Beyond Formal Power : How Central Roles in Political Networks are Related to Media Visibility

Juho Vesa*, Arttu Malkamäki, Antti Gronow, Paul Wagner, Tuomas Ylä-Anttila

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

11 Lataukset (Pure)

Abstrakti

A recurring finding in communication studies is that political actors with formal-institutional power are highly visible in the media. The relationship between informal power and media visibility remains less understood. This study examines whether central roles in networks of political collaboration—as indicators of informal power—are associated with increased visibility in mainstream news media. We hypothesize that organizations with central roles are more visible in the media because informal power increases their newsworthiness. Using social network methods and Bayesian regressions on survey and media data on organizations involved in climate policy in Finland, we find that central organizations with many collaboration partners receive more media coverage. Other central roles, such as brokerage or coalition leadership, are not associated with media visibility. This study advances knowledge of media visibility by showing that informal power is associated with media visibility, and that some power positions are more important than others.

AlkuperäiskieliEnglanti
Artikkeli00936502251343986
JulkaisuCommunication Research
DOI - pysyväislinkit
TilaSähköinen julkaisu (e-pub) ennen painettua julkistusta - 19 kesäk. 2025
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Rahoitus

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work has been supported by the Research Council of Finland (projects no. 332916, 309934, 341137, and 352561) and the Kone Foundation (grants no. 201805496, 201804137, 202203761, and 201609129). We also thank Eva Gronow and Sonja Savolainen for their work on media data coding, Aasa Karimo for her work on the survey data, and Ted Chen for his work on the social media data. We also acknowledge the computational resources provided by the Aalto Science-IT project.

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