An econometric model for popularrity on media

An econometric model for popularrity on media

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.

___

  • [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.
Cumhuriyet Science Journal-Cover
  • ISSN: 2587-2680
  • Yayın Aralığı: Yılda 4 Sayı
  • Başlangıç: 2002
  • Yayıncı: SİVAS CUMHURİYET ÜNİVERSİTESİ > FEN FAKÜLTESİ
Sayıdaki Diğer Makaleler

Forecasting the returns of pension investment funds in Turkey with artificial neural network

Fatih ÇEMREK, Özge DEMİR

Synthesis, characterization and biological activity evaluation of novel thiazole derivatives containing acetic acid residue as selective COX-1 inhibitors

Derya OSMANİYE, Begüm Nurpelin SAĞLIK

Analysing the spatial dynamics of earthquakes using event synchronization method: Anatolian Case

Ahmet ÇELİKOĞLU

Methylene blue adsorption capacity and coherent isotherm model of commercial activated carbon

İlhan KÜÇÜK

Investigation of joining properties of AA 5083 material in MIG and TIG weldings

Hatice VAROL ÖZKAVAK, Serdar MERCAN

Electrochemical investigation of DNA and Capecitabine interaction using glassy carbon electrode (GCE)

Derya KIZILOLUK, Gültekin GÖKÇE, Şenay ÇETİNUS

Identification and validation of key genes associated with smoking induced lung adenocarcinoma development through bioinformatics analysis and predictions of small-molecule drugs

Hamid CEYLAN

The effect of strontium carbonate additive on the production of graphitic boron nitride using modified O'connor method

Muhammed ÖZ

The therapeutic potential of targeting HDAC6 with Tubastatin A in TFK-1 and EGI-1 cholangiocarcinoma cells

Münevver YENİGÜL, Emel Başak GENCER AKÇOK

Synthesis, molecular docking, in silico ADME and antimicrobial activity studies of some new benzimidazole-triazole derivatives

Asaf Evrim EVREN, Ismail ÇELİK, Ulviye ACAR ÇEVİK