Jianyu Li


2023

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PingAnLifeInsurance at SemEval-2023 Task 12: Sentiment Analysis for Low-resource African Languages with Multi-Model Fusion
Meizhi Jin | Cheng Chen | Mengyuan Zhou | Mengfei Yuan | Xiaolong Hou | Xiyang Du | Lianxin Jiang | Jianyu Li
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)

This paper describes our system used in the SemEval-2023 Task12: Sentiment Analysis for Low-resource African Languages using Twit- ter Dataset (Muhammad et al., 2023c). The AfriSenti-SemEval Shared Task 12 is based on a collection of Twitter datasets in 14 African languages for sentiment classification. It con- sists of three sub-tasks. Task A is a monolin- gual sentiment classification which covered 12 African languages. Task B is a multilingual sen- timent classification which combined training data from Task A (12 African languages). Task C is a zero-shot sentiment classification. We uti- lized various strategies, including monolingual training, multilingual mixed training, and trans- lation technology, and proposed a weighted vot- ing method that combined the results of differ- ent strategies. Substantially, in the monolingual subtask, our system achieved Top-1 in two lan- guages (Yoruba and Twi) and Top-2 in four languages (Nigerian Pidgin, Algerian Arabic, and Swahili, Multilingual). In the multilingual subtask, Our system achived Top-2 in publish leaderBoard.