<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="durlich-2018-kluenicorn">
    <titleInfo>
        <title>KLUEnicorn at SemEval-2018 Task 3: A Naive Approach to Irony Detection</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Luise</namePart>
        <namePart type="family">Dürlich</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2018-jun</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of The 12th International Workshop on Semantic Evaluation</title>
        </titleInfo>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">New Orleans, Louisiana</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>This paper describes the KLUEnicorn system submitted to the SemEval-2018 task on “Irony detection in English tweets”. The proposed system uses a naive Bayes classifier to exploit rather simple lexical, pragmatical and semantical features as well as sentiment. It further takes a closer look at different adverb categories and named entities and factors in word-embedding information.</abstract>
    <identifier type="citekey">durlich-2018-kluenicorn</identifier>
    <identifier type="doi">10.18653/v1/S18-1099</identifier>
    <location>
        <url>https://aclanthology.org/S18-1099</url>
    </location>
    <part>
        <date>2018-jun</date>
        <extent unit="page">
            <start>607</start>
            <end>612</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T KLUEnicorn at SemEval-2018 Task 3: A Naive Approach to Irony Detection
%A Dürlich, Luise
%S Proceedings of The 12th International Workshop on Semantic Evaluation
%D 2018
%8 jun
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F durlich-2018-kluenicorn
%X This paper describes the KLUEnicorn system submitted to the SemEval-2018 task on “Irony detection in English tweets”. The proposed system uses a naive Bayes classifier to exploit rather simple lexical, pragmatical and semantical features as well as sentiment. It further takes a closer look at different adverb categories and named entities and factors in word-embedding information.
%R 10.18653/v1/S18-1099
%U https://aclanthology.org/S18-1099
%U https://doi.org/10.18653/v1/S18-1099
%P 607-612

Markdown (Informal)

[KLUEnicorn at SemEval-2018 Task 3: A Naive Approach to Irony Detection](https://aclanthology.org/S18-1099) (Dürlich, SemEval 2018)

• KLUEnicorn at SemEval-2018 Task 3: A Naive Approach to Irony Detection (Dürlich, SemEval 2018)

ACL

• Luise Dürlich. 2018. KLUEnicorn at SemEval-2018 Task 3: A Naive Approach to Irony Detection. In Proceedings of The 12th International Workshop on Semantic Evaluation, pages 607–612, New Orleans, Louisiana. Association for Computational Linguistics.