Abstract
This paper is a short introduction to computer-aided content analysis in which words or phrases are the basic units. The advantages of computer-aided content analysis are noted and some general issues in its use discussed. Several ways of manipulating text by computer are then illustrated, including ordered word frequency lists, key-word-in-context lists, concordances, classifications of text in terms of content categories, category counts, and category-based retrievals from text. Although examples are based on Democratic and Republican platforms in presidential campaigns, these techniques can be applied to texts from a variety of sources, including in-depth and open-ended interviews, fieldnotes, letters, speeches, newspapers, books, and diaries, to cite a few examples.
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This research was supported in part by Kurzweil Computer Products, Inc., a subsidiary of Xerox Corp. Sue Williamson of Kurzweil played a key role, and her generosity and help is gratefully acknowledged. Randi Lynn Miller assisted with data entry at an earlier phase of research. Additional support has been provided by ZUMA, the Center for Surveys, Methods, and Analysis, Mannheim, FRG. For helpful comments and suggestions, thanks to Tom Davenport, Peter Mohler, J. Zvi Namenwirth, Philip J. Stone, and especially one anonymous reviewer. Thanks also to Kathy Tenerowicz for research assistance and to Barbara Norman for editorial assistance.
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Weber, R.P. Computer-aided content analysis: A short primer. Qual Sociol 7, 126–147 (1984). https://doi.org/10.1007/BF00987112
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DOI: https://doi.org/10.1007/BF00987112