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Uncovering the Reasons Behind COVID-19 Vaccine Hesitancy in Serbia: Sentiment-Based Topic Modeling
NMF is a nonprobabilistic method based on matrix decomposition actively used for topic modeling [44,45]. It has also been applied to the theme of COVID-19 to determine the main pandemic health effects [34] and the public sentiment toward vaccination [22]. Compared to LDA, which gives more general descriptions of broader topics [46], the architecture of NMF enables it to find more detailed, clear-cut, and coherent topics [37,46,47].
J Med Internet Res 2022;24(11):e42261
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CNN: convolutional neural network; NMF: utilized nonnegative matrix factorization.
We used the Ar COV-19 [16] dataset, which is an ongoing collection of Arabic tweets related to COVID-19 starting from January 27, 2020. The tweets were collected using the Twitter search application programming interface (API) to obtain the most popular tweets using different queries, such as simple keywords (eg, Corona), hashtags (eg, #Corona), or phrases (eg, novel Coronavirus).
J Med Internet Res 2020;22(12):e22609
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