@inproceedings{nina-alcocer-2019-haterecognizer,
title = "{HATER}ecognizer at {S}em{E}val-2019 Task 5: Using Features and Neural Networks to Face Hate Recognition",
author = "Nina-Alcocer, Victor",
editor = "May, Jonathan and
Shutova, Ekaterina and
Herbelot, Aurelie and
Zhu, Xiaodan and
Apidianaki, Marianna and
Mohammad, Saif M.",
booktitle = "Proceedings of the 13th International Workshop on Semantic Evaluation",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S19-2072",
doi = "10.18653/v1/S19-2072",
pages = "409--415",
abstract = "This paper presents a detailed description of our participation in task 5 on SemEval-2019. This task consists of classifying English and Spanish tweets that contain hate towards women or immigrants. We carried out several experiments; for a finer-grained study of the task, we analyzed different features and designing architectures of neural networks. Additionally, to face the lack of hate content in tweets, we include data augmentation as a technique to in- crease hate content in our datasets.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="nina-alcocer-2019-haterecognizer">
<titleInfo>
<title>HATERecognizer at SemEval-2019 Task 5: Using Features and Neural Networks to Face Hate Recognition</title>
</titleInfo>
<name type="personal">
<namePart type="given">Victor</namePart>
<namePart type="family">Nina-Alcocer</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 presents a detailed description of our participation in task 5 on SemEval-2019. This task consists of classifying English and Spanish tweets that contain hate towards women or immigrants. We carried out several experiments; for a finer-grained study of the task, we analyzed different features and designing architectures of neural networks. Additionally, to face the lack of hate content in tweets, we include data augmentation as a technique to in- crease hate content in our datasets.</abstract>
<identifier type="citekey">nina-alcocer-2019-haterecognizer</identifier>
<identifier type="doi">10.18653/v1/S19-2072</identifier>
<location>
<url>https://aclanthology.org/S19-2072</url>
</location>
<part>
<date>2019-06</date>
<extent unit="page">
<start>409</start>
<end>415</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T HATERecognizer at SemEval-2019 Task 5: Using Features and Neural Networks to Face Hate Recognition
%A Nina-Alcocer, Victor
%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 nina-alcocer-2019-haterecognizer
%X This paper presents a detailed description of our participation in task 5 on SemEval-2019. This task consists of classifying English and Spanish tweets that contain hate towards women or immigrants. We carried out several experiments; for a finer-grained study of the task, we analyzed different features and designing architectures of neural networks. Additionally, to face the lack of hate content in tweets, we include data augmentation as a technique to in- crease hate content in our datasets.
%R 10.18653/v1/S19-2072
%U https://aclanthology.org/S19-2072
%U https://doi.org/10.18653/v1/S19-2072
%P 409-415
Markdown (Informal)
[HATERecognizer at SemEval-2019 Task 5: Using Features and Neural Networks to Face Hate Recognition](https://aclanthology.org/S19-2072) (Nina-Alcocer, SemEval 2019)
ACL