Abstract
This paper presents a case study of analyzing and improving intercoder reliability in discourse tagging using statistical techniques. Bias-corrected tags are formulated and successfully used to guide a revision of the coding manual and develop an automatic classifier.
Keywords
Computer scienceClassifier (UML)SubjectivityCoding (social sciences)Artificial intelligenceNatural language processingReliability (semiconductor)Data miningMachine learningInformation retrievalStatisticsMathematics
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Publication Info
- Year
- 1999
- Type
- article
- Pages
- 246-253
- Citations
- 498
- Access
- Closed
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Cite This
Janyce Wiebe,
Rebecca Bruce,
Thomas P. O'Hara
(1999).
Development and use of a gold-standard data set for subjectivity classifications.
Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics -
, 246-253.
https://doi.org/10.3115/1034678.1034721
Identifiers
- DOI
- 10.3115/1034678.1034721