A Computational Exploration of Pejorative Language in Social Media
Liviu P. Dinu, Ioan-Bogdan Iordache, Ana Sabina Uban, Marcos Zampieri
Abstract
In this paper we study pejorative language, an under-explored topic in computational linguistics. Unlike existing models of offensive language and hate speech, pejorative language manifests itself primarily at the lexical level, and describes a word that is used with a negative connotation, making it different from offensive language or other more studied categories. Pejorativity is also context-dependent: the same word can be used with or without pejorative connotations, thus pejorativity detection is essentially a problem similar to word sense disambiguation. We leverage online dictionaries to build a multilingual lexicon of pejorative terms for English, Spanish, Italian, and Romanian. We additionally release a dataset of tweets annotated for pejorative use. Based on these resources, we present an analysis of the usage and occurrence of pejorative words in social media, and present an attempt to automatically disambiguate pejorative usage in our dataset.
BibTeX
@inproceedings{dinu-etal-2021-computational-exploration,
title = "A Computational Exploration of Pejorative Language in Social Media",
author = "Dinu, Liviu P. and
Iordache, Ioan-Bogdan and
Uban, Ana Sabina and
Zampieri, Marcos",
editor = "Moens, Marie-Francine and
Huang, Xuanjing and
Specia, Lucia and
Yih, Scott Wen-tau",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2021",
month = nov,
year = "2021",
address = "Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.findings-emnlp.296/",
doi = "10.18653/v1/2021.findings-emnlp.296",
pages = "3493--3498"
}