Sentiment Analysis (SA) is a subset of Natural Language Processing (NLP) which has become a promising research area enabling the provision of language specific services. Although research in high resource languages such as English and Chinese has achieved promising results, research in low resource African languages such as Sesotho is still in its infancy due to limited text and speech datasets. This study contributes in this regard by availing the Sesotho News (SN) dataset, as an annotated dataset for the SA and Aspect Based Sentiment Analysis (ABSA) tasks.
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