GEPSA, a tool for monitoring social challenges in digital press

This papers presents a platform for monitoring press narratives with respect to several social challenges, including gender equality, migrations and minority languages. As narratives are encoded in natural language, we have to use natural processing techniques to automate their analysis. Thus, crawled news are processed by means of several NLP modules, including named entity recognition, keyword extraction,document classification for social challenge detection, and sentiment analysis. A Flask powered interface provides data visualization for a user-based analysis of the data. This paper presents the architecture of the system and describes in detail its different components. Evaluation is provided for the modules related to extraction and classification of information regarding social challenges.