  Fertility choices are linked to the different preferences and constraints of
individuals and couples, and vary importantly by socio-economic status, as well
by cultural and institutional context. The meaning of childbearing and
child-rearing, therefore, differs between individuals and across groups. In
this paper, we combine data from Google Correlate and Google Trends for the
U.S. with ground truth data from the American Community Survey to derive new
insights into fertility and its meaning. First, we show that Google Correlate
can be used to illustrate socio-economic differences on the circumstances
around pregnancy and birth: e.g., searches for "flying while pregnant" are
linked to high income fertility, and "paternity test" are linked to non-marital
fertility. Second, we combine several search queries to build predictive models
of regional variation in fertility, explaining about 75% of the variance.
Third, we explore if aggregated web search data can also be used to model
fertility trends.
