#babyfever: Social and Media Influences on Fertility Desires
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
After tweets were recorded, two independent raters that were blind to the hypotheses coded each tweet on the following dimensions: if the tweet mentioned exposure to babies, exposure to pregnant women, exposure to baby-related items, babies in the user’s family, a friend’s or acquaintances’ baby, the perception that “everyone” seems to be having babies, positive emotional valence, negative emotional valence, exposure to babies in the media, inclusion of a baby-related image, or themes of envy, regret, or jealousy. After all 499 tweets were coded on these dimensions, the two raters met to discuss and resolve any coding disagreements – mutual agreement was reached in all cases of differential coding through brief discussions.