content analysis is used to do what to what data?
to quantify qualitative data
content analysis
researcher analyses written, verbal and visual communication numerically using a pre-determined set of categories
key characteristics of content analysis
quantative focus
systematic coding
objectivity + reliability
application
quantitative focus
counting the frequency of specific words, phrases or themes in the data
systematic coding
researchers predetermine a coding scheme of categories based on their research Qs or hypothesis
objectivity + reliability
content analysis aims to be objective with clear definitions and category rules to ensure consistency and reliability across codes and categories
application
analysis of interview transcripts, open ended survey responses, and historical document analysis
the procedure for content analysis
1 a sample of materials is examined by at least two separate researchers (inter-rater reliability)
2 reading/looking over the material leads to the identification of suitable/relevant categories
3 categories are then agreed on and operationalised
4 coding occurs by 2 different researchers separately reading back over the material and counting the frequency in which it occurs
5 the frequencies are tallied by each researcher and compared and checked for inter-rater reliability
strengths of content analysis
useful to gather data from a wide range of areas -high ecological validity
many ethical issues are avoided - data that may be studied can be public domain E.G. TV
reliable as it is replicable (due to codes)
limitation of content analysis
time consuming to operationalise and find themes
system can be biased by researchers