Papers by Nitya Parthasarthi
GenderQuant: Quantifying Mention-Level Genderedness (N19-1)
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| Challenge: | Existing approaches to detect gendered language require considerable annotation efforts for each language, domain, and author, and often require handcrafted lexicons and features. |
| Approach: | They use existing NLP pipelines to automatically annotate gender of mentions in the text and train a supervised classifier to predict the gender of any mention from its context and evaluate it on unseen text. |
| Outcome: | The proposed method can detect gendered language on movie summaries, movie reviews, news articles, and fiction novels. |