Various fields such as news communication, literature, history, culture, poetry, ancient Chinese classics and philosophy.
LDA topic model (Latent Dirichlet Allocation Topic Model, LDA-TM), because of its distant reading and super bookshelf functions, can visually present the hidden content of a single text and a massive text library in the form of topic word clustering. Semantic structures are increasingly used to assist humanistic explanations and arguments, and now cover various fields such as journalism, literature, history, culture, poetry, ancient Chinese classics, and philosophy.
For example, the Chinese-Chinese topic model jointly developed by Xi'an Jiaotong University and Indiana University in the United States is an LDA topic model based on the ancient Chinese text corpus.