Document Type
Conference Proceeding
Publication Date
1-1-2022
Journal / Book Title
Unimplicit 2022 2nd Workshop on Understanding Implicit and Underspecified Language Proceedings of the Workshop
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.
Montclair State University Digital Commons Citation
Lee, Patrick; Gavidia, Martha; Feldman, Anna; and Peng, Jing, "Searching for PETs: Using Distributional and Sentiment-Based Methods to Find Potentially Euphemistic Terms" (2022). Department of Computer Science Faculty Scholarship and Creative Works. 680.
https://digitalcommons.montclair.edu/compusci-facpubs/680
Rights
CC BY 4.0 https://creativecommons.org/licenses/by/4.0/