  After decades of improvements in the employment conditions of females in
Spain, this process came to a sudden stop with the Great Spanish Recession of
2008. In this contribution, we analyse a large longitudinal corpus of national
and regional news outlets employing advanced Natural Language Processing
techniques to capture the valence of mentions of gender inequality expressed in
the Spanish press. The automatic analysis of the news articles does indeed
capture the known hardships faced by females in the Spanish labour market. Our
approach can be straightforwardly generalised to other topics of interest.
Assessing the sentiment and moral values expressed in the articles, we notice
that females are, in the majority of cases, concerned more than males when
there is a deterioration in the overall labour market conditions, based on
newspaper articles. This behaviour has been present in the entire period of
study (2000--2022) and looked particularly pronounced during the economic
crisis of 2008 and the recent COVID-19 pandemic. Most of the time, this
phenomenon looks to be more pronounced at the regional level, perhaps caused by
a significant focus on local labour markets rather than on aggregate statistics
or because, in local contexts, females might suffer more from an isolation or
discrimination condition. Our findings contribute to a deeper understanding of
the gender inequalities in Spain using alternative data, informing policymakers
and stakeholders.
