A sample of 499 tweets containing #babyfever
were recorded during the fall of 2012. This sample size was determined based on
a convenience sampling of the available tweets obtained in a search of the
hashtag “#babyfever” during the fall of 2012.
When tweets were recorded, raters also collected any available
demographic information available on the Twitter user’s personal profile (i.e.,
the relationship status of the user, biological sex, race/ethnicity, and place
of origin). Of the available data, our
sample was almost exclusively female (95%), mostly White (67.5%; 16.2% African
American, 9.0% Hispanic), and mostly childless (87%) with an average age of
20.52 (SDage = 2.21)
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.