hhuEDOS at SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS) - Binary Sexism Detection (Subtask A)

被引:0
|
作者
Petersen, Wiebke [1 ]
Diem-Ly Tran [1 ]
Wroblewitz, Marion [1 ]
机构
[1] Heinrich Heine Univ Dusseldorf, Dusseldorf, Germany
关键词
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we describe our contribution to the SemEval-2023 Task 10 (Subtask A), a shared task on detecting and predicting sexist language. The dataset consists of labeled sexist and non-sexist data targeted towards women acquired from both Reddit and Gab. We present and compare several approaches we experimented with and our final submitted model. Additional error analysis is given to recognize challenges we dealt with in our process. A total of 84 teams participated. Our model ranks 55th overall in Subtask A of the shared task.
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页码:1476 / 1482
页数:7
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