Abstract
This article suggests one way to systematically code textual data for research. The approach utilizes computer content analysis to examine patterns of emphasized ideas in text as well as the social context or underlying perspective reflected in the text. A conceptual dictionary is used to organize word meanings. An extensive profile of word meanings is used to characterize and discriminate social contexts. Social contexts are analyzed in relation to four reference dimensions (traditional, practical, emotional and analytic) which are used in the social science literature. The approach is illustrated with five widely varying texts, analyzed with selected comparative data. This approach has been useful in many social science investigations to system-atically score open-ended textual information. Scores can be incorporated into quantitative analysis with other data, used as a guide to qualitative studies, and to help integrate strengths of quantitative and qualitative approaches to research.
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Abbreviations
- C-scores:
-
Contextual scores
- E-scores:
-
Idea/emphasis scores
- KWIC:
-
Key Word In Context
- MCCA:
-
Minnesota Contextual Content Analysis
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An early version of this paper was presented at the Pacific Sociological Association Meetings, Seattle, April 12, 1984.
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McTavish, D.G., Pirro, E.B. Contextual content analysis. Qual Quant 24, 245–265 (1990). https://doi.org/10.1007/BF00139259
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DOI: https://doi.org/10.1007/BF00139259