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The dataset contains the Yoruba data used to evaluate the performance of different weakly supervised learning techniques for text classification in low-resourced languages. The text was collected from the BBC news website for Yoruba and annotated by two native speakers. The data has seven categories based on the news headlines: Sports, Entertainment, Nigeria, Africa, World, Health, and Politics. It contains 1,908 sentences.
text classification, Yoruba, news topics, BBC
text classification, Yoruba, news topics, BBC
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 3 |

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