@inproceedings{ec4562e246ea4cb993758da0104b3a32,
title = "Searching for PETs: Using Distributional and Sentiment-Based Methods to Find Potentially Euphemistic Terms",
abstract = "This paper presents a linguistically driven proof of concept for finding potentially euphemistic terms, or PETs. Acknowledging that PETs tend to be commonly used expressions for a certain range of sensitive topics, we make use of distributional similarities to select and filter phrase candidates from a sentence and rank them using a set of simple sentiment-based metrics. We present the results of our approach tested on a corpus of sentences containing euphemisms, demonstrating its efficacy for detecting single and multi-word PETs from a broad range of topics. We also discuss future potential for sentiment-based methods on this task.",
author = "Patrick Lee and Martha Gavidia and Anna Feldman and Jing Peng",
note = "Publisher Copyright: {\textcopyright} 2022 Association for Computational Linguistics.; 2nd Workshop on Understanding Implicit and Underspecified Language, UnImplicit 2022 ; Conference date: 15-07-2022",
year = "2022",
language = "English",
series = "UnImplicit 2022 - 2nd Workshop on Understanding Implicit and Underspecified Language, Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "22--32",
editor = "Valentina Pyatkin and Daniel Fried and Talita Anthonio",
booktitle = "UnImplicit 2022 - 2nd Workshop on Understanding Implicit and Underspecified Language, Proceedings of the Workshop",
address = "United States",
}