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        <title>Illegal is not a Noun: Linguistic Form for Detection of Pejorative Nominalizations</title>
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    <name type="personal">
        <namePart type="given">Alexis</namePart>
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    <name type="personal">
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            <title>Proceedings of the First Workshop on Abusive Language Online</title>
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    <abstract>This paper focuses on a particular type of abusive language, targeting expressions in which typically neutral adjectives take on pejorative meaning when used as nouns - compare ‘gay people’ to ‘the gays’. We first collect and analyze a corpus of hand-curated, expert-annotated pejorative nominalizations for four target adjectives: female, gay, illegal, and poor. We then collect a second corpus of automatically-extracted and POS-tagged, crowd-annotated tweets. For both corpora, we find support for the hypothesis that some adjectives, when nominalized, take on negative meaning. The targeted constructions are non-standard yet widely-used, and part-of-speech taggers mistag some nominal forms as adjectives. We implement a tool called NomCatcher to correct these mistaggings, and find that the same tool is effective for identifying new adjectives subject to transformation via nominalization into abusive language.</abstract>
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%0 Conference Proceedings
%T Illegal is not a Noun: Linguistic Form for Detection of Pejorative Nominalizations
%A Palmer, Alexis
%A Robinson, Melissa
%A Phillips, Kristy K.
%Y Waseem, Zeerak
%Y Chung, Wendy Hui Kyong
%Y Hovy, Dirk
%Y Tetreault, Joel
%S Proceedings of the First Workshop on Abusive Language Online
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, BC, Canada
%F palmer-etal-2017-illegal
%X This paper focuses on a particular type of abusive language, targeting expressions in which typically neutral adjectives take on pejorative meaning when used as nouns - compare ‘gay people’ to ‘the gays’. We first collect and analyze a corpus of hand-curated, expert-annotated pejorative nominalizations for four target adjectives: female, gay, illegal, and poor. We then collect a second corpus of automatically-extracted and POS-tagged, crowd-annotated tweets. For both corpora, we find support for the hypothesis that some adjectives, when nominalized, take on negative meaning. The targeted constructions are non-standard yet widely-used, and part-of-speech taggers mistag some nominal forms as adjectives. We implement a tool called NomCatcher to correct these mistaggings, and find that the same tool is effective for identifying new adjectives subject to transformation via nominalization into abusive language.
%R 10.18653/v1/W17-3014
%U https://aclanthology.org/W17-3014
%U https://doi.org/10.18653/v1/W17-3014
%P 91-100

Markdown (Informal)

[Illegal is not a Noun: Linguistic Form for Detection of Pejorative Nominalizations](https://aclanthology.org/W17-3014) (Palmer et al., ALW 2017)

• Illegal is not a Noun: Linguistic Form for Detection of Pejorative Nominalizations (Palmer et al., ALW 2017)

ACL

• Alexis Palmer, Melissa Robinson, and Kristy K. Phillips. 2017. Illegal is not a Noun: Linguistic Form for Detection of Pejorative Nominalizations. In Proceedings of the First Workshop on Abusive Language Online, pages 91–100, Vancouver, BC, Canada. Association for Computational Linguistics.