N.G. Yarushkina – Dr.Sc.(Eng.), Professor, Head of Department «Information Systems», Ulyanovsk State Technical University E-mail: jng@ulstu.ru

V.S. Moshkin – Ph.D.(Eng.), Associate Professor, Department «Information Systems», Ulyanovsk State Technical University E-mail: v.moshkin@ulstu.ru

A.A. Filippov – Ph.D.(Eng.), Associate Professor, Department «Information Systems», Ulyanovsk State Technical University E-mail: al.filippov@ulstu.ru

G.Yu. Guskov – Post-graduate Student, Department «Information Systems», Ulyanovsk State Technical University E-mail: guskovgleb@gmail.com

A.A. Romanov – Ph.D.(Eng.), Associate Professor, Department «Information Systems», Ulyanovsk State Technical University E-mail: romanov73@gmail.com

A.M. Namestnikov – Ph.D.(Eng.), Associate Professor, Department «Information Systems»,  Ulyanovsk State Technical University

E-mail: nam@ulstu.ru

The article presents the architecture of the developed intelligent software tool for the semantic analysis of social networks. This software implements new algorithms for hybridization of ontological analysis with natural language processing methods for extracting the semantic and sentiment of a component of unstructured text resources. The authors analyze the graphical knowledge base model of the ontology repository. An original algorithm for translating the RDF/OWL ontology into a graphical knowledge base is also proposed.

1. Chetviorkin I., Loukachevitch N. Sentiment Analysis Track at ROMIP-2012. Computer linguistics and intellectual technologies. Computer linguistics and intellectual technologies: Dialogue-2013. Sat. scientific articles V. 2. P. 40−50.
2. The Heart of the Elastic Stack. URL = https://www.elastic.co/products/elasticsearch (data obrashheniya 15.05.2018).
3. García-Moya L., Anaya-Sanchez H., Berlanga-Llavori R.. Retrieving product features and opinions from customer reviews // IEEE Intelligent Systems. 2013.  28(3). P. 19−27.
4. Key Trends to Watch in Gartner 2012 Emerging Technologies Hype Cycle. URL = http://www.forbes.com/sites/ gartnergroup/2012/09/18/key-trends-to-watch-in-gartner2012-emerging-technologies-hype-cycle-2 (data obrashheniya 15.05.2018).
5. Gjoka M. et al. Practical recommendations on crawling online social networks // IEEE Journal on Selected Areas in Communications. 2011. V. 29. № 9. P. 1872−1892.
6. Introducing the Neo4j Graph Platform. URL = https://neo4j.com (data obrashheniya 15.05.2018).
7. Leskovec J., Faloutsos C. Sampling from large graphs // Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining. 2006. ACM. P. 631−636.
8. MongoDB. For Giant ideas. URL = https://www.mongodb.com (data obrashheniya 15.05.2018).
9. OWL Web Ontology Language Overview. URL = https://www.w3.org/TR/owl-features (data obrashheniya 15.05.2018).
10. Resource Description Framework (RDF). URL = https://www.w3.org/RDF (data obrashheniya 15.05.2018).
11. Pallis G., Zeinalipour-Yazti D., Dikaiakos M. Online Social Networks: Status and Trends. New Directions in Web Data Management 1 // Studies in Computational Intelligence. 2011. V. 331. P. 213−234.
12. Pang B., Lee L., Vaithyanathan S. Thumbs up? Sentiment Classification using Machine Learning Techniques. 2002. P. 79−86.
13. Representational state transfer. URL = https://en.wikipedia.org/wiki/ Representational_state_transfer (data obrashheniya 15.05.2018).
14. Turney P. Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews // Proceedings of the Association for Computational Linguistics. 2002. P. 417−424.
15. Yarushkina N., Filippov A., Moshkin V. Development of the unified technological platform for constructing the domain knowledge base through the context analysis // Communications in Computer and Information Science. 2017. V. 754. P. 62−72.
16. Antonova A., Solov'ev A. Ispol'zovanie metoda uslovny'x sluchajny'x polej dlya obrabotki tekstov na russkom yazy'ke. Komp'yuternaya lingvistika i intellektual'ny'e texnologii: «Dialog-2013» // Sb. nauch. statej. № 12 (19). M.: Izd-vo RGGU. 2013. S. 27−44.
17. Pazel'skaya A., Solov'ev A. Metod opredeleniya e'moczij v tekstax na russkom yazy'ke // Sb. nauchny'x statej «Komp'yuternaya lingvistika i intellektual'ny'e texnologii «Dialog-2011». M.: Izd-vo RGGU. 2011. № 11(18). S. 510−523.
18. Tarasov D. Glubokie rekurrentny'e nejronny'e seti dlya aspektno-orientirovannogo analiza tonal'nosti otzy'vov pol'zovatelej na razlichny'x yazy'kax // Po materialam ezhegodnoj Mezhdunar. konf. «Dialog». Doklady' speczial'ny'x sekczij. V 2-x tomax. M.: Izd-vo RGGU. 2015. T. 2. № 14(21). S. 53−64.