The content analysis backed up the evolutionary theory - men looked for significantly younger mates and women significantly older mates, men showed off resources more than women, and women mentioned their own attractiveness more than men
Getting a second researcher to complete the content analysis separately using the same operationalised behaviour categories, then comparing the two sets of data
Researchers generally accept a correlation coefficient of 0.8 between the ratings as showing the data is reliable- correlation is assessed through correlation test
Possibility of observer bias as the researcher often needs to interpret subjective text and could interpret it in a way that supports their pre-existing views
Cultural bias – interpretation of verbal or written content will be affected by the language and culture of the observer
A variation on content analysis where the researcher starts by attempting to discover deeper meanings in the text/interviews, spotting patterns that can be coded, and then identifying themes (emergent themes)
Content analysis is a method used to analyse qualitative data (non-numerical data). In its most common form it is a technique that allows a researcher to take qualitative data and to transform it into quantitative data (numerical data)
Performing a thematic analysis
collect text/turn recordings into text through transcription(writing it down)
read text/transcripts first to spot patterns that can be coded and collected
re-read the transcriptions looking for emergent themes
in thematic analysis, the themes are not pre-determined by the researcher but come from the data
thematic analysis strengths
theories come after the discovery of themes so thematic analysis may stop the researcher imposing their own bias on the analysis by only looking for what they want to see