No 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 systematically 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.Abbreviations: C-scores = Contextual scores, E-scores = Idea/emphasis scores, KWIC = Key Word In Context, MCCA = Minnesota Contextual Content Analysis An early version of this paper was presented at the Pacific Sociological Association Meetings Seattle, April 12, 1984.

Language patterns of family business owners were explored by identifying discourse styles and emphasized ideas in four presenting contexts: business, family, intersection of family and business, and business success. The content analysis supports the existence of a general discourse style within family businesses and of similarities and differences between men and women in emphasized ideas as they frame their family businesses. The emotional discourse style (words of personal involvement, concern, and preference) was prominent across contexts for both genders, and there was a distinct absence of analytical language. Women had a higher emotional discourse style score for managing the business than did men, and balanced their emotional language with the practicality of planning tasks and creating efficiencies.

Stories in a sample of 92 television (TV) food ads aimed at children were analyzed for thematic and subtextual content. Violence as a surface theme ranked first in use receiving a nonzero score in 62% of the ads, followed by conflict (41%), achievement (24%), mood alteration (23%), enablement (18%), trickery (20%), and product dependence (8%). Cluster analysis identified six groupings of themes, with 64% of the ads characterized by some combination of violence, conflict, and trickery. Regarding subtexts, the computer‐based Minnesota Contextual Content Analysis program evaluated the voiced material in ads in terms of four marker categories named “traditional (normative)”, “practical”, “emotional”, and “analytic”. It was found that the texts had a strong emphasis on the emotional subtext or thrust, and a pronounced underemphasis on the analytic context. These analyses identify possibly dubious content in a significant segment of children's TV viewing.

This investigation provides an examination of the validity of the Job Diagnostic Survey (JDS) and the Job Characteristics Inventory (JCI). The verbal content of the two measure is examined, as are the contrasts between the verbal content of these scales and the verbal content of three popular measures of job satisfaction. The Minnesota Contextual Content Analysis program is used to examine the ideas emphasized by these research scales. Both measures of job characteristics were found to discriminate from certain measures of job satisfaction, to emphasize an instrumental and not an affective context, and to possess some internal dimensionality problems.