After decades of improvements in the employment conditions of women 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 both national and regional news outlets employing advanced Natural Language Processing techniques, to capture valence of mentions of gender inequality expressed in the Spanish press. We show that the automatic analysis of the news articles does indeed capture the known hardships faced by women in the Spanish labour market. Our approach can be generalized to other topics of interest in a simple and straightforward manner. Performing an in-depth analysis of the sentiment and moral values expressed in the articles we show that women are, in the majority of cases, affected more than men when there is a deterioration in the overall labour market conditions, based on newspaper articles. This behaviour is present in the entire period of study (2000-2022), and looks particularly pronounced during the economic crisis of 2008 and the recent COVID-19 pandemic. Most of the times, this phenomenon looks to be more pronounced at regional level as reported by the Spanish press, perhaps caused by either a major focus on local labour markets rather than on aggregate statistics, or because at local contexts women might suffer more from isolation or discrimination. Our findings contribute to a deeper understanding of the gender inequalities in Spain using alternative data, informing policymakers and stakeholders.

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