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Abstract

Computer content analysis provides another approach to measuring differential aspects of social structure (positions and perspectives), as evident in language. Using verbatim transcripts of interviews with occupants of positions in nursing homes talking about their organizational situation, Minnesota Contextual Content Analysis (MCCA-PC) analyzes the meaning in these texts and computes a language-based measurement of social distance as a function of differences between perspectives, facilitating an examination of social distance with other organizational and personal outcomes. Correlates of distance between roles across nursing homes suggest consequences for organizational structure and meanings residents express about their experience. Content scores permit identification of each respondent with a particular nursing home, a measurable aspect of organizational culture. This methodology is compared to techniques in information retrieval for characterizing documents by semantic vectors. Semantic analysis of MCCA categories using WordNet reveals semantic domains, whose refinement may better characterize identified differences.

Keywords

content analysis semantic analysis computing MCCA social distance

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A Computer Content Analysis Approach to Measuring Social Distance in Residential Organizations for Older People

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