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Spelling correction with large language models to reduce measurement error in open-ended survey responses
9 references·0 citing·38 second hop
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this work references cited by second hop

References

  • 1992The Nature and Origins of Mass Opinion7,804 cited
  • 1964Ideology and Discontent3,905 cited
  • 2014Structural Topic Models for Open‐Ended Survey Responses1,967 cited
  • 2023ChatGPT outperforms crowd workers for text-annotation tasks1,338 cited
  • 2017Text Preprocessing For Unsupervised Learning: Why It Matters, When It Misleads, And What To Do About It469 cited
  • 2023Text as Data: A New Framework for Machine Learning and the Social Sciences207 cited
  • 2024Large language models as a substitute for human experts in annotating political text117 cited
  • 2022Do AIs know what the most important issue is? Using language models to code open-text social survey responses at scale96 cited
  • 2022Troll and divide: the language of online polarization85 cited

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