<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="wang-ding-2019-ynu">
    <titleInfo>
        <title>YNU NLP at SemEval-2019 Task 5: Attention and Capsule Ensemble for Identifying Hate Speech</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Bin</namePart>
        <namePart type="family">Wang</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Haiyan</namePart>
        <namePart type="family">Ding</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2019-06</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 13th International Workshop on Semantic Evaluation</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Jonathan</namePart>
            <namePart type="family">May</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Ekaterina</namePart>
            <namePart type="family">Shutova</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Aurelie</namePart>
            <namePart type="family">Herbelot</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Xiaodan</namePart>
            <namePart type="family">Zhu</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Marianna</namePart>
            <namePart type="family">Apidianaki</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Saif</namePart>
            <namePart type="given">M</namePart>
            <namePart type="family">Mohammad</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <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 system submitted to SemEval 2019 Task 5: Multilingual detection of hate speech against immigrants and women in Twitter (hatEval). Its main purpose is to conduct hate speech detection on Twitter, which mainly includes two specific different targets, immigrants and women. We participate in both subtask A and subtask B for English. In order to address this task, we develope an ensemble of an attention-LSTM model based on HAN and an BiGRU-capsule model. Both models use fastText pre-trained embeddings, and we use this model in both subtasks. In comparison to other participating teams, our system is ranked 16th in the Sub-task A for English, and 12th in the Sub-task B for English.</abstract>
    <identifier type="citekey">wang-ding-2019-ynu</identifier>
    <identifier type="doi">10.18653/v1/S19-2095</identifier>
    <location>
        <url>https://aclanthology.org/S19-2095</url>
    </location>
    <part>
        <date>2019-06</date>
        <extent unit="page">
            <start>529</start>
            <end>534</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T YNU NLP at SemEval-2019 Task 5: Attention and Capsule Ensemble for Identifying Hate Speech
%A Wang, Bin
%A Ding, Haiyan
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%S Proceedings of the 13th International Workshop on Semantic Evaluation
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota, USA
%F wang-ding-2019-ynu
%X This paper describes the system submitted to SemEval 2019 Task 5: Multilingual detection of hate speech against immigrants and women in Twitter (hatEval). Its main purpose is to conduct hate speech detection on Twitter, which mainly includes two specific different targets, immigrants and women. We participate in both subtask A and subtask B for English. In order to address this task, we develope an ensemble of an attention-LSTM model based on HAN and an BiGRU-capsule model. Both models use fastText pre-trained embeddings, and we use this model in both subtasks. In comparison to other participating teams, our system is ranked 16th in the Sub-task A for English, and 12th in the Sub-task B for English.
%R 10.18653/v1/S19-2095
%U https://aclanthology.org/S19-2095
%U https://doi.org/10.18653/v1/S19-2095
%P 529-534

Markdown (Informal)

[YNU NLP at SemEval-2019 Task 5: Attention and Capsule Ensemble for Identifying Hate Speech](https://aclanthology.org/S19-2095) (Wang & Ding, SemEval 2019)

• YNU NLP at SemEval-2019 Task 5: Attention and Capsule Ensemble for Identifying Hate Speech (Wang & Ding, SemEval 2019)

ACL

• Bin Wang and Haiyan Ding. 2019. YNU NLP at SemEval-2019 Task 5: Attention and Capsule Ensemble for Identifying Hate Speech. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 529–534, Minneapolis, Minnesota, USA. Association for Computational Linguistics.