Misinformation detection in Luganda-English code-mixed social media text
dc.contributor.author | Nabende, Peter | |
dc.contributor.author | Kabiito, David | |
dc.contributor.author | Babirye, Claire | |
dc.contributor.author | Tusiime, Hewitt | |
dc.contributor.author | Nakatumba-Nabende, Joyce | |
dc.date.accessioned | 2022-12-29T13:47:24Z | |
dc.date.available | 2022-12-29T13:47:24Z | |
dc.date.issued | 2021 | |
dc.description.abstract | The increasing occurrence, forms, and negative effects of misinformation on social media platforms has necessitated more misinformation detection tools. Currently, work is being done addressing COVID-19 misinformation however, there are no misinformation detection tools for any of the 40 distinct indigenous Ugandan languages. This paper addresses this gap by presenting basic language resources and a misinformation detection data set based on code-mixed Luganda- English messages sourced from the Facebook and Twitter social media platforms. Several machine learning methods are applied on the misinformation detection data set to develop classification models for detecting whether a code-mixed Luganda-English message contains misinformation or not. A 10-fold cross validation evaluation of the classification methods in an experimental misinformation detection task shows that a Discriminative Multinomial Na¨ıve Bayes (DMNB) method achieves the highest accuracy and F-measure of 78.19% and 77.90% respectively. Also, Support Vector Machine and Bagging ensemble classification models achieve comparable results. These results are promising since the machine learning models are based on n-gram features from only the misinformation detection data set. | en_US |
dc.identifier.citation | Nabende, P., Kabiito, D., Babirye, C., Tusiime, H., & Nakatumba-Nabende, J. (2021). Misinformation detection in Luganda-English code-mixed social media text. arXiv preprint arXiv:2104.00124. | en_US |
dc.identifier.uri | https://arxiv.org/abs/2104.00124 | |
dc.identifier.uri | https://nru.uncst.go.ug/handle/123456789/6746 | |
dc.language.iso | en | en_US |
dc.publisher | . arXiv preprint arXiv | en_US |
dc.title | Misinformation detection in Luganda-English code-mixed social media text | en_US |
dc.type | Other | en_US |
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