Text as Data
A New Framework for Machine Learning and the Social Sciences
Book •
Text as Data: A New Framework for Machine Learning and the Social Sciences provides a comprehensive guide to leveraging textual data in social science research.
It emphasizes a task-focused approach, guiding researchers through the process of discovery, measurement, prediction, and causal inference.
The book bridges the gap between computer science and social science methodologies, offering practical applications and examples.
It encourages an iterative and inductive research design, acknowledging the abundance of data in the digital age.
The authors advocate for a nuanced approach to validation, emphasizing the importance of substantive knowledge and close reading.
It emphasizes a task-focused approach, guiding researchers through the process of discovery, measurement, prediction, and causal inference.
The book bridges the gap between computer science and social science methodologies, offering practical applications and examples.
It encourages an iterative and inductive research design, acknowledging the abundance of data in the digital age.
The authors advocate for a nuanced approach to validation, emphasizing the importance of substantive knowledge and close reading.
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Peter Lorentzen
Justin Grimmer et al., "Text as Data: A New Framework for Machine Learning and the Social Sciences" (Princeton UP, 2022)
