corpus, Field experiment, Freedom of speech, Social science, Close reading, Voting, Censorship, Thought, Literature, Quantity, Business ethics, General knowledge, Manifesto, Measurement, Research program, Information sensitivity, Observation, Stylometry, Hand coding, Notation, Analysis, Digital humanities, Prediction, Test theory, Coding (social sciences), Email spam, Content analysis, Religion, Accuracy and precision, Indication (medicine), Qualitative research, Computational resource, Hypothesis, Prevalence, Test set, Conceptualization (information science), KPR, Data science, Ideology, Causal inference, Principle, Inductive reasoning, Result, Topic model, Observational study, Essay, Item response theory, Inference, Party platform, Theory, Complexity, Curse of dimensionality, Explanation, Humanities, Computer scientist