Preview

The Review of Economy, the Law and Sociology

Advanced search

Text Data Parsing Method and its Potential for Thematic Analysis as a Tool for Exploratory Research

https://doi.org/10.24412/1998-5533-2024-4-300-303

Abstract

The relevance of the research topic is due to the increasing demand of researchers for the development and testing of a methodology aimed at obtaining pilot results based on social network data. The purpose of the study is to demonstrate the potential of the developed research design in solving the designated problem. To achieve the goal, a number of research tasks were solved: a research design was developed that solves the problem under consideration; the design was tested for the analysis of musical communities; the data were compared with research and analytical works in this area. Scientific and practical significance lies in the development of an original research design suitable for solving the methodological problem under consideration. The scientific novelty of the result is confirmed by the absence of uniform generally accepted approaches to solving the designated methodological problem that could be replicated by limited research resources.

About the Authors

A. V. Maltseva
Saint Petersburg State University
Russian Federation


S. D. Gurieva
Saint Petersburg State University
Russian Federation


T. S. Masharo
Saint Petersburg State University
Russian Federation


References

1. Ткач С., Воробьева П.Д., Русакова М.М. Опыт реализации дискурс-анализа и концептуального картирования сообществ здорового питания // Социология: методология, методы, математическое моделирование. 2023. № 56. С. 143–172. DOI: 10.19181/4m.2023.32.1.4.

2. Kaushik A., Naithani S. A comprehensive study of text mining approach // International Journal of Computer Science and Network Security (IJCSNS). 2016. Vol. 16. №. 2. Art. 69.

3. Miller S. Fox H., Ramshaw L., Weischedel R. A novel use of statistical parsing to extract information from text // 1st Meeting of the North American Chapter of the Association for Computational Linguistics. 2000. Р. 226–233.

4. Radovanović M., Ivanović M. Text mining: Approaches and applications // Novi Sad J. Math. 2008. Vol. 38. №. 3. Р. 227–234.

5. Alwidian S.A., Bani-Salameh H.A., Alslaity A.N. Text data mining: a proposed framework and future perspectives // International Journal of Business Information Systems. 2015. Vol. 18. №. 2. Р. 127–140.

6. Splichal S. In data we (don't) trust: The public adrift in data-driven public opinion models // Big Data & Society. 2022. Vol. 9. №. 1. Art. 20539517221097319.

7. Белая Е.К., Кашина М.А. K-pop, социальные сети, гендерные представления: проблемы презентации и восприятия (на примере творчества группы BTS) // Управленческое консультирование. 2022. № 11(167). С. 67–85.

8. Тагильцева Н.Г., Курлапов М.Н. Музыкальные предпочтения студентов негуманитарных специальностей технического университета // Педагогическое образование в России. 2024. № 2. С. 232–238.

9. Захваткин А.В., Темникова Е Ю. Музыкальные предпочтения молодежи как индикатор их психоэмоционального состояния // Ученые записки НТГСПИ. Серия: Педагогика и психология. 2023. № 4. С. 84–93.

10. Fiske J. The cultural economy of fandom // The adoring audience. – Routledge, 2002. Р. 30–49.

11. VK Музыка рассказывает, кого слушали в 2023 г. // ВКонтакте. URL: https://vk.com/press/music-2023 (дата обращения: 06.10.2023).


Review

For citations:


Maltseva A.V., Gurieva S.D., Masharo T.S. Text Data Parsing Method and its Potential for Thematic Analysis as a Tool for Exploratory Research. The Review of Economy, the Law and Sociology. 2024;(4):300-303. (In Russ.) https://doi.org/10.24412/1998-5533-2024-4-300-303

Views: 24

JATS XML


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1998-5533 (Print)