[Objective] This paper proposes a framework for identifying subjects of online opinion from public health emergencies, aiming to utilizing the advantages of semantic recognition.[Methods] First, we constructed RDF triples with dependency parsing analysis and semantic role annotations from the perspectives of grammar, semantics, and pragmatics.Then, we decided the core nodes based on degrees of the semantic graph and PageRank values. Finally, we conducted an empirical study to discover the subjects of public opinion.[Results] We successfully constructed a semantic graph for public opinion topics, and discovered the core nodes focusing on events and governments.[Limitations] The depth of semantic recognition needs to be improved.[Conclusions] The proposed model could help us identify public opinion topics.
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