DANKMEMES @ EVALITA 2020: The Memeing of Life: Memes, Multimodality and Politics

Martina Miliani, Giulia Giorgi, Ilir Rama, G. Anselmi, Gianluca E. Lebani
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引用次数: 20

Abstract

DANKMEMES is a shared task proposed for the 2020 EVALITA campaign, focusing on the automatic classification of Internet memes. Providing a corpus of 2.361 memes on the 2019 Italian Government Crisis, DANKMEMES features three tasks: A) Meme Detection, B) Hate Speech Identification, and C) Event Clustering. Overall, 5 groups took part in the first task, 2 in the second and 1 in the third. The best system was proposed by the UniTor group and achieved a F1 score of 0.8501 for task A, 0.8235 for task B and 0.2657 for task C. In this report, we describe how the task was set up, we report the system results and we discuss them.
DANKMEMES @ EVALITA 2020:生活的模因:模因,多模态和政治
DANKMEMES是为2020年EVALITA活动提出的一项共享任务,重点是网络模因的自动分类。DANKMEMES提供了一个关于2019年意大利政府危机的2.361个模因的语料库,主要有三个任务:a)模因检测,B)仇恨言论识别,C)事件聚类。总共有5组参加了第一项任务,2组参加了第二项任务,1组参加了第三项任务。UniTor小组提出了最佳系统,任务a的F1得分为0.8501,任务B的F1得分为0.8235,任务c的F1得分为0.2657。在本报告中,我们描述了任务的设置过程,报告了系统结果并进行了讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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