@inproceedings{el-zanaty-2019-zeyad,
title = "Zeyad at {S}em{E}val-2019 Task 6: That{'}s Offensive! An All-Out Search For An Ensemble To Identify And Categorize Offense in Tweets.",
author = "El-Zanaty, Zeyad",
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/S19-2144",
doi = "10.18653/v1/S19-2144",
pages = "823--828",
abstract = "The objective of this paper is to provide a description for a classification system built for SemEval-2019 Task 6: OffensEval. This system classifies a tweet as either offensive or not offensive (Sub-task A) and further classifies offensive tweets into categories (Sub-tasks B - C). The system consists of two phases; a brute-force grid search to find the best learners amongst a given set and an ensemble of a subset of these best learners. The system achieved an F1-score of 0.728, ranking in subtask A, an F1-score score of 0.616 in subtask B and an F1-score of 0.509 in subtask C.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="el-zanaty-2019-zeyad">
<titleInfo>
<title>Zeyad at SemEval-2019 Task 6: That’s Offensive! An All-Out Search For An Ensemble To Identify And Categorize Offense in Tweets.</title>
</titleInfo>
<name type="personal">
<namePart type="given">Zeyad</namePart>
<namePart type="family">El-Zanaty</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>The objective of this paper is to provide a description for a classification system built for SemEval-2019 Task 6: OffensEval. This system classifies a tweet as either offensive or not offensive (Sub-task A) and further classifies offensive tweets into categories (Sub-tasks B - C). The system consists of two phases; a brute-force grid search to find the best learners amongst a given set and an ensemble of a subset of these best learners. The system achieved an F1-score of 0.728, ranking in subtask A, an F1-score score of 0.616 in subtask B and an F1-score of 0.509 in subtask C.</abstract>
<identifier type="citekey">el-zanaty-2019-zeyad</identifier>
<identifier type="doi">10.18653/v1/S19-2144</identifier>
<location>
<url>https://aclanthology.org/S19-2144</url>
</location>
<part>
<date>2019-06</date>
<extent unit="page">
<start>823</start>
<end>828</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Zeyad at SemEval-2019 Task 6: That’s Offensive! An All-Out Search For An Ensemble To Identify And Categorize Offense in Tweets.
%A El-Zanaty, Zeyad
%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 el-zanaty-2019-zeyad
%X The objective of this paper is to provide a description for a classification system built for SemEval-2019 Task 6: OffensEval. This system classifies a tweet as either offensive or not offensive (Sub-task A) and further classifies offensive tweets into categories (Sub-tasks B - C). The system consists of two phases; a brute-force grid search to find the best learners amongst a given set and an ensemble of a subset of these best learners. The system achieved an F1-score of 0.728, ranking in subtask A, an F1-score score of 0.616 in subtask B and an F1-score of 0.509 in subtask C.
%R 10.18653/v1/S19-2144
%U https://aclanthology.org/S19-2144
%U https://doi.org/10.18653/v1/S19-2144
%P 823-828
Markdown (Informal)
[Zeyad at SemEval-2019 Task 6: That’s Offensive! An All-Out Search For An Ensemble To Identify And Categorize Offense in Tweets.](https://aclanthology.org/S19-2144) (El-Zanaty, SemEval 2019)
ACL