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An econometric model for popularrity on media

Yıl 2021, Cilt: 42 Sayı: 4, 934 - 941, 29.12.2021

Öz

This paper aims to determine and estimate an econometric model which can be used to forecast media popularity of a governmental organization. Number of media sources monitored was used as regressors while taking types of these sources into account. Some linear models were estimated besides some non-linear models. According to the results, number of national, local, regional newspapers and number of television channels monitored were not found important to estimate number of news caught through media monitoring. On the other hand, number of internet media sources was found important to estimate the dependent variable. Additionally, number of news caught on select subjects in previous year was also found important. In the end an autoregressive panel data model with some additional regressors such as number of monitored sources was suggested to forecast popularity of organization. Any data only accessible to TurkStat members was never used in this paper. TurkStat is not responsible for any inference made in this study.

Kaynakça

  • [1] Craufurd Smith R., Monitoring media pluralism in the digital era: application of the Media Pluralism Monitor 2020 in the European Union, Albania and Turkey in the years 2018-2019. Country report: United Kingdom , (2020).
  • [2] Mukhamediev R. I., Yakunin K., Mussabayev R., Buldybayev T., Kuchin Y., Murzakhmetov S., Yelis M. (2020). Classification of Negative Information on Socially Significant Topics in Mass Media, Symmetry, 12(12) (2020) 1945.
  • [3] Sánchez-Núñez P., Yanez E. R., Cabrera F. E., Peláez-Repiso A., Government Communication Management in Digital Ecosystems: A Real Case of Country Brand Analysis, In 2020 Seventh International Conference on eDemocracy & eGovernment (ICEDEG) (pp. 264-268) (2020, April) IEEE.
  • [4] Hsiao C., Panel data analysis, (2003).
  • [5] Arellano M., Panel data econometrics. Oxford university press, (2003).
  • [6] Baltagi B., Econometric analysis of panel data. John Wiley & Sons, (2008).
  • [7] Frees E. W., Longitudinal and panel data: analysis and applications in the social sciences. Cambridge University Press, (2004).
  • [8] Hsiao C., Why panel data?. The Singapore Economic Review, 50(02) (2005) 143-154.
  • [9] Hsiao C. Analysis of panel data (No. 54). Cambridge university press, (2014)..
  • [10] Wooldridge J. M., Econometric analysis of cross section and panel data. MIT press, (2010).
  • [11] Regusci E., A Content Analysis of News Coverage about Plant-Based Milk, master thesis, Faculty of Texas Tech University, (2020).
  • [12] Chouliaraki L., Georgiou M., Zaborowski R., Oomen W. A., The European ‘migration crisis’ and the media: a cross-European press content analysis, (2017).
  • [13] Trattner C., Moesslang D., Elsweiler D.,. On the predictability of the popularity of online recipes. EPJ Data Science, 7(1) (2018) 1-39.
Yıl 2021, Cilt: 42 Sayı: 4, 934 - 941, 29.12.2021

Öz

Kaynakça

  • [1] Craufurd Smith R., Monitoring media pluralism in the digital era: application of the Media Pluralism Monitor 2020 in the European Union, Albania and Turkey in the years 2018-2019. Country report: United Kingdom , (2020).
  • [2] Mukhamediev R. I., Yakunin K., Mussabayev R., Buldybayev T., Kuchin Y., Murzakhmetov S., Yelis M. (2020). Classification of Negative Information on Socially Significant Topics in Mass Media, Symmetry, 12(12) (2020) 1945.
  • [3] Sánchez-Núñez P., Yanez E. R., Cabrera F. E., Peláez-Repiso A., Government Communication Management in Digital Ecosystems: A Real Case of Country Brand Analysis, In 2020 Seventh International Conference on eDemocracy & eGovernment (ICEDEG) (pp. 264-268) (2020, April) IEEE.
  • [4] Hsiao C., Panel data analysis, (2003).
  • [5] Arellano M., Panel data econometrics. Oxford university press, (2003).
  • [6] Baltagi B., Econometric analysis of panel data. John Wiley & Sons, (2008).
  • [7] Frees E. W., Longitudinal and panel data: analysis and applications in the social sciences. Cambridge University Press, (2004).
  • [8] Hsiao C., Why panel data?. The Singapore Economic Review, 50(02) (2005) 143-154.
  • [9] Hsiao C. Analysis of panel data (No. 54). Cambridge university press, (2014)..
  • [10] Wooldridge J. M., Econometric analysis of cross section and panel data. MIT press, (2010).
  • [11] Regusci E., A Content Analysis of News Coverage about Plant-Based Milk, master thesis, Faculty of Texas Tech University, (2020).
  • [12] Chouliaraki L., Georgiou M., Zaborowski R., Oomen W. A., The European ‘migration crisis’ and the media: a cross-European press content analysis, (2017).
  • [13] Trattner C., Moesslang D., Elsweiler D.,. On the predictability of the popularity of online recipes. EPJ Data Science, 7(1) (2018) 1-39.
Toplam 13 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İstatistik
Bölüm Natural Sciences
Yazarlar

Orçun Aydın 0000-0001-9454-0259

Erol Terzi 0000-0002-2309-827X

Yayımlanma Tarihi 29 Aralık 2021
Gönderilme Tarihi 26 Temmuz 2021
Kabul Tarihi 21 Kasım 2021
Yayımlandığı Sayı Yıl 2021Cilt: 42 Sayı: 4

Kaynak Göster

APA Aydın, O., & Terzi, E. (2021). An econometric model for popularrity on media. Cumhuriyet Science Journal, 42(4), 934-941.