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Cognitive Linguistics Methods in Applied Research

Major: Philology
Code of Subject: 8.035.00.M.29
Credits: 3
Department: Applied Linguistics
Lecturer: O.P. Levchenko, Doctor of Philology, Prof.
Semester: 4 семестр
Mode of Study: заочна
Learning outcomes:
By the end of the course, students should achieve the following learning outcomes:
Know:
PLO1 - be able to demonstrate in-depth knowledge and understanding of the fundamental principles of linguistics, know the trends of applied linguistics and areas of linguistic study in Ukraine and, in general, in the world;
PLO2 - be aware of the linguistic problems of man and society and be able to find optimal solutions;
PLO4 - be able to demonstrate advanced knowledge of current scientific methods of linguistic research within the communicative and cognitive areas of linguistics;
Be able to:
PLO5 - be able to correlate the conceptual apparatus of theoretical and applied linguistics, translation studies and theory of intercultural communication with real facts and phenomena of professional activity and use it to solve professional problems;
PLO10 - be able to effectively perceive, store, process and transmit linguistic information, to foresee the peculiarities of information perception and prevent the occurrence of communicative failures;
PLO11 - be able to model communicative acts of different types: monologue, dialogue and polylogue; taking into account culturally specific features of the linguistic community;
PLO21 - be able to structure and integrate knowledge from different fields of professional activity, creatively use and develop it in the process of solving professional problems;
PLO27 - be able to critically evaluate experience from the perspective of recent advances in philology and computer science and social work.
Required prior and related subjects:
General Linguistics
Formal Models for Lexis and Grammar Description
Summary of the subject:
The change of scientific paradigms in linguistics and formation of cognitive linguistics (the definition of scientific paradigm; linguistic paradigms in diachrony; paradigmatic reorientation of modern linguistics: affirmation of anthropocentric linguistics; emergence and development of cognitive linguistics; basic principles of cognitive linguistics). Theory and methodology of conceptual analysis (the concept of categorization; research on principles of language categorization; the basic level of categorization). The concept as the central term of modern anthropological linguistics. Methodology of concept description in scientific research (conceptual analysis as a general concept analysis; conceptual analysis as a method of studying abstract nomen). Approaches to concept modeling. Cognitive modeling of the system of conceptual structures (prototype theory; image scheme, scenario, frame). A cognitive approach to metaphor and methods for its identification in cognitive linguistics. Identification of metaphor in modern linguistic studies.
Recommended Books:
Al-Saggaf, M. A., Yasin, M. S. M., & Ho-Abdullah, I.: Semasiological corpus-based approach to identifying conceptual metaphor (SCAICM). Cognitive Linguistic Studies, 2(1), pp. 116-128 (2015).
ATT-Meta Project, https://www.cs.bham.ac.uk/~jab/ATT-Meta/Databank/
Birke, J., Sarkar, A.: A clustering approach for nearly unsupervised recognition of non-literal language. In: 11th Conference of the European Chapter of the Association for Computational Linguistics (2006).
Caruso, A. S.: A corpus-based metaphor analysis of news reports on the Middle East Road Map peace process (2011), www.birmingham.ac.uk/research/activity/corpus/ pub-lications/conference-archives/2011-birmingham.aspx
Croft, William, and D. Alan Cruse. Cognitive linguistics. Cambridge University Press, 2004.
David, O., Matlock, T.: Cross-linguistic automated detection of metaphors for poverty and cancer. Language and Cognition, 10(3), 467-493 (2018).
Deignan, A.: Metaphor and Corpus Linguistics. Amsterdam/Philadelphia: John Benja-mins (2005).
Dolan, W. B.: Metaphor as an emergent property of machine-readable dictionaries. In: Proceedings of Representation and Acquisition of Lexical Knowledge: Polysemy, Am-biguity, and Generativity, 27-29 (1995).
Evans, Vyvyan, and Melanie Green. Cognitive linguistics: An introduction. Routledge, 2018.
Evans, Vyvyan. Glossary of cognitive linguistics. Edinburgh University Press, 2007.
Fillmore C.J. 1968 The case for case // E. Bach, R.T. Harms eds. Universals in linguistic theory. – L. etc.: Holt, Rinehart and Winston, 1968. 1-88.
Fillmore C.J. The case for case reopened // P. Cole, J.M. Sadock eds. Grammatical relations. – N.Y. etc.: Acad. Press, 1977. 59-81.
Gandy L., Allan N., Atallah M., Frieder O., Howard N., Kanareykin S., Koppel M., Last M., Neuman Y., Argamon1 Sh.: Automatic Identification of Conceptual Met-aphorsWith Limited Knowledge. In: Proceedings of the Twenty-Seventh AAAI Con-ference on Artificial Intelligence (2013), https://www.researchgate.net/publication/26279 4264_Automatic_Identification_of_Conceptual_Metaphors_with_Limited_Knowledge
Gceraerts, D., Cognitive Grammar and the History of Lexical Semantics. - In: Rudzka-Ostyn 1988, 647-677.
Geeraerts, Dirk, ed. Cognitive linguistics: Basic readings. Vol. 34. Walter de Gruyter, 2006.
Goatly, A.: The language of metaphors. Routledge, London (1997).
Grac v.3., http://www.parasolcorpus.org/bonito/run.cgi/
Hampe, Beate, and Joseph E. Grady, eds. From perception to meaning: Image schemas in cognitive linguistics. Vol. 29. Walter de Gruyter, 2005.
Jackendoff R.S. Semantics and cognition. – Cambr. (Mass.): MIT, 1983.
Koivisto-Alanko, P., Tissari, H.: Sense and sensibility: Rational thought versus emotion in metaphorical language. Corpus-Based Approaches to Metaphor and Metonymy, Ber-lin. Mouton de Gruyter (2006).
Koller, V., Hardie, A., Rayson, P., Semino, E.: Using a semantic annotation tool for the analysis of metaphor in discourse. Metaphorik. de, 15(1), pp. 141-160 (2008).
Lakoff, G., M. Johnson. Metaphors We Live By Chicago: University of Chicago Press, 1980
Lakoff, G., The Contemporary Theory of Metaphor. Ortony, A. (ed.), Metaphor and Thought. Cambridge: Cambridge University Press. Second edition, 1993, 202-251.
Lakoff, G., Women, Fire, and Dangerous Things. Wat Categories Reveal About the Mind. Chicago: Univ. of Chicago Press, 1987.
Langacker, R., Concept, Image, and Symbol: The Cognitive Basis of Grammar. Berlin/New York: Mouton de Gruyter, 1991
Langacker, R., Foundations of Cognitive Grammar, Vol. 1: Theoretical Prerequisites. Stanford: Stanford University Press, 1987.
Levin, L. S., Mitamura, T., MacWhinney, B., Fromm, D., Carbonell, J.G., Feely, W., Frederking, R. E., Gershman, A., Ramirez, C.: Resources for the Detection of Conven-tionalized Metaphors in Four Languages. In: LREC, pp. 498-501 (2014).
LNCS Homepage, http://www.springer.com/lncs, last accessed 2016/11/21.
Martin, J. H.: A corpus-based analysis of context effects on metaphor comprehension. Trends in Linguistics Studies and Monographs, de Gruyter, Berlin; N. Y. (2006).
Mason, Z. J.: CorMet: a computational, corpus-based conventional metaphor extraction system. Computational linguistics, 30(1), pp. 23-44 (2004).
MetaNet, https://metanet.icsi.berkeley.edu/metanet/
Nayak, S., Mukerjee, A.: A grounded cognitive model for metaphor acquisition. In: Twenty-Sixth AAAI Conference on Artificial Intelligence (2012, July).
Neuman, Y., Assaf, D., Cohen, Y., Last, M., Argamon, S., Howard, N., Frieder, O.: Metaphor identification in large texts corpora. PloS one, 8(4), (2013).
Shimizu, T., Shimokura, M.: Developing the T-Scope (version 2.0) program for a statis-tical approach to business metaphor analysis. Osaka Keidai Ronshu (The Journal of Osaka University of Economics), 61(2), pp. 329-343 (2010).
Shimizu, T.: Mental Distance’concept for chronological metaphor analysis of business executive speeches. Osaka Keidai Ronshu (The Journal of Osaka University of Eco-nomics), 60(6), pp. 245-268 (2010).
Shutova, E., Teufel, S., Korhonen, A.: Statistical metaphor processing. Computational Linguistics, 39(2), pp.1-92 (2012).
Statistics used in the Sketch Engine system, https://www.sketchengine.eu/wp-content/uploads/ske-statistics.pdf
Steen, G. J., Dorst, A. G., Herrmann, J. B., Kaal, A. A., Krennmayr, T., Pasma, T.: A method for linguistic metaphor identification: From MIP to MIPVU. John Benjamins, Amsterdam (2010).
Stickles, E., Dodge, E., Hong, J.: A construction-driven, MetaNet-based approach to metaphor extraction and corpus analysis. In: 12th meeting of Conceptual Structure, Discourse, and Language (CSDL 12), Santa Barbara, California (2014, November).
Sweetser Eve E. Ted Sanders, Jose Sanders and Eve Sweetser. Causality, cognition and communication: A mental space analysis of subjectivity in causal connectives. In Ted Sanders and Eve Sweetser (eds.) Causal categories in discourse and cognition. Berlin: Mouton de Gruyter, 2009, 19-60.
Sweetser Eve E.Looking at space to study mental spaces: Co-speech gesture as a crucial data source in cognitive linguistics. In Monica Gonzalez-Marquez, Irene Mittleberg, Seana Coulson and Michael Spivey (eds.), Methods in Cognitive Linguistics. Amsterdam: John Benjamins. 2006, 203-226.
Sweetser Eve E.Myriam Bouveret and Eve Sweetser. Multi-frame semantics, metaphoric extensions and grammar. BLS, 2009, 35.
Turney, P. D., Neuman, Y., Assaf, D., Cohen, Y.: Literal and metaphorical sense iden-tification through concrete and abstract context. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (pp. 680-690). Association for Computational Linguistics (2011, July).
VU Amsterdam Metaphor Corpus, http://ota.ahds.ac.uk/headers/2541.xml.
Wallington, A. M., Barnden, J. A., Buchlovsky, P., Fellows, L., Glasbey, S. R.: Meta-phor annotation: A systematic study. COGNITIVE SCIENCE RESEARCH PAPERS-UNIVERSITY OF BIRMINGHAM CSRP, 2(2), pp. 3-4 (2003).
Assessment methods and criteria:
Current assessment during tutorials, seminars is carried out in order to reveal students’ performance in the following forms:
• selective oral questioning;
• checking individual tasks;
• evaluation of postgraduate students’ engagement in the lesson, suggestions made, original decisions, clarifications and definitions, additions to previous answers, etc.
The examination consists of:
• a) test - choosing the correct answers;
• b) problematic task - creating problematic situations;
• c) question-answer mode - identifying cause and effect relations;
• d) situational tasks - answer taking into account a specific situation;
• e) reproductive issues - determination of practical significance;
The final assessment is carried out on the basis of the results of current assessment and examination. Current assessment - 50 points (preparation for classes - 40 points, individual task - 10 points), examination - 50 points (written - 25 points, oral - 25 points).