#babyfever: Social and Media Influences on Fertility Desires

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.

2012年秋季，本研究所采集的样本包含499条带有#babyfever标签的推文。该样本量是基于对2012年秋季搜索所得的#babyfever标签推文的便利抽样确定的。在记录推文的同时，评估者还收集了Twitter用户个人资料上可用的任何人口统计信息（例如，用户的恋爱状况、生物学性别、种族/民族和籍贯）。在可用的数据中，我们的样本几乎全部为女性（占比95%），以白人为主（占比67.5%；非洲裔美国人占比16.2%，西班牙裔美国人占比9.0%），并且大多数为无子女者（占比87%），平均年龄为20.52岁（标准差为2.21岁）。记录推文后，两位对假设内容不知情的独立评估者对每条推文在以下维度上进行了编码：提及婴儿的接触、接触孕妇、接触与婴儿相关的物品、用户家庭成员中的婴儿、朋友或熟人的婴儿、普遍认为“每个人”似乎都在生孩子的感知、积极的情绪倾向、消极的情绪倾向、接触媒体中的婴儿、包含与婴儿相关的图像，或嫉妒、后悔或羡慕的主题。在所有499条推文都完成编码后，两位评估者会面讨论并解决任何编码分歧——通过简短的讨论，所有差异编码的情况均达成了共识。