1. Moretti F., Conjectures on World Literature, New Left Review. Available at: https://newleftreview.org/issues/ii1/articles/franco-moretti-conjectures-on-world-literature (accessed: 10.10.2025).
2. Moretti F., Graphs, Maps, Trees: Abstract Models for a Literary History, Verso, London, 2005.
3. Moretti F., Distant Reading, Verso, London, 2013.
4. Kozan O., Close and distant reading in translation studies (a case of poetry), Istanbul University Journal of Translation Studies, 22 (2025) 127–147. DOI: 10.26650/iujts.2025.1555242
5. Gaballo V., The language of business, economics and finance: A corpus-driven, analytical discourse approach, EUM, Macerata, 2012.
6. Martínez Egido J.J., Creation of a corpus on the economic-financial discourse in Spanish: Preambles for the study of lexis modalization, Procedia – Social and Behavioral Sciences, 95 (2013) 276–283. DOI: 10.1016/j.sbspro.2013.10.648
7. Priola M.P., Molino A., Tizzanini G., Zicchino L., The informative value of central banks talks: A topic model application to sentiment analysis, Data Science in Finance and Economics, 2 (3) (2022) 181–204. DOI: 10.3934/dsfe.2022009
8. Alonso-Robisco A., Carbó J.M., Central bank digital currencies in discourse: Sentiment analysis with large language models, Economía y Sociedad Digital, 5 (1) (2023) 45–59. DOI: 10.1016/j.frl.2023.104643
9. Vaca C., Astorgano M., López-Rivero A.J., Tejerina F., Sahelices B., Interpretability of deep learning models in analysis of Spanish financial text, Neural Computing and Applications, 36 (10) (2024) 7509–7527. DOI: 10.1007/s00521-024-09474-8
10. Hu K., Li Q., Xie J., Pu Y., Guo Y., Using pre-trained models and graph convolution networks to find the causal relations among events in the Chinese financial text data, Multimedia Tools and Applications, 83 (7) (2024) 18699–18720. DOI: 10.1007/s11042-023-15496-6
11. Vazirani K., Evaluating the economic disparities in the world: Sentiment analysis on central bank speeches from third world and first world countries, International Journal of Information Technology, 16 (1) (2024) 69–76. DOI: 10.1007/s41870-023-01627-7
12. Loukas L., Fergadiotis M., Androutsopoulos I., Malakasiotis P., EDGAR-CORPUS: Billions of tokens make the world go round, Proceedings of the Third Workshop on Economics and Natural Language Processing, Association for Computational Linguistics, Punta Cana, 2021. pp. 13–18. DOI: 10.18653/v1/2021.econlp-1.2
13. Soares da Silva A., From economic crisis to austerity policies through conceptual metaphor: A corpus-based comparison of metaphors of crisis and austerity in the Portuguese press, The Language of Crisis Metaphors, frames and discourses, ed. by M. Huang, L.-L. Holmgreen, John Benjamins, Amsterdam, 2020. pp. 51–86. DOI: 10.1075/dapsac.87.02soa
14. Cheng W., Ho J., A Corpus Study of Bank Financial Analyst Reports: Semantic Fields and Metaphors, International Journal of Business Communication, 54 (3) (2015) 258–282. DOI: 10.1177/2329488415572790
15. García A.C., Translation in financial Spanish: A corpus-based study on the use of metaphor, Current Trends in Translation Teaching and Learning E, 6 (2019) 331–356.
16. Apresyan K.G., Metaforizatsiya v sovremennom finansovom diskurse (na materiale angloyazychnoy, russkoyazychnoy pressy [Metaphorization in contemporary financial discourse (based on English- and Russian-language press)], Lingvisticheskoye naslediye L.V. Shcherby v svete sovremennoy nauki o yazyke: sbornik nauchnykh trudov Mezhdunarodnoy nauchno-prakticheskoy konferentsii v ramkakh V Mezhdunarodnogo festivalya nauki [The linguistic heritage of L.V. Shcherba in the light of modern language science: a collection of scientific papers of the International Scientific and Practical Conference within the framework of the 5th International Science Festival], IIU MGOU, Moscow, 2020. pp. 5–11.
17. Telegin V.V., Monetarnyy diskurs: Kommunikativnaya sfera tsentralnogo banka Rossii [Monetary discourse: The communicative sphere of the Central Bank of Russia], Finansovyy diskurs: Aktualnyye aspekty issledovaniya [Financial Discourse: Current Aspects of Research], FLINTA, Moscow, 2022, pp. 74–92.
18. Boyacıoğlu E.Z., Adıgüzel T., Taş H., Türksever E., An emotional explanation of the interest decision: Twitter analysis in Türkiye, Ekonomi Maliye İşletme Dergisi, 6 (2) (2023) 82–99. DOI: 10.46737/emid.1311081
19. Derbisheva Z.K., Sravnitelnaya grammatika russkogo i turetskogo yazykov [Comparative Grammar of the Russian and Turkish Languages], FLINTA, Moscow, 2015.
20. Yazykovaya nominatsiya (Obshchiye voprosy) [Linguistic Naming (General Issues)], ed. by B.A. Serebrennikov, A.A. Ufimtseva, Nauka, Moscow, 1977.
21. Kozan O., Dil Dizgesinde Eşdizimlilik: Öğretim Odaklı Dilbilimsel Betimleme Örneği [Collocations in the Language System: A Linguistic Description for Pedagogical Purposes], Dil Eğitimi ve Araştırmaları Dergisi, 5 (2) (2019) 251–266. DOI: 10.31464/jlere.570068