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For more information on topic modeling in health science, including proposed applications and functions, see studies by Valdez et al [13] and Valdez and Goodson [25].
Coherence score cross-validation refers to an iterative analysis to identify the optimal number of topics for a given corpus. Coherence score cross-validation was completed by programming a computer to iteratively run an LDA topic model for an increasing k number of topics.
J Med Internet Res 2023;25:e48405
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Valdez and Patterson [31] propose that computationally driven analyses can complement and verify traditional quantitative or qualitative research findings. Therefore, this study aims to investigate longitudinal mpox-related narratives on social media using deep-learning techniques.
The mpox outbreak marks the first public health emergency and response following a once-in-a-generation global pandemic.
J Med Internet Res 2023;25:e43841
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Valdez et al [15] have provided examples of exploratory topic models in practice. The second step uses an iterative topic model analysis that meta-analytically generates models with an increasing number of topics per corpus (ie, 1 topic, 2 topics…20 topics) [16]. This analysis generates a coherence score for each iteration, such that higher scores are equated with better model fit and interpretability.
JMIR Infodemiology 2021;1(1):e29011
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