Motivation of Individuals to Install Medical Applications: Analysis of the Open Text Data Using Machine Learning Methods
https://doi.org/10.25205/1818-7935-2022-20-4-77-89
Abstract
This paper describes the results of the open text data study, and on the basis of these data the features of the communicative interaction of individuals with mobile applications have been identified. Using the method of automatic data collection and analysis, 150 applications from the Google Store were analyzed in order to highlight the facts that motivate an individual’s entry into a communicative act with a mobile application. The article provides visualization of the text structures. Based on the data obtained, it was possible to identify the main characteristics of the communicative interaction of a user with the application; in particular, some hypotheses were put forward regarding the linearity of the communicative model used by individuals.
About the Author
A. V. Chizhik
Saint Petersburg State University
Russian Federation
Russian Federation
Anna V. Chizhik, leading research engineer, National Center for Cognitive Technologies of ITMO University; senior lecturer, Department of Information Systems in Arts and Humanities
Saint Petersburg
References
1. Antoniadis, I., Paltsoglou, S., Patoulidis, V. Post popularity and reactions in retail brand pages on Facebook. Int J Retail Distrib Manag., 2019, vol. 47, pp. 957–973.
2. Artetxe, M., Schwenk, H. Massively multilingual sentence embeddings for zero-shot cross-lingual transfer and beyond. Transactions of the Association for Computational Linguistics, 2018, vol. 7, pp. 597–610.
3. Maaten, L., Hinton, G. Visualizing data using t-SNE. Journal of machine learning research, 2008, vol. 9, pp. 2579–2605.
4. Borisova, E. G. Marketing linguistics: prospects and trends. Verkhnevolzhsky Philological Bulletin, 2016, no. 4, pp. 140–143. (in Russ.)
5. Mayorova, E. V. On sentiment analysis and prospects for its application. Social and humanitarian sciences. Russian and foreign literature. Ser. 6, Linguistics: Abstract journal, 2020, no. 4, pp. 78–87. (in Russ.)
6. Shabaev, Yu. P., Sadokhin, A. P. Cultural boundaries and markers in the ethnic space of modern Russia. Case Study Experience. Social Sciences and Modernity, 2012, no. 6, pp. 166–173. ( Russ.)
Review
For citations:
Chizhik A.V. Motivation of Individuals to Install Medical Applications: Analysis of the Open Text Data Using Machine Learning Methods. NSU Vestnik. Series: Linguistics and Intercultural Communication. 2022;20(4):77-89. (In Russ.) https://doi.org/10.25205/1818-7935-2022-20-4-77-89
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