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AdelaideCyC at SemEval-2020 Task 12: Ensemble of Classifiers for Offensive Language Detection in Social Media

机译:AdelaideCyc在Semeval-2020任务12:社交媒体中攻击性语言检测的分类器组合

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This paper describes the systems our team (AdelaideCyC) has developed for SemEval Task 12 (OffensEval 2020) to detect offensive language in social media. The challenge focuses on three subtasks - offensive language identification (subtask A), offense type identification (subtask B), and offense target identification (subtask C). Our team has participated in all the three subtasks. We have developed machine learning and deep learning-based ensembles of models. We have achieved F1-scores of 0.906, 0.552, and 0.623 in subtask A, B, and C respectively. While our performance scores are promising for subtask A, the results demonstrate that subtask B and C still remain challenging to classify.
机译:本文介绍了我们的团队(AdelaideCyc)为Semeval Task 12(Offenseval 2020)开发了社交媒体的攻击语言。 挑战重点关注三个子任务 - 冒犯性语言识别(子任务A),冒犯型识别(SubTask B)和冒犯目标识别(子任务C)。 我们的团队参加了所有三个子组织。 我们开发了机器学习和基于深度学习的模型集合。 我们分别在子任务A,B和C中实现了0.906,0.552和0.623的F1分数。 虽然我们的性能分数是对子任务A的承诺,但结果表明,SubTask B和C仍然保持挑战以进行分类。

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