Documenting Lexical Innovation in Azerbaijani Youth Speech: A Methodological Framework

Authors

DOI:

https://doi.org/10.69760/gsrh.0260304024

Keywords:

Azerbaijani youth speech, lexical innovation, neologisms, slang, borrowing, lexical documentation, digital communication

Abstract

Research on youth vocabulary requires a distinction between expressions that attract attention and lexical innovations supported by evidence. This article develops a methodological framework for documenting new forms, meanings, and uses in Azerbaijani youth speech. Drawing on sociolinguistics, word formation, digital discourse research, and computational approaches to lexical change, it separates the discovery of candidate items from the verification of novelty. The proposed procedure combines contextual recording, comparison with earlier sources, multidimensional classification, and documentation of uncertain decisions. It also distinguishes spoken interaction from digitally mediated writing and treats frequency, temporal persistence, and distribution across speakers as different indicators. A standard lexical record and a constructed Azerbaijani example illustrate how original forms, normalised entries, interpretations, and verification status can be maintained without conflating them. The article argues that a useful lexical database must preserve the relationship between an item and its attested uses, including evidence that challenges an initial interpretation. The framework provides a basis for future empirical research; it reports no newly collected corpus or statistical findings.

Author Biography

References

Androutsopoulos, J. (2015). Networked multilingualism: Some language practices on Facebook and their implications. International Journal of Bilingualism, 19(2), 185–205. https://doi.org/10.1177/1367006913489198

Babayev, J. (2022). Slang and its characteristic features. In G. Y. Gulyaev (Ed.), European research: Proceedings of the XXXV international scientific and practical conference (pp. 152–154). Nauka i Prosveshchenie.

Bender, E. M., & Friedman, B. (2018). Data statements for natural language processing: Toward mitigating system bias and enabling better science. Transactions of the Association for Computational Linguistics, 6, 587–604. https://doi.org/10.1162/tacl_a_00041

Crystal, D. (2006). Language and the Internet (2nd ed.). Cambridge University Press. https://doi.org/10.1017/CBO9780511487002

Durkin, P. (2014). Borrowed words: A history of loanwords in English. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199574995.001.0001

Eble, C. (1996). Slang and sociability: In-group language among college students. University of North Carolina Press.

Eckert, P. (2012). Three waves of variation study: The emergence of meaning in the study of sociolinguistic variation. Annual Review of Anthropology, 41, 87–100. https://doi.org/10.1146/annurev-anthro-092611-145828

Eisenstein, J., O'Connor, B., Smith, N. A., & Xing, E. P. (2014). Diffusion of lexical change in social media. PLOS ONE, 9(11), Article e113114. https://doi.org/10.1371/journal.pone.0113114

franzke, a. s., Bechmann, A., Zimmer, M., Ess, C., & Association of Internet Researchers. (2020). Internet research: Ethical guidelines 3.0. Association of Internet Researchers. https://aoir.org/reports/ethics3.pdf

Grieve, J., Nini, A., & Guo, D. (2017). Analyzing lexical emergence in modern American English online. English Language & Linguistics, 21(1), 99–127. https://doi.org/10.1017/S1360674316000113

Grieve, J., Nini, A., & Guo, D. (2018). Mapping lexical innovation on American social media. Journal of English Linguistics, 46(4), 293–319. https://doi.org/10.1177/0075424218793191

Hamilton, W. L., Leskovec, J., & Jurafsky, D. (2016). Diachronic word embeddings reveal statistical laws of semantic change. In K. Erk & N. A. Smith (Eds.), Proceedings of the 54th annual meeting of the Association for Computational Linguistics (Volume 1: Long papers) (pp. 1489–1501). Association for Computational Linguistics. https://doi.org/10.18653/v1/P16-1141

Hohenhaus, P. (2005). Lexicalization and institutionalization. In P. Štekauer & R. Lieber (Eds.), Handbook of word-formation (pp. 353–373). Springer. https://doi.org/10.1007/1-4020-3596-9_15

Hovy, D., & Prabhumoye, S. (2021). Five sources of bias in natural language processing. Language and Linguistics Compass, 15(8), Article e12432. https://doi.org/10.1111/lnc3.12432

Labov, W. (1972). Sociolinguistic patterns. University of Pennsylvania Press.

Schlechtweg, D., McGillivray, B., Hengchen, S., Dubossarsky, H., & Tahmasebi, N. (2020). SemEval-2020 Task 1: Unsupervised lexical semantic change detection. In A. Herbelot, X. Zhu, A. Palmer, N. Schneider, J. May, & E. Shutova (Eds.), Proceedings of the fourteenth workshop on semantic evaluation (pp. 1–23). International Committee for Computational Linguistics. https://doi.org/10.18653/v1/2020.semeval-1.1

Seidova, E., Babayev, J., Sadikhova, S., Aghayeva, G., & Mammadova, Z. (2026). AI-powered lexical innovation: Modeling neologisms with NLP. Scientific Work, 20(3), 171–179. https://doi.org/10.36719/2663-4619/127/171-179

Tagliamonte, S. A. (2016). Teen talk: The language of adolescents. Cambridge University Press. https://doi.org/10.1017/CBO9781139583800

Tagliamonte, S. A., & Denis, D. (2008). Linguistic ruin? LOL! Instant messaging and teen language. American Speech, 83(1), 3–34. https://doi.org/10.1215/00031283-2008-001

Würschinger, Q. (2021). Social networks of lexical innovation: Investigating the social dynamics of diffusion of neologisms on Twitter. Frontiers in Artificial Intelligence, 4, Article 648583. https://doi.org/10.3389/frai.2021.648583

Yule, G. (2020). The study of language (7th ed.). Cambridge University Press. https://doi.org/10.1017/9781108582889

Downloads

Published

2026-10-22

Issue

Section

Articles

How to Cite

Heyderova, N. (2026). Documenting Lexical Innovation in Azerbaijani Youth Speech: A Methodological Framework. Global Spectrum of Research and Humanities , 3(4), 238-249. https://doi.org/10.69760/gsrh.0260304024