Offensive Language Detection in Turkish Tweets with Bert Models

Anil Özberk, I. Çiçekli
{"title":"Offensive Language Detection in Turkish Tweets with Bert Models","authors":"Anil Özberk, I. Çiçekli","doi":"10.1109/UBMK52708.2021.9559000","DOIUrl":null,"url":null,"abstract":"As the insulting statements increase on the online platform, these negative statements create a reaction and disturb the peace of society. Offensive language detection research has been increased in recent years. This paper explores the effects of the usage of BERT models and fine-tuning techniques on offensive language detection on Turkish tweets. We emphasize the pre-trained model importance on the performance of a downstream task and the importance of the used BERT model.","PeriodicalId":106516,"journal":{"name":"2021 6th International Conference on Computer Science and Engineering (UBMK)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 6th International Conference on Computer Science and Engineering (UBMK)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UBMK52708.2021.9559000","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

Abstract

As the insulting statements increase on the online platform, these negative statements create a reaction and disturb the peace of society. Offensive language detection research has been increased in recent years. This paper explores the effects of the usage of BERT models and fine-tuning techniques on offensive language detection on Turkish tweets. We emphasize the pre-trained model importance on the performance of a downstream task and the importance of the used BERT model.
基于Bert模型的土耳其语推文攻击性语言检测
随着网络平台上侮辱性言论的增加,这些负面言论产生了一种反应,扰乱了社会的安宁。近年来,攻击性语言检测的研究有所增加。本文探讨了使用BERT模型和微调技术对土耳其推文攻击性语言检测的影响。我们强调预训练模型对下游任务性能的重要性以及所使用的BERT模型的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信