METHODS OF ANALYTICS OF BIG DATA OF POPULAR ELECTRONIC NEWSPAPERS ON FACEBOOK

I. Mysiuk, R. Mysiuk, R. Shuvar, V. Yuzevych

Abstract


Due to the popularity of social networks, all famous brands use them to promote and support their product. For example, well-known foreign newspapers such as: Washington Post, New York Times, Time, Reuters, Forbes duplicate information about news on the Facebook social network for greater readership. Using methods of automated data collection from web pages, a list of posts is formed based on which data analysis is performed. Statistical results of frequency, popularity of certain articles, audience reach and people's reaction to posts are obtained from a large volume of data. In the Java programming language and using additional Selenium, JavaFX libraries, all processes for data normalization is developed and data visualization is used. In addition, the dependence of the post coverage of newspaper editions on the number of posts published during the day is investigated in Facebook social network. The work also examines the most popular posts and their topics. The relationship between keywords and real events is analyzed.

Keywords: big data, social networks, data analytics, automated data collection, data processing.


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References


  1. Popenoe R., Langius-Eklöf A., Stenwall E., Jervaeus A. A practical guide to data analysis in general literature reviews // Nordic Journal of Nursing Research. 2021. Vol. 41, No 4: P. 175-186. doi: https://doi.org/10.1177/2057158521991949
  2. Domingue J., Lasierra N., Fensel A., van Kasteren T., Strohbach M., Thalhammer A. // Big Data Analysis. In: Cavanillas, J., Curry, E., Wahlster, W. (eds) New Horizons for a Data-Driven Economy. Springer, Cham. 2016. doi: https://doi.org/10.1007/978-3-319-21569-3_5.
  3. New York Times [Online]. URL: https://www.facebook.com/nytimes/
  4. Reuters [Online]. URL: https://www.facebook.com/Reuters/
  5. Washington Post [Online]. URL: https://www.facebook.com/washingtonpost/
  6. Forbes [Online]. URL: https://www.facebook.com/forbes/
  7. Selenium automates browsers. [Online]. URL: https://www.selenium.dev/
  8. JavaFX. [Online]. URL: https://openjfx.io/
  9. Crews B., Drees J., Greene D. Data-driven quality assurance to prevent erroneous test results // Critical Reviews in Clinical Laboratory Sciences, 2020. Vol. 57. No 3, P. 146-160, DOI: https://doi.org/10.1080/10408363.2019.1678567
  10. Singh D., Singh B. Investigating the impact of data normalization on classification performance // Applied Soft Computing, Volume 97, Part B, 2020, 105524, ISSN 1568-4946, doi: https://doi.org/10.1016/j.asoc.2019.105524.
  11. Mysiuk R., Yuzevych V., Mysiuk I. Api test automation of search functionality with artificial intelligence // Stuc. intelekt. 2022. Vol. 27, No 1. P. 269-274 doi: https://doi.org/10.15407/jai2022.01.269
  12. Hızal, A. Frequency domain data merging in operational modal analysis based on least squares approach // Measurement, 2021. Vol. 170, 108742. https://doi.org/10.1016/j.measurement.2020.108742
  13. Marino C, Gini G, Vieno A, Spada M. A comprehensive meta-analysis on Problematic Facebook Use // Computers in Human Behavior, 2018. Vol. 83, P. 262-277, ISSN 0747-5632, https://doi.org/10.1016/j.chb.2018.02.009.
  14. Ostic Dragana, Qalati Sikandar Ali, Barbosa Belem, Shah Syed Mir Muhammad, Galvan Vela Esthela, Herzallah Ahmed Muhammad, Liu Feng. Effects of Social Media Use on Psychological Well-Being: A Mediated Model // Frontiers in Psychology. 2021. Vol. 12. ISSN 1664-1078. doi: https://doi.org/10.3389/fpsyg.2021.678766
  15. Ji Changqing & Li Yu & Qiu Daowen & Jin Yingwei & Xu Yujie & Awada Uchechukwu & Li Keqiu & Qu Wenyu. Big data processing: Big challenges. Journal of Interconnection Networks. 2013. doi: https://doi.org/10.1142/S0219265912500090.




DOI: http://dx.doi.org/10.30970/eli.19.6

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