Content Analysis—a Probabilistic Approach

Abstract

A probabilistic model is presented which may be applied to perform content analysis on the computer. The procedure employs word stems as category entries and probabilities rather than units for allocating and enumerating content among categories. An application of the model was made to compare content coverage in monopoly and competitive newspapers. There was no appreciable difference due to interaction among monopoly and competitive paper types and content categories. Comparisons among categories showed an appreciably greater probability of news of more‘everyday’than of a violent classification, a finding which challenges a common criticism that the press presents disproportionate content of an inflammatory or violent nature.

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