Searching for PETs: Using Distributional and Sentiment-Based Methods to Find Potentially Euphemistic Terms
2022-05-20NAACL (unimplicit) 2022Code Available0· sign in to hype
Patrick Lee, Martha Gavidia, Anna Feldman, Jing Peng
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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.