Papers by Patricia Chiril
Seeds of Discourse: A Multilingual Corpus of Direct Quotations from African Media on Agricultural Biotechnologies (2025.findings-naacl)
Copied to clipboard
| Challenge: | a new study examines how media amplify messages around GM crops . agribusiness companies have placed ads for their products in newspapers . |
| Approach: | They present a multilingual corpora of 1,657 direct quotes from Africa-based news sources . they provide 665 instances annotated for Aspect-Based Sentiment Analysis . |
| Outcome: | The results of this study are available in English and French. |
Tales and Tropes: Gender Roles from Word Embeddings in a Century of Children’s Books (2022.coling-1)
Copied to clipboard
Anjali Adukia, Patricia Chiril, Callista Christ, Anjali Das, Alex Eble, Emileigh Harrison, Hakizumwami Birali Runesha
| Challenge: | In 100 years of influential children's books, gender is portrayed in a way that reproduces traditional gender norms in society. |
| Approach: | They use word embeddings to train a model to detect individual sentences containing stereotypes to measure how gender is portrayed in children's books. |
| Outcome: | The proposed model trains a model to detect individual sentences containing stereotypes to gain a deeper understanding of the messages conveyed to children by the books they read. |
What Did You Learn To Hate? A Topic-Oriented Analysis of Generalization in Hate Speech Detection (2023.eacl-main)
Copied to clipboard
| Challenge: | Hate speech detection datasets often use different annotation guidelines, resulting in inconsistencies . authors propose a topic-oriented approach to study generalization across popular hate speech datasets . |
| Approach: | They propose a topic-oriented approach to study generalization across popular hate speech datasets . they compare Transformer-based models in capturing topic-generic and topic-specific knowledge . |
| Outcome: | The proposed approach improves the reliability of hate speech detection on social media platforms. |
An Annotated Corpus for Sexism Detection in French Tweets (2020.lrec-1)
Copied to clipboard
Patricia Chiril, Véronique Moriceau, Farah Benamara, Alda Mari, Gloria Origgi, Marlène Coulomb-Gully
| Challenge: | Social media networks allow users to share opinions and sentiments, which can cause a large spreading of hatred or abusive messages. |
| Approach: | They propose to annotate 12,000 tweets with a sexism detection scheme in France . they propose to use deep learning to detect if a message with sexist content is really s. |
| Outcome: | The proposed scheme detects sexist content and identifies if it is really sexism . the proposed scheme is the first of its kind in the u.s. |
“Be nice to your wife! The restaurants are closed”: Can Gender Stereotype Detection Improve Sexism Classification? (2021.findings-emnlp)
Copied to clipboard
| Challenge: | a new study examines the impact of gender stereotype detection on sexism classification . GS is defined as "pictures in our heads" and is used to describe social group members . |
| Approach: | They propose to use tweets as a dataset to detect sexist hate speech . they propose a method for data augmentation based on sentence similarity with external datasets . |
| Outcome: | The proposed method detects sexist hate speech in tweets and then uses it for sexism classification. |
He said “who’s gonna take care of your children when you are at ACL?”: Reported Sexist Acts are Not Sexist (2020.acl-main)
Copied to clipboard
Patricia Chiril, Véronique Moriceau, Farah Benamara, Alda Mari, Gloria Origgi, Marlène Coulomb-Gully
| Challenge: | Sexism is prejudice or discrimination based on a person's gender. |
| Approach: | They propose to use a French dataset annotated for sexism detection to characterize sexist content and to train deep learning experiments on tweets. |
| Outcome: | The proposed dataset is the first to be used for sexism detection in France and constitutes a first step towards offensive content moderation. |