Content Analysis—a Probabilistic Approach
Bibliographic Data
| ID | 20300513 |
|---|---|
| Authors | Mervin D Lynch (University of Wisconsin–Madison), John C Merrill (University of Iowa) |
| Year | 1968 |
| Volume | 18 |
| Issue | 2 |
| Pages | 151-159 |
| Publication date | 1968-06-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Communication (JOURNAL) |
| Journal identifiers | ISSN: 0021-9916 • E-ISSN: 1460-2466 |
| Publisher | Oxford University Press (OUP) (PUBLISHER) |
| DOI | 10.1111/j.1460-2466.1968.tb00066.x |
| OpenAlex | W2093907908 |
| Language | EN |
| References cited | 7 |
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
Content analysis · Journalism · Library science · Media studies · Social science · Sociology · Advanced Text Analysis Techniques · Computational and Text Analysis Methods · Computer Science
| Highly cited | No |
|---|