<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="garcia-cumbreras-etal-2019-sinai">
    <titleInfo>
        <title>SINAI-DL at SemEval-2019 Task 7: Data Augmentation and Temporal Expressions</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Miguel</namePart>
        <namePart type="given">A</namePart>
        <namePart type="family">García-Cumbreras</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Salud</namePart>
        <namePart type="given">María</namePart>
        <namePart type="family">Jiménez-Zafra</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Arturo</namePart>
        <namePart type="family">Montejo-Ráez</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Manuel</namePart>
        <namePart type="given">Carlos</namePart>
        <namePart type="family">Díaz-Galiano</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Estela</namePart>
        <namePart type="family">Saquete</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2019-jun</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 13th International Workshop on Semantic Evaluation</title>
        </titleInfo>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Minneapolis, Minnesota, USA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>This paper describes the participation of the SINAI-DL team at RumourEval (Task 7 in SemEval 2019, subtask A: SDQC). SDQC addresses the challenge of rumour stance classification as an indirect way of identifying potential rumours. Given a tweet with several replies, our system classifies each reply into either supporting, denying, questioning or commenting on the underlying rumours. We have applied data augmentation, temporal expressions labelling and transfer learning with a four-layer neural classifier. We achieve an accuracy of 0.715 with the official run over reply tweets.</abstract>
    <identifier type="citekey">garcia-cumbreras-etal-2019-sinai</identifier>
    <identifier type="doi">10.18653/v1/S19-2196</identifier>
    <location>
        <url>https://aclanthology.org/S19-2196</url>
    </location>
    <part>
        <date>2019-jun</date>
        <extent unit="page">
            <start>1120</start>
            <end>1124</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T SINAI-DL at SemEval-2019 Task 7: Data Augmentation and Temporal Expressions
%A García-Cumbreras, Miguel A.
%A Jiménez-Zafra, Salud María
%A Montejo-Ráez, Arturo
%A Díaz-Galiano, Manuel Carlos
%A Saquete, Estela
%S Proceedings of the 13th International Workshop on Semantic Evaluation
%D 2019
%8 jun
%I Association for Computational Linguistics
%C Minneapolis, Minnesota, USA
%F garcia-cumbreras-etal-2019-sinai
%X This paper describes the participation of the SINAI-DL team at RumourEval (Task 7 in SemEval 2019, subtask A: SDQC). SDQC addresses the challenge of rumour stance classification as an indirect way of identifying potential rumours. Given a tweet with several replies, our system classifies each reply into either supporting, denying, questioning or commenting on the underlying rumours. We have applied data augmentation, temporal expressions labelling and transfer learning with a four-layer neural classifier. We achieve an accuracy of 0.715 with the official run over reply tweets.
%R 10.18653/v1/S19-2196
%U https://aclanthology.org/S19-2196
%U https://doi.org/10.18653/v1/S19-2196
%P 1120-1124

Markdown (Informal)

[SINAI-DL at SemEval-2019 Task 7: Data Augmentation and Temporal Expressions](https://aclanthology.org/S19-2196) (García-Cumbreras et al., SemEval 2019)

• SINAI-DL at SemEval-2019 Task 7: Data Augmentation and Temporal Expressions (García-Cumbreras et al., SemEval 2019)

ACL

• Miguel A. García-Cumbreras, Salud María Jiménez-Zafra, Arturo Montejo-Ráez, Manuel Carlos Díaz-Galiano, and Estela Saquete. 2019. SINAI-DL at SemEval-2019 Task 7: Data Augmentation and Temporal Expressions. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 1120–1124, Minneapolis, Minnesota, USA. Association for Computational Linguistics.