  The wide use of social media sites and other digital technologies have
resulted in an unprecedented availability of digital data that are being used
to study human behavior across research domains. Although unsolicited opinions
and sentiments are available on these platforms, demographic details are
usually missing. Demographic information is pertinent in fields such as
demography and public health, where significant differences can exist across
sex, racial and socioeconomic groups. In an attempt to address this
shortcoming, a number of academic studies have proposed methods for inferring
the demographics of social media users using details such as names, usernames,
and network characteristics. Gender is the easiest trait to accurately infer,
with measures of accuracy higher than 90 percent in some studies. Race,
ethnicity and age tend to be more challenging to predict for a variety of
reasons including the novelty of social media to certain age groups and a lack
of significant deviations in user details across racial and ethnic groups.
Although the endeavor to predict user demographics is plagued with ethical
questions regarding privacy and data ownership, knowing the demographics in a
data sample can aid in addressing issues of bias and population representation,
so that existing societal inequalities are not exacerbated.
