Within the framework of the GILL project (Gender Innovation Living Labs), this study extends the project's first phase by refining the analysis of gender-related discussions on social media through advanced Artificial Intelligence techniques. Methodological enhancements are introduced, incorporating Word2Vec and sentiment analysis to achieve a deeper understanding of semantic and emotional relationships. Additionally, interactive visualization techniques are optimized to facilitate the interpretation of results. The implemented innovations improve analytical accuracy and will be integrated into an interactive dashboard, enabling dynamic exploration of gender perceptions and offering a more nuanced view of the public debate. This article describes the methodologies employed, the main findings, and the improvements made, emphasizing their usefulness for informing evidence-based public policies in gender equality.