Sentiment Analysis of Weibo Comments based on LDA Model
DOI:
https://doi.org/10.54097/hset.v24i.3883Keywords:
LDA Model; Weibo; Sentiment Analysis.Abstract
The essence of LDA (Latent Dirichlet Allocation) model is a generative Bayesian probability model that contains three layers of words, topics and corpus (sometimes called document set). Under the LDA algorithm theory, each document represents a probability distribution formed by some topics, and each topic represents a probability distribution formed by many words. Therefore, the model fitting results will present the core keywords and specific probabilities of each topic, and researchers can interpret the meaning of the document according to the model results. In this paper, we hope to use the LDA model as the basis for the emotional analysis of microblog comments.
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