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This project is a unique opportunity to compare human versus computer coding
and analysis using the same set of data and with the same research questions in mind. In
this methodological case study, the focus is on the similarities and differences in both
process and results in a content analysis project.
Plus, this project involves second-level agenda-setting, also known as attribute
agenda-setting. Instead of just studying a person or issue, second-level agenda setting
attempts to get at how that person or issue is perceived. So the analysis must involve not
only frequencies but also the affect involved.
LITERATURE REVIEW
Computer-assisted Content Analysis
One of the earliest definitions of content analysis predicted the future role
computers would play in the methodology. Pioneer communication researcher Bernard
Berleson (1952) is widely quoted to this day because of his description of content
analysis as a “research technique for the objective, systematic, and quantitative
description of the manifest content of communication.” The key terms are systematic and
quantitative. The precision element of content analysis plays to the strength of
computers. Manifest content is also important for computer use. By limiting content
analysis to what is actually in the text as opposed to the deeper meaning, often referred to
as latent content, computers can be very effective. Computers are good at counting what
is there but aren’t as effective at reading between the lines.
Content analysis computer programs have allowed researchers to tackle some
large projects. Danielson and Lasorsa (1997) were able to analyze a sample of one
Convention