Сontent Analysis as a Method to Research the Attitude to Medicine in Modern Russia on the Basis of the Data Collected from the Users’ Posts in Social Networks “Vkontakte” and “Instagram” | South-Russian Journal of Social Sciences
Сontent Analysis as a Method to Research the Attitude to Medicine in Modern Russia on the Basis of the Data Collected from the Users’ Posts in Social Networks “Vkontakte” and “Instagram”
Vol. 20 (2019) No. 1, Sociological Interpretations
Vol. 20 (2019) No. 1
Sociological Interpretations

Сontent Analysis as a Method to Research the Attitude to Medicine in Modern Russia on the Basis of the Data Collected from the Users’ Posts in Social Networks “Vkontakte” and “Instagram”

Nikolskaya A.V.
Kosygin Russian State University
ORCID ID 0000-0001-8821-5177
Kostrigin A.A.
Kosygin Russian State University
ORCID ID 0000-0002-5454-7357
PDF (Russian)
https://doi.org/10.31429/26190567-20-1-72-90
https://doi.org/10.31429/26190567-20-1-72-90

How to Cite Array

Nikolskaya A.V., Kostrigin A.A. (2019) Сontent Analysis as a Method to Research the Attitude to Medicine in Modern Russia on the Basis of the Data Collected from the Users’ Posts in Social Networks “Vkontakte” and “Instagram”. South-Russian Journal of Social Sciences, 20 (1), pp. 72-90. DOI: 10.31429/26190567-20-1-72-90 (In Russian)
Submission Date 2018-07-13
Accepted Date 2018-12-20
Published Date 2019-03-23

Copyright (c) 2019 Анастасия Всеволодовна Никольская, Артем Андреевич Костригин

Creative Commons License

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

Abstract

The article analyzes the Russian readers’ attitude to medicine and to healthcare. The research is carried out on the data of public opinion polls on the problem. The reliability of the data is pointed out. Content analysis is suggested as a perspective method to examine the attitude to medicine and healthcare, on the basis of studying social networks’ texts and the users’ posts. Problems and potentialities of content analysis in this area are touched upon and discussed. The object of the research is to study the public’s attitude to medicine. The quantitative and the qualitative varieties of content analysis have been used to study social posts on medical issues in “VKontakte” and “Instagram” social networks. As a result, the authors have singled out various characteristics of the texts posted by the users, namely, the most frequently occurring words, “water” content, ”nausea” of the text, stop words and the core of the text. On the basis of the data obtained, the authors have drawn their conclusions concerning the users’ attitude to Russian medicine, i. e., what is the users idea of “good doctors” and “bad doctors”, of their attitude to commercial and free medicine, and of disinterested aid and money extortion in medical service. On the basis of the data obtained, the authors conclude that content analysis makes it possible to set new research and applied tasks in the area of studying public opinion on various issues, as well as to draw attention to problems that are insufficiently covered in social polling. To name but a few, they are the characteristics of “good” and “bad” medicine and the ideal doctor, money extortion, the public’s needs, etc.

Keywords

content analysis, social networks, public opinion, medicine, doctor, commercial medicine, free medicine, attitude to medicine, healthcare

References

  1. Achkasov, E. E., Shurupova, R. V., Kurshev, V. V. (2015). Formirovanye pozitivnogo imidzha vracha v protsesse professional’nogo obrazovaniya (po materialam kontent-analiza SMI) Formation of Positive Image of the Doctor in the Course of Professional Education (on Materials of the Content Analysis of Mass Media)]. Sotsiologiya obrazovaniya [Sociology of Education], 6, 79–96.
  2. Bollen, J., Mao, H., & Zeng, X. (2011). Twitter Mood Predicts the Stock Market. Journal of computational science, 2 (1), 1–8. DOI: 10.1016/j.jocs.2010.12.007
  3. Chizhik, A. V. (2016). Faktory formirovaniya sotsial’nogo nastroeniya na osnove analiza emotsional’noi okraski postov v russkoyazychnom Twitter [Factors of Social Mood Formation Revealed through the Analysis of Emotional Coloring of Posts on the Russian-Language Twitter]. Novye informatsionnye tekhnologii v avtomatizirovannykh sistemakh [New Information Technologies in Automation Systems], 19, 61–64.
  4. Gergen, K. J. (1985). The Social Constructionist Movement in modern Psychology. American Psychologist, 40 (3), 266–275. DOI: 10.1037/0003-066X.40.3.266
  5. Grigor’eva, S. V., Dmitrieva, T. V. (2015). Sotsial’nye seti kak kanaly rasprostraneniya nedostovernoi informatsii, formiruyushchie obshchestvennoe mnenie [Social Networks as Channels which Disseminate Unreliable Information and Shape Public Opinion]. In E. A. Il’in (Eds.) Informatsionnoe prostranstvo regiona: istoriya, sovremennost’ i aktual’nye problemy: sbornik nauchnykh statei [Information Space of the Region: History, the Present and Focal Problems] (46–51). Cheboksary: Chuvashskii gosudarstvennyi pedagogicheskii universitet im. I. Ya. Yakovleva.
  6. Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. New York, NY: Springer.
  7. Khraban, T. E. (2017). Diskursivnyi analiz rasprostraneniya lozhnoi informatsii v sotsial’nykh setyakh [The Discourse Analysis of Unreliable Information Dissemination in Social Networks]. Uchenye zapiski UO VGU im. P. M. Masherova [Bulletin of Vitebsk State University named after P. M. Masherov], 24, 127–132.
  8. Kuz’min, K. V., Semyonova (Pavlenko), E. V., Petrova, L. E., Zakroeva, A. G. (2016). Kommunikatsiya vracha i patsienta: proshloe, nastoyashchee, budushchee (istoricheskii i mediko-sotsiologicheskii analiz) [Doctor-Patient Communication: the Past, the Present and the Future (Historical and Medico-sociological Analysis)]. Ekaterinburg: “Yuzhno-Ural’skii gosudarstvennyi meditsinskii universitet”.
  9. Ledovaya, Ya. A., Panicheva, P. V., Prichislenko, A. G., Butakov, N. A. (2017). Nauchnaya sostavlyayushchaya tekstov po psikhologii, publikuyushchikhsya v sotsial’noi seti “Vkontakte” [A Scientific Component of Psychology Texts Published in the Social Network “VKontakte”]. Voprosy psikhologii [Issues of Psychology], 6, 79–91.
  10. Litovka, V. A. (2013). Kontent-analiz reklamnykh fotografii klinik reproduktivnoi meditsiny [Content-Analysis of Advertisement Photos of Reproductive Medicine Clinics]. Teoriya i praktika obshchestvennogo razvitiya [Theory and Practice of Public Development], 10, 136–138.
  11. Nikitin, P. V., Muradyants, A. A., Shostak, N. A. (2015). Mobil’noe zdravookhranenie: vozmozhnosti, problemy, perspektivy [Mobile Healthcare: Possibilities, Problems, Prospects]. Klinitsist [The Clinicist], 9 (4), 13–21.
  12. Pang, B., & Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval, 2 (1–2), 1–135. DOI: 10.1561/1500000011
  13. Panova, E. L., Tutorskaya, M. S. (2018). Sotsial’nye seti i organizatsiya vneauditornogo obucheniya studentov v sisteme vysshego meditsinskogo obrazovaniya [Social Networks and the Organization of Out-of-class Teaching in the System of Higher Education (Medicine)]. Problemy sotsial’noi gigieny, zdravookhraneniya i istorii meditsiny [Problems of Social Hygiene, Healthcare and History of Medicine], 26 (1), 48–52.
  14. Pennebaker, J. W., Boyd, R. L., Jordan, K., & Blackburn, K. (2007). The Development and Psychometric Properties of LIWC2007. LIWC2007, 1–22.
  15. Polynskaya, G. A., Mesropyan, M. G. (2018). Vyyavlenie modelei i trendov povedeniya patsientov pri ispol’zovanii elektronnykh prilozhenii i Internet-resursov dlya samodiagnostiki [Identification of Models and Trends of Patients’ Behavior in Self-Diagnostics with the Help of Electronic Applications and Internet Resources]. Biznes-informatika [Business Informatics], 1 (43), 28–38.
  16. Russian Public Opinion Research Center. (2017). Vrach v Rossii: doverie patsientov, dokhody, polozhenie v obshchestve [A Doctor in Russia: The Patients’ Confidence, Incomes, Status]. Retrieved from https://wciom.ru/index.php?id=236&uid=3590
  17. Russian Public Opinion Research Center. (2018). Kazhdomu vozrastu — svoi sotsseti [An Individual Social Network to Each Age Group]. Retrieved from https://wciom.ru/index.php?id=236&uid=116691
  18. Savel’eva, Zh. V. (2011). Potreblenie meditsinskikh uslug ili okazanie meditsinskoi pomoshchi: konstruirovanie obrazov platnoi i besplatnoi meditsiny sredstvami massovoi kommunikatsii [Consumption of Medical Services or Medical Care: Constructing Images of Paid and Free Medicine in the Media]. Zhurnal sotsiologii i sotsial’noi antropologii [Journal of Sociology and Social Anthropology], 14 (5), 347–355.
  19. Semenova, O. A. (2016). Regional’nye SMI o problemakh zdravookhraneniya i putyakh ikh resheniya [Regional Mass Media on Healthcare Problems and Their Solutions]. In O. I. Lepilkina, A. M. Gorbachev (Eds.) Mediachteniya SKFU: sbornik nauchnykh statei Vserossiiskogo nauchnogo seminara [Media Readings of the North-Caucasian Federal University: Collected Articles of the All-Russian Scientific Seminar] (169–174). Stavropol’: Severo-Kavkazskii federal’nyi universitet.
  20. Vershinin, E. G., Kovaleva, M. D., Khvastunova, E. P. (2015). Kakie novye sotsial’nye problemy meditsiny interesuyut otechestvennykh issledovatelei? [What New Social Problems of Medicine are Interested for Russian Researchers?]. Mezhdunarodnyi zhurnal eksperimental’nogo obrazovaniya [International Journal of Experimental Education], 8–1, 14–16.