COMPUTER-ASSISTED CONTENT-ANALYSIS OF NEWSPAPERS - CAN WE MAKE AN EXPENSIVE RESEARCH TOOL MORE EFFICIENT

Content analysis as a methodology of data collection from text sources is very labor intensive and therefore costly. Advances in computer-as sisted content analysis have greatly increased the power of the method ology. But, even in a computer environment, complex searches require e xtensive prior manipulation of the original text in order to assign to it a basic structure. It is this structure that allows researchers to perform complex queries in highly general ways. I argue that Semantic s provides powerful templates for structuring text data (text grammars ) and other conceptual tools that can be profitably used to increase t he efficiency of content analysis projects (e.g. news schema and macro propositions). More generally, I argue that efficiency in content ana lysis projects depends upon such characteristics as (1) organization o f the coding task; (2) newspaper reporting practices. The discussion o f these characteristics results in several suggestions on how to incre ase the efficiency of the methodology.