Understanding news outlets’ audience-targeting patterns

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Elejalde, E.; Ferres, L.; Schifanella, R.: Understanding news outlets’ audience-targeting patterns. In: EPJ Data Science 8 (2019), Nr. 1, S. 16. DOI: https://doi.org/10.1140/epjds/s13688-019-0194-8

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/5073

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Sum total of downloads: 285

The power of the press to shape the informational landscape of a population is unparalleled, even now in the era of democratic access to all information outlets. However, it is known that news outlets (particularly more traditional ones) tend to discriminate who they want to reach, and who to leave aside. In this work, we attempt to shed some light on the audience targeting patterns of newspapers, using the Chilean media ecosystem. First, we use the gravity model to analyze geography as a factor in explaining audience reachability. This shows that some newspapers are indeed driven by geographical factors (mostly local news outlets) but some others are not (national-distribution outlets). For those which are not, we use a regression model to study the influence of socioeconomic and political characteristics in news outlets adoption. We conclude that indeed larger, national-distribution news outlets target populations based on these factors, rather than on geography or immediacy.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2019
Appears in Collections:Forschungszentren

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Luxembourg Luxembourg 84 29.47%
2 image of flag of Germany Germany 60 21.05%
3 image of flag of United States United States 47 16.49%
4 image of flag of Vietnam Vietnam 43 15.09%
5 image of flag of United Kingdom United Kingdom 10 3.51%
6 image of flag of No geo information available No geo information available 7 2.46%
7 image of flag of China China 6 2.11%
8 image of flag of Russian Federation Russian Federation 3 1.05%
9 image of flag of Hong Kong Hong Kong 3 1.05%
10 image of flag of Afghanistan Afghanistan 2 0.70%
    other countries 20 7.02%

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