NAACL 2025long0 citations
Automatically Discovering How Misogyny is Framed on Social Media
Rakshitha Rao Ailneni, Sanda M. Harabagiu
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.
BibTeX
@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/",
pages = "12189--12208",
ISBN = "979-8-89176-189-6"
}