AMI @ EVALITA2020: Automatic Misogyny Identification

E. Fersini, Debora Nozza, Paolo Rosso
{"title":"AMI @ EVALITA2020: Automatic Misogyny Identification","authors":"E. Fersini, Debora Nozza, Paolo Rosso","doi":"10.4000/BOOKS.AACCADEMIA.6764","DOIUrl":null,"url":null,"abstract":"English. Automatic Misogyny Identification (AMI) is a shared task proposed at the Evalita 2020 evaluation campaign. The AMI challenge, based on Italian tweets, is organized into two subtasks: (1) Subtask A about misogyny and aggressiveness identification and (2) Subtask B about the fairness of the model. At the end of the evaluation phase, we received a total of 20 runs for Subtask A and 11 runs for Subtask B, submitted by 8 teams. In this paper, we present an overview of the AMI shared task, the datasets, the evaluation method-ology, the results obtained by the participants and a discussion about the method-ology adopted by the teams. Finally, we draw some conclusions and discuss future work.","PeriodicalId":184564,"journal":{"name":"EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"61","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4000/BOOKS.AACCADEMIA.6764","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 61

Abstract

English. Automatic Misogyny Identification (AMI) is a shared task proposed at the Evalita 2020 evaluation campaign. The AMI challenge, based on Italian tweets, is organized into two subtasks: (1) Subtask A about misogyny and aggressiveness identification and (2) Subtask B about the fairness of the model. At the end of the evaluation phase, we received a total of 20 runs for Subtask A and 11 runs for Subtask B, submitted by 8 teams. In this paper, we present an overview of the AMI shared task, the datasets, the evaluation method-ology, the results obtained by the participants and a discussion about the method-ology adopted by the teams. Finally, we draw some conclusions and discuss future work.
AMI @ EVALITA2020:厌女症自动识别
英语。厌女症自动识别(AMI)是在Evalita 2020评估活动中提出的一项共享任务。AMI挑战基于意大利语推文,分为两个子任务:(1)关于厌女症和攻击性识别的子任务A和(2)关于模型公平性的子任务B。在评估阶段结束时,我们总共收到了8个团队提交的子任务a的20次运行和子任务B的11次运行。本文概述了AMI共享任务、数据集、评估方法、参与者获得的结果,并讨论了团队采用的方法。最后,提出了一些结论,并对今后的工作进行了讨论。
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:604180095
Book学术官方微信