@inproceedings{ailneni-harabagiu-2025-automatically,
title = "Automatically Discovering How Misogyny is Framed on Social Media",
author = "Ailneni, Rakshitha Rao and
Harabagiu, Sanda M.",
editor = "Chiruzzo, Luis and
Ritter, Alan and
Wang, Lu",
booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)",
month = apr,
year = "2025",
address = "Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.naacl-long.608/",
doi = "10.18653/v1/2025.naacl-long.608",
pages = "12189--12208",
ISBN = "979-8-89176-189-6",
abstract = "Misogyny, which is widespread on social media, can be identified not only by recognizing its many forms but also by discovering how misogyny is framed. This paper considers the automatic discovery of misogyny problems and their frames through the Dis-MP{\&}F method, which enables the generation of a data-driven, rich Taxonomy of Misogyny (ToM), offering new insights in the complexity of expressions of misogyny. Furthermore, the Dis-MP{\&}F method, informed by the ToM, is capable of producing very promising results on a misogyny benchmark dataset."
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%0 Conference Proceedings
%T Automatically Discovering How Misogyny is Framed on Social Media
%A Ailneni, Rakshitha Rao
%A Harabagiu, Sanda M.
%Y Chiruzzo, Luis
%Y Ritter, Alan
%Y Wang, Lu
%S Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
%D 2025
%8 April
%I Association for Computational Linguistics
%C Albuquerque, New Mexico
%@ 979-8-89176-189-6
%F ailneni-harabagiu-2025-automatically
%X Misogyny, which is widespread on social media, can be identified not only by recognizing its many forms but also by discovering how misogyny is framed. This paper considers the automatic discovery of misogyny problems and their frames through the Dis-MP&F method, which enables the generation of a data-driven, rich Taxonomy of Misogyny (ToM), offering new insights in the complexity of expressions of misogyny. Furthermore, the Dis-MP&F method, informed by the ToM, is capable of producing very promising results on a misogyny benchmark dataset.
%R 10.18653/v1/2025.naacl-long.608
%U https://aclanthology.org/2025.naacl-long.608/
%U https://doi.org/10.18653/v1/2025.naacl-long.608
%P 12189-12208
Markdown (Informal)
[Automatically Discovering How Misogyny is Framed on Social Media](https://aclanthology.org/2025.naacl-long.608/) (Ailneni & Harabagiu, NAACL 2025)
ACL
- Rakshitha Rao Ailneni and Sanda M. Harabagiu. 2025. Automatically Discovering How Misogyny is Framed on Social Media. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pages 12189–12208, Albuquerque, New Mexico. Association for Computational Linguistics.