Xin ZHAO Wayne, Jing JIANG, , Jing HE, , &
Latent Dirichlet Allocation (LDA) has been widely used in textual analysis. The original LDA is used to find hidden "topics" in the documents, where a topic is a subject like "arts" or "education" that is discussed in the documents. The original setting in LDA, where each word has a topic label, may not work well with Twitter as tweets are short and a single tweet is more likely to talk about one topic. Hence, Twitter-LDA...
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