Development of a software for the semantic analysis of social media content

Abstract

The paper presents a developed intelligent tool for Opinion Mining of social media. In addition, the article presents new algorithms to the hybridization of ontological analysis and methods of knowledge engineering with methods of nature language processing (NLP) for extracting the semantic and emotional component of semi-structured and unstructured text resources. These approaches will improve the efficiency of the analysis of social media content-specific data and fuzziness of natural language. Also the original algorithm for translating the RDF/OWL-ontology into a graphical knowledge base is proposed. In addition, the article presents an approach to the inference on the ontology repository. The approach based on translating the SWRL constructs into the elements of the Cypher language.