<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="lee-etal-2022-searching">
    <titleInfo>
        <title>Searching for PETs: Using Distributional and Sentiment-Based Methods to Find Potentially Euphemistic Terms</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Patrick</namePart>
        <namePart type="family">Lee</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Martha</namePart>
        <namePart type="family">Gavidia</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Anna</namePart>
        <namePart type="family">Feldman</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Jing</namePart>
        <namePart type="family">Peng</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2022-07</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Second Workshop on Understanding Implicit and Underspecified Language</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Valentina</namePart>
            <namePart type="family">Pyatkin</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Daniel</namePart>
            <namePart type="family">Fried</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Talita</namePart>
            <namePart type="family">Anthonio</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Seattle, USA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <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 distri- butional 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.</abstract>
    <identifier type="citekey">lee-etal-2022-searching</identifier>
    <identifier type="doi">10.18653/v1/2022.unimplicit-1.4</identifier>
    <location>
        <url>https://aclanthology.org/2022.unimplicit-1.4</url>
    </location>
    <part>
        <date>2022-07</date>
        <extent unit="page">
            <start>22</start>
            <end>32</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Searching for PETs: Using Distributional and Sentiment-Based Methods to Find Potentially Euphemistic Terms
%A Lee, Patrick
%A Gavidia, Martha
%A Feldman, Anna
%A Peng, Jing
%Y Pyatkin, Valentina
%Y Fried, Daniel
%Y Anthonio, Talita
%S Proceedings of the Second Workshop on Understanding Implicit and Underspecified Language
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, USA
%F lee-etal-2022-searching
%X 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 distri- butional 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.
%R 10.18653/v1/2022.unimplicit-1.4
%U https://aclanthology.org/2022.unimplicit-1.4
%U https://doi.org/10.18653/v1/2022.unimplicit-1.4
%P 22-32

Markdown (Informal)

[Searching for PETs: Using Distributional and Sentiment-Based Methods to Find Potentially Euphemistic Terms](https://aclanthology.org/2022.unimplicit-1.4) (Lee et al., unimplicit 2022)

• Searching for PETs: Using Distributional and Sentiment-Based Methods to Find Potentially Euphemistic Terms (Lee et al., unimplicit 2022)

ACL

• Patrick Lee, Martha Gavidia, Anna Feldman, and Jing Peng. 2022. Searching for PETs: Using Distributional and Sentiment-Based Methods to Find Potentially Euphemistic Terms. In Proceedings of the Second Workshop on Understanding Implicit and Underspecified Language, pages 22–32, Seattle, USA. Association for Computational Linguistics.