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An Influence Prediction Model for Microblog Entries on Public Health Emergencies

research works on microblog influence are abundant. However, research on the influence of microblog in specific fields, such as public health emergencies, is relatively insufficient. This study attempts to propose a microblog influence prediction model for public health emergencies, which is composed of user, time, and content features and which uses the random forest method ( Breiman, 2001 ) and the Best Match 25-based latent Dirichlet allocation model (LDA-BM25) ( Li, 2013 ). As this model is constructed specifically for public health emergencies, it highlights the

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