Measuring Male Fertility Rates by Making Use of Facebook Data
Can social media channels like Facebook be used to analyse fertility data? According to recent research, it can be.
In a paper by Francesco Rampazzo, Emilio Zagheni, Ingmar Weber, Maria Rita Testa and Francesco Billari, they sought out to determine if anonymous and aggregate data from Facebook advertising can be a viable source for fertility data. This is particularly relevant when looking at developing countries, where official data is less available.
Facebook is a non-representative source of data for the whole population of a country, but it is a regularly updated digital source. When using the Facebook advertising tool, one can choose certain criteria to define their target group. Populations can be identified based on the following criteria: Demographics (e.g. age, gender, relationship status, education, etc.), location, interests and behaviour. There are numerous possibilities to filter information because one can also combine criteria, such as fertility and education, age and relationship status, and so on.
Rampazzo et al. filtered Facebook users to find individuals (male and female) between the ages of 15 and 49, who had a child in the last 12 months – on a global level. Subsequently, the researchers obtained United Nations estimates for fertility data, which they compared to the Facebook data.
Their results showed that by using the Facebook advertising tool, it is possible to fill data gaps in many developing countries where estimates are currently unavailable. Their research highlights the advantages and possibilities, as well as the limitations of this data source. One big advantage is that estimates can be made instantly. The global reach is another plus: As more and more people worldwide are using social networks, data will become even more obtainable.
The researchers believe that this is a promising and new direction for future work. Their paper provides the basis for running more detailed male fertility analyses through Facebook advertising data as it shows the feasibility to estimate the trustable demographic indicators at a global level.
The data used for this paper is available upon request after the submission of a google form.
The code is available on this Github repository