| Popis: |
It is proposed a method for constructing and using semantic models (SM) for the purpose of continuous monitoring of public opinion, opinion mining (OM). Under the semantic model in the framework of this work, it is implied the subject domain model, which has the form of a directed graph, the vertices of which correspond to the concepts of the domain, and the arcs define the relations between them. Semantic models make it possible to use the results of linguistic statistical analysis of texts (Text Mining) and the use of Information Extraction methods contained in texts from the Internet for opinion mining. While the existing public opinion analysis projects are more focused on one-time (static) public opinion research on objects and phenomena, it is proposed a method for automated construction and use of SM based on continuous monitoring of public opinion on the Internet. The OM procedure consists of three steps: the construction and clustering of the SM; selection of documents and the sentiment definition of topics; visualization of results. The SM construction using the compactified horizontal visibility graph algorithm, the use of cluster analysis methods for determining relevant topics, estimating the proportion and tonality of individual sub-themes in the overall thematic information flow is shown. As examples, the models of subject areas corresponding to the topics: «One Belt, One Road», «Nord Stream», «Genetically Modified Organisms» are examined. The obtained results confirm the possibility of using the proposed method of opinion monitoring in various subject areas. |
