A Machine Learning Model for detecting Covid-19 Misinformation in Swahili Language
نویسندگان
چکیده
The recorded cases of corona virus (COVID-19) pandemic disease are millions and its mortality rate was maximized during the period from April 2020 to January 2022. Misinformation arose regarding this threat, which spread through social media platforms, especially Twitter, often spreading confusion, turmoil, panic public. To identify such misinformation, a machine learning model is needed detect whether given information true (true information) or not (misinformation). aim paper present machine-learning for detecting COVID-19 misinformation in Swahili language tweets. five algorithms that were trained related Logistic Regression (LR), Support Vector Machine (SVM), Bagging Ensemble (BE), Multinomial Naïve Bayes (MNB), Random Forest (RF). study used qualitative research method because non-numerical data, i.e. text, used. Python programming data analysis due powerful libraries as pandas numpy. Four metrics evaluate performance. results revealed SVM achieved highest accuracy 83.67% followed by LR with 82.47%. MNB best precision 92.00% terms recall F1-score, RF, 84.82% 81.45%, respectively. This will enable public easily circulated on Twitter platform.
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ژورنال
عنوان ژورنال: Engineering, Technology & Applied Science Research
سال: 2023
ISSN: ['1792-8036', '2241-4487']
DOI: https://doi.org/10.48084/etasr.5636