JCT at SemEval-2023 Tasks 12 A and 12B: Sentiment Analysis for Tweets Written in Low-resource African Languages using Various Machine Learning and Deep Learning Methods, Resampling, and HyperParameter Tuning
Ron Keinan, Yaakov HaCohen‐Kerner · 2023
In this paper, we describe our submissions to the SemEval-2023 contest.We tackled subtask 12 -"AfriSenti-SemEval: Sentiment Analysis for Low-resource African Languages using Twitter Dataset".We developed different models for 12 African languages and a 13 th model for a multilingual dataset built from these 12 languages.We applied a wide variety of word and char n-grams based on their tfidf values, 4 classical machine learning methods, 2 deep learning methods, and 3 oversampling methods.We used 12 sentiment lexicons and applied extensive hyperparameter tuning.