CORPUS ANALYSIS OF SPEECH UNITS IN SOCIAL NETWORKS
Ключевые слова:
NLP, API, Twitter, Reddit, Facebook, LinkedIn.Аннотация
В данной статье описано использование электронной базы данных для изучения и проверки анализа речевых единиц в социальных сетях с помощью корпуса, выявления выраженных речевых изменений, их специфических особенностей и причин их изменений.
Библиографические ссылки
Computational Linguistics: An Introduction (Studies in Natural Language Processing). Cambridge University Press.
Taweh Beysolow. Applied Natural Language Processing with Python.California, 2018.
Michele Zappavigna. Discourse of Twitter and Social Media: How We Use Language to Create Affiliation on the Web. A&C Black, 2012.
David Bamman, Noah A. Smith. Contextualized Sarcasm Detection on Twitter. International Conference on Web and Social Media. Computer Science, Linguistics, 2015.
Abdurakhmonova, N., Tuliyev, U., Ismailov, A., & Abduvahobo, G. (2022). Uzbek electronic corpus as a tool for linguistic analysis. In Компьютерная обработка тюркских языков. TURKLANG 2022 (pp. 231-240).
Abduraxmonova, N. Z. Q., & Urazaliyeva, M. Y. (2022). O ‘zbek tili elektron korpusida (http://uzbekcorpus. uz/) og ‘zaki matnlar korpusini yaratishning nazariy va amaliy masalalari. Academic research in educational sciences, 3(3), 644-650.
Mengliev, D., Barakhnin, V., & Abdurakhmonova, N. (2021). Development of intellectual web system for morph analyzing of uzbek words. Applied Sciences, 11(19), 9117.
Jacob Eisenstein. Introduction to Natural Language Processing Adaptive Computation and Machine Learning series. MIT Press, 2019.
Cynthia Van Hee, Els Lefever, Veronique Hoste. Exploring the Realization of Irony in Twitter Data.International Conference on Web and Social Media, 2016.
D. Nguyen, A. Seza Doğruöz, F. D. Jong. Computational Sociolinguistics: A Survey. Computational Linguistics, 2016.
L. Jenny, Davis, T. Graham. Emotional consequences and attention rewards: the social effects of ratings on Reddit. Information Communication and Society 24(4):1-18, 2021.
J. Nathan Matias. Going Dark: Social Factors in Collective Action Against Platform Operators in the Reddit Blackout. Microsoft Research, 2015.
S. Michael, E. Bakshy, B. Karrer. Quantifying the invisible audience in social networks. International Conference on Human Factors in Computing Systems, 2013.
Abdurakhmonova, N. (2019). Dependency parsing based on Uzbek Corpus. In of the International Conference on Language Technologies for All (LT4All).
Agostini, A., Usmanov, T., Khamdamov, U., Abdurakhmonova, N., & Mamasaidov, M. (2021, January). Uzwordnet: A lexical-semantic database for the uzbek language. In Proceedings of the 11th Global Wordnet conference (pp. 8-19).
Загрузки
Опубликован
Выпуск
Раздел
Лицензия
Это произведение доступно по лицензии Creative Commons «Attribution» («Атрибуция») 4.0 Всемирная.
