Papers › Radar de Parité: An NLP system to measure gender representation in French news stories
Radar de Parité: An NLP system to measure gender representation in French news stories
Valentin-Gabriel Soumah, Prashanth Rao, Philipp Eibl, Maite Taboada
We present the Radar de Parit\'e, an automated Natural Language Processing (NLP) system that measures the proportion of women and men quoted daily in six Canadian French-language media outlets. We outline the system's architecture and detail the challenges we overcame to address French-specific issues, in particular regarding coreference resolution, a new contribution to the NLP literature on French. We also showcase statistics covering over one year's worth of data (282,512 news articles). Our results highlight the underrepresentation of women in news stories, while also illustrating the application of modern NLP methods to measure gender representation and address societal issues.
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