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Policy Studies Journal
Article . 2024 . Peer-reviewed
License: CC BY
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https://doi.org/10.31235/osf.i...
Article . 2023 . Peer-reviewed
License: CC BY
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Research.fi
Article . 2024 . Peer-reviewed
License: CC BY
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https://doi.org/10.4337/978103...
Part of book or chapter of book . 2025 . Peer-reviewed
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Policy influence and influencers online and off

Authors: Anniina Kotkaniemi; Tuomas Ylä-Anttila; Ted Hsuan Yun Chen;

Policy influence and influencers online and off

Abstract

Abstract Social media is an important arena for policy contestation. Although online social media debates can yield notable power over political processes offline, little research has examined the relationship between policy actors' influence in offline policymaking and social media policy arenas. We explore the relationship between four types of influence: reputational and formal‐institutional influence offline, and broadcasting and boosting influence online. We ask (1) are influential policy actors better able than others to broadcast their own messages on social media? and (2) are they better able than others to boost the broadcasting influence of other policy actors in social media? Using exponential random graph models on survey and Twitter data from the Finnish climate policy domain, we find that actors with high reputational influence in offline policymaking are also influential online, when measuring influence as the ability to broadcast one's own message. The pattern does not hold for those with formal‐institutional influence offline. Additionally, offline influence does not translate to the ability to further shape online influence by making boosting other actors' visibility. Our results suggest that although online influence partially corresponds to influence in policymaking, influence varies across arenas of policy contestation.

Countries
Finland, Finland
Related Organizations
Keywords

influence, Political Science, social media, policy network, Twitter, Public Policy, Public Affairs, Public Policy and Public Administration, Social and Behavioral Sciences, 5171 Political Science, exponential random graph model

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    2
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Green
hybrid