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原文連結
論文資訊
- 類型：已發表論文
- 日期：2022-08-30
摘要
Text as Data represents a major advance for teaching text analysis in the 社會 sciences, digital humanities and data science by providing an integrated framework for how to conceptualize and deploy natural 語言 processing techniques to enrich descriptive and causal analyses of 社會 life in and from text. Here I review achievements of the book and highlight complementary paths not taken, including discussion of recent 計算 techniques like transformers, which have come to dominate automated 語言 understanding and are just beginning to find their way into the careful research designs showcased in the book. These new methods not only highlight text as a signal from society, but textual models as simulations of society, which could fuel future advances in causal inference and experimentation. Text as Dat
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