“News Desertification” in Europe: Highlighting Correlations for Future Research
Abstract
:1. Introduction
2. Background
Analysis of the LM4D Report Indicators
3. Theoretical Framework
3.1. The Relationship between PSM and News Deserts
3.2. The Relationship between Social Media Usage and News Desertification
3.3. The Relationship between News Deserts and Disinformation
3.4. Hypotheses
- H1: There is a correlation between the quality of Public Service Media (PSM) and the risk of news desertification within a specific country.
- H2: There is a correlation between the prevalence of social media usage in a given country and the risk of news desertification.
- H3: The disinformation risk in a given country is correlated with the risk of news desertification.
4. Methodology and Research Design
5. Results and Discussion
5.1. PSM Quality and News Desertification
5.2. Social Media Usage and News Desertification
5.3. Disinformation and News Desertification
6. Limitations
7. Future Research
8. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
1 | Pearson’s correlation coefficient measures the direction and strength of linear relationship between two variables, which is represented by the r-value which ranges from −1 to 1. A number close to 1 or −1 indicates a strong positive or negative correlation and a number close to 0 indicates a weak correlation. The p-value indicates the statistical significance of the correlation coefficient. In more technical terms, the p-value is the probability of obtaining a test statistic at least as extreme as the one observed, if the null hypothesis (i.e., no correlation) is true. The commonly accepted threshold for statistical significance is 0.05. A linear model operates under the assumption that the relationship between variables is linear and data is normally distributed. It is important to acknowledge that the model’s sensitivity to outliers can significantly impact the results, so we should exercise caution when interpreting the results. |
2 | Media Pluralism Monitor 2023-CMPF (https://www.eui.eu/en/home, accessed on 27 May 2024). |
3 | DataReportal–Global Digital Insights. |
4 | These are sub-indicators of the 2023 Media Pluralism Monitor. For more information, please refer to this link: https://cmpf.eui.eu/wp-content/uploads/2023/07/questionnaire-MPM-2023.pdf (accessed on 27 May 2024). |
5 | CMPF-Variables-2023 (https://www.eui.eu/en/home, accessed on 27 May 2024). |
6 | https://cmpf.eui.eu/wp-content/uploads/2023/06/questionnaire-final-05.6.23.pdf (accessed on accessed on 27 May 2024). |
7 | Transparency International. (2024). 2023 Corruption Perceptions Index. Transparency.org. https://www.transparency.org/en/cpi/2023/ (accessed on 27 May 2024). |
8 | Reporters without Borders. (2023). Index|RSF. Rsf.org. https://rsf.org/en/index (accessed on 27 May 2024). |
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Kermer, J.; Reviglio, U.; Blagojev, T. “News Desertification” in Europe: Highlighting Correlations for Future Research. Journal. Media 2024, 5, 718-738. https://doi.org/10.3390/journalmedia5020047
Kermer J, Reviglio U, Blagojev T. “News Desertification” in Europe: Highlighting Correlations for Future Research. Journalism and Media. 2024; 5(2):718-738. https://doi.org/10.3390/journalmedia5020047
Chicago/Turabian StyleKermer, Jan, Urbano Reviglio, and Tijana Blagojev. 2024. "“News Desertification” in Europe: Highlighting Correlations for Future Research" Journalism and Media 5, no. 2: 718-738. https://doi.org/10.3390/journalmedia5020047
APA StyleKermer, J., Reviglio, U., & Blagojev, T. (2024). “News Desertification” in Europe: Highlighting Correlations for Future Research. Journalism and Media, 5(2), 718-738. https://doi.org/10.3390/journalmedia5020047