phone +7 (3412) 91 60 92

Archive of Issues


Russia Izhevsk
Year
2019
Volume
29
Issue
1
Pages
106-116
<<
>>
Section Computer science
Title Logical analysis of emotions in text from natural language
Author(-s) Beltyukov A.P.a, Abbasi M.M.a
Affiliations Udmurt State Universitya
Abstract The study of emotional text analysis today is one of the most interesting and developing areas. The emotions presented in the text and their analysis are a special topic of our interest. In this article, we will explore the various modal judgments in logic, the emotional model and their connection with the analysis of emotions. We will offer interpretations of some simple modalities in connection with information technologies for analyzing emotions in texts. We will expand the logic of the possible worlds; our modalities will better explain and comprehend this logic of the perceived state of the environment. We are presenting the logical formulas for defining the most common modalities for analyzing emotions from text. Our work is a continuation of the work done on modalities with more flexibility and completeness. The paper discusses the logical properties of emotional modalities, the logic of emotional evaluations and the definition of various modalities for analyzing emotions. We propose six different definitions of modalities and use three theorems to prove our hypothesis. This methodology also sets the directions for future research on logical modalities for analyzing emotions from text.
Keywords text analysis, natural language processing, emotional modalities, emotion analysis
UDC 510.643
MSC 03B45
DOI 10.20537/vm190110
Received 15 February 2019
Language English
Citation Beltyukov A.P., Abbasi M.M. Logical analysis of emotions in text from natural language, Vestnik Udmurtskogo Universiteta. Matematika. Mekhanika. Komp'yuternye Nauki, 2019, vol. 29, issue 1, pp. 106-116.
References
  1. Solovyev V., Polyakov V., Ivanov V., Anisimov I., Ponomarev A. An approach to semantic natural language processing of Russian texts, Research in Computing Science, 2013, issue 65, pp. 65-73. http://www.rcs.cic.ipn.mx/2013_65
  2. Shetty A., Bajaj R. Auto text summarization with categorization and sentiment analysis, International Journal of Computer Applications, 2015, vol. 130, issue 7, pp. 57-60. https://doi.org/10.5120/ijca2015907065
  3. Bochkarev V., Solovyev V., Wichmann S. Universals versus historical contingencies in lexical evolution, Journal of The Royal Society Interface, 2014, vol. 11, issue 101, pp. 20140841. https://doi.org/10.1098/rsif.2014.0841
  4. Wiebe J., Wilson T., Cardie C. Annotating expressions of opinions and emotions in language, Language Resources and Evaluation, 2005, vol. 39, issue 2-3, pp. 165-210. https://doi.org/10.1007/s10579-005-7880-9
  5. Elizarov A.M., Kirillovich A.V., Lipachev E.K., Nevzorova O.A., Solovyev V.D., Zhiltsov N.G. Mathematical knowledge representation: semantic models and formalisms, Lobachevskii Journal of Mathematics, 2014, vol. 35, issue 4, pp. 348-354. https://doi.org/10.1134/S1995080214040143
  6. Kanda T., Hirano T., Eaton D., Ishiguro H. Interactive robots as social partners and peer tutors for children: a field trial, Human-Computer Interaction, 2004, vol. 19, issue 1, pp. 61-84. https://doi.org/10.1207/s15327051hci1901&2_4
  7. Pronoza E., Yagunova E. Comparison of sentence similarity measures for Russian paraphrase identification, 2015 Artificial Intelligence and Natural Language and Information Extraction, Social Media and Web Search FRUCT Conference (AINL-ISMW FRUCT), 2015, pp. 74-82. https://doi.org/10.1109/AINL-ISMW-FRUCT.2015.7382973
  8. Hagenau M., Liebmann M., Neumann D. Automated news reading: Stock price prediction based on financial news using context-capturing features, Decision Support Systems, 2013, vol. 55, issue 3, pp. 685-697. https://doi.org/10.1016/j.dss.2013.02.006
  9. Yu L.-C., Wu J.-L., Chang P.-C., Chu H.-S. Using a contextual entropy model to expand emotion words and their intensity for the sentiment classification of stock market news, Knowledge-Based System, 2013, vol. 41, pp. 89-97. https://doi.org/10.1016/j.knosys.2013.01.001
  10. Girlando M., Negri S., Olivetti N., Risch V. Conditional beliefs: From neighborhood semantics to sequent calculus, The Review of Symbolic Logic, 2018, vol. 11, issue 4, pp. 736-779. https://doi.org/10.1017/S1755020318000023
  11. Batrinca B., Treleaven Ph.C. Social media analytics: a survey of techniques, tools and platforms, Artificial Intelligence & Society, 2015, vol. 30, issue 1, pp. 89-116. https://doi.org/10.1007/s00146-014-0549-4
  12. Kharde V.A., Sonawane S.S. Sentiment analysis of twitter data: A survey of techniques, International Journal of Computer Applications, 2016, vol. 139, no. 11, pp. 5-15. https://doi.org/10.5120/ijca2016908625
  13. Dattu B.S., Gore D.V. A survey on sentiment analysis on twitter data using different techniques, International Journal of Computer Science and Information Technologies, 2015, vol. 6, no. 6, pp. 5358-5362. http://www.ijcsit.com/docs/Volume%206/vol6issue06/ijcsit20150606110.pdf
  14. Suttles J., Ide N. Distant supervision for emotion classification with discrete binary values, Computational Linguistics and Intelligent Text Processing, Berlin: Springer, 2013, pp. 121-136. https://doi.org/10.1007/978-3-642-37256-8_11
  15. Janda L.A., Solovyev V.D. What constructional profiles reveal about synonymy: A case study of Russian words for sadness and happiness, Cognitive Linguistics, 2009, vol. 20, issue 2, pp. 367-393. https://doi.org/10.1515/COGL.2009.018
  16. Lewis C.I. IV. - Implication and the algebra of logic, Mind, 1912, vol. 21, issue 84, pp. 522-531. https://doi.org/10.1093/mind/XXI.84.522
  17. Barcan R.C. A functional calculus of first order based on strict implication, The Journal of Symbolic Logic, 1946, vol. 11, no. 1, pp. 1-16. https://doi.org/10.2307/2269159
  18. Ioup G. Specificity and the interpretation of quantifiers, Linguistics and Philosophy, 1977, vol. 1, issue 2, pp. 233-245. https://link.springer.com/article/10.1007/BF00351105
  19. McKinsey J.C.C., Tarski A. Some theorems about the sentential calculi of Lewis and Heyting, The Journal of Symbolic Logic, 1948, vol. 13, issue 1, pp. 1-15. https://doi.org/10.2307/2268135
  20. Jonsson B., Tarski A. Boolean algebras with operators. Part I, American Journal of Mathematics, 1951, vol. 73, no. 4, pp. 891-939. https://doi.org/10.2307/2372123
  21. Jonsson B., Tarski A. Boolean algebras with operators. Part II, American Journal of Mathematics, 1952, vol. 74, no. 1, pp. 127-162. https://doi.org/10.2307/2372074
  22. Kripke S.A. A completeness theorem in modal logic, Journal of Symbolic Logic, 1959, vol. 24, issue 1, pp. 1-14. https://doi.org/10.2307/2964568
  23. Kripke S.A. The undecidability of monadic modal quantification theory, Mathematical Logic Quarterly, 1962, vol. 8, issue 2, pp. 113-116. https://doi.org/10.1002/malq.19620080204
  24. Kripke S.A. Semantical analysis of modal logic I. Normal modal propositional calculi, Zeitschrift für Mathematische Logik und Grundlagen der Mathematik, 1963, vol. 9, issues 5-6, pp. 67-96. https://doi.org/10.1002/malq.19630090502
  25. Kripke S.A. Semantical analysis of modal logic II. Non-normal modal propositional calculi, The theory of models: Proceedings of the 1963 International Symposium at Berkeley, Amsterdam: North-Holland Publishing Company, 1963, pp. 206-220. https://doi.org/10.1016/B978-0-7204-2233-7.50026-5
  26. Hintikka J. Cogito, Ergo Sum as an inference and a performance, The Philosophical Review, 1963, vol. 72, issue 4, pp. 487-496. https://doi.org/10.2307/2183033
  27. Bull R., Segerberg K. Basic modal logic, Handbook of Philosophical Logic, Dordrecht: Springer, 1984, pp. 1-88. https://doi.org/10.1007/978-94-009-6259-0_1
  28. Boolos G.S. The logic of provability, Cambridge: Cambridge University Press, 1994. https://doi.org/10.1017/CBO9780511625183
  29. Rahman S., Symons J., Gabbay D.M., van Bendegem J.P. Logic, epistemology, and the unity of science, Dordrecht: Springer, 2004. https://doi.org/10.1007/978-1-4020-2808-3
  30. Lellmann B., Pattinson D. Sequent systems for Lewis' conditional logics, Logics in Artificial Intelligence. JELIA 2012, Berlin: Springer, 2012, pp. 320-332. https://doi.org/10.1007/978-3-642-33353-8_25
  31. Tishkovsky D., Schmidt R.A., Khodadadi M. The tableau prover generator MetTeL2, Logics in Artificial Intelligence. JELIA 2012, Berlin: Springer, 2012, pp. 492-495. https://doi.org/10.1007/978-3-642-33353-8_41
  32. Lyaletski A. Evidence algorithm and search in first-order logics, Journal of Automated Reasoning, 2015, vol. 55, issue 3, pp. 269-284. https://doi.org/10.1007/s10817-015-9346-0
  33. Alama J., Heskes T., Kühlwein D., Tsivtsivadze E., Urban J. Premise selection for mathematics by corpus analysis and kernel methods, Journal of Automated Reasoning, 2014, vol. 52, issue 2, pp. 191-213. https://doi.org/10.1007/s10817-013-9286-5
  34. Orlandelli E. Proof analysis in deontic logics, Deontic Logic and Normative Systems, 2014, pp. 139-148. https://doi.org/10.1007/978-3-319-08615-6_11
  35. Lellmann B., Pimentel E. Proof search in nested sequent calculi, Logic for Programming, Artificial Intelligence, and Reasoning. LPAR 2015, Berlin: Springer, 2015, pp. 558-574. https://doi.org/10.1007/978-3-662-48899-7_39
Full text
<< Previous article
Next article >>