We present the first Africentric SemEval Shared task, Sentiment Analysis for African Languages (AfriSenti-SemEval) - The dataset is available at https://github.com/afrisenti-semeval/afrisent-semeval-2023. AfriSenti-SemEval is a sentiment classification challenge in 14 African languages: Amharic, Algerian Arabic, Hausa, Igbo, Kinyarwanda, Moroccan Arabic, Mozambican Portuguese, Nigerian Pidgin, Oromo, Swahili, Tigrinya, Twi, Xitsonga, and Yor\`ub\'a (Muhammad et al., 2023), using data labeled with 3 sentiment classes. We present three subtasks: (1) Task A: monolingual classification, which received 44 submissions; (2) Task B: multilingual classification, which received 32 submissions; and (3) Task C: zero-shot classification, which received 34 submissions. The best performance for tasks A and B was achieved by NLNDE team with 71.31 and 75.06 weighted F1, respectively. UCAS-IIE-NLP achieved the best average score for task C with 58.15 weighted F1. We describe the various approaches adopted by the top 10 systems and their approaches.
翻译：我们提出了首个针对非洲语言的 SemEval 比赛，称为非洲语言情感分析（AfriSenti-SemEval）- 数据集可在 https://github.com/afrisenti-semeval/afrisent-semeval-2023 找到。AfriSenti-SemEval 是一个情感分类挑战，覆盖了14种非洲语言： 阿姆哈拉语，阿尔及利亚阿拉伯语，豪萨语，伊博语，基尼亚卢旺达语，摩洛哥阿拉伯语，莫桑比克葡萄牙语，尼日利亚皮钦语，奥罗莫语， 斯瓦希里语，提格里尼亚语，特威语、克松加语和约鲁巴语（Muhammad 等人，2023年），使用具有3个情感类别标记的数据。 我们提出了三个子任务：（1）任务A：单语言分类，收到44个提交；（2）任务B：多语言分类，收到32个提交；（3）任务C：零样本分类，收到34个提交。任务A和B的最佳表现分别由 NLNDE 团队获得，加权F1分别为71.31和75.06。UCAS-IIE-NLP 在任务C 中获得了最佳平均得分，加权F1 为58.15。我们描述了前10个系统及其方法采用的各种方法。
相关内容
微信扫码咨询专知VIP会员