Searching for PETs: Using Distributional and Sentiment-Based Methods to Find Potentially Euphemistic Terms

Patrick Lee, Martha Gavidia, Anna Feldman, Jing Peng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

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.

Original languageEnglish
Title of host publicationUnImplicit 2022 - 2nd Workshop on Understanding Implicit and Underspecified Language, Proceedings of the Workshop
EditorsValentina Pyatkin, Daniel Fried, Talita Anthonio
PublisherAssociation for Computational Linguistics (ACL)
Pages22-32
Number of pages11
ISBN (Electronic)9781955917926
StatePublished - 2022
Event2nd Workshop on Understanding Implicit and Underspecified Language, UnImplicit 2022 - Seattle, United States
Duration: 15 Jul 2022 → …

Publication series

NameUnImplicit 2022 - 2nd Workshop on Understanding Implicit and Underspecified Language, Proceedings of the Workshop

Conference

Conference2nd Workshop on Understanding Implicit and Underspecified Language, UnImplicit 2022
Country/TerritoryUnited States
CitySeattle
Period15/07/22 → …

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