Emotions and reputation learning by audience networks: a research agenda in bureaucratic politics
Emotions and reputation learning by audience networks: a research agenda in bureaucratic politics
Audiences that observe and interact with government agencies play a crucial role in shaping these agencies' reputations. However, existing research often treats these audience networks as monolithic, overlooking the inherent diversity in their cognitive and emotional processing of reputational information. This approach fails to account for the variations in how audiences experience and evaluate agencies. To address this gap, we propose a new research agenda focused on the role of emotions in bureaucratic politics. We introduce a novel theoretical framework of Reputation Learning, informed by Affect-as-Information Theory and Affective Intelligence Theory, to explore the downstream effects of emotions as content and as process in shaping judgment formation and information processing. Specifically, we identify emotion-based components of bureaucratic reputation and examine how emotions influence audience decision-making processes and perceptions of government agencies. We conclude by outlining four key contributions of this framework to advancing the study of emotions in bureaucratic politics.
affect-as-information theory, affective intelligence theory, audience networks, emotions, government agencies, reputation learning
156-170
Maor, Moshe
350b6a8e-59a9-4035-a28c-e3997b7bd5e5
Rimkute, Dovile
05917869-d5a0-423d-bca0-8090ee946dac
Capelos, Tereza
bd3b5744-cbcc-44a4-9b73-b088d82154e7
19 January 2026
Maor, Moshe
350b6a8e-59a9-4035-a28c-e3997b7bd5e5
Rimkute, Dovile
05917869-d5a0-423d-bca0-8090ee946dac
Capelos, Tereza
bd3b5744-cbcc-44a4-9b73-b088d82154e7
Maor, Moshe, Rimkute, Dovile and Capelos, Tereza
(2026)
Emotions and reputation learning by audience networks: a research agenda in bureaucratic politics.
Public Administration Review, 86 (1), .
(doi:10.1111/puar.70004).
Abstract
Audiences that observe and interact with government agencies play a crucial role in shaping these agencies' reputations. However, existing research often treats these audience networks as monolithic, overlooking the inherent diversity in their cognitive and emotional processing of reputational information. This approach fails to account for the variations in how audiences experience and evaluate agencies. To address this gap, we propose a new research agenda focused on the role of emotions in bureaucratic politics. We introduce a novel theoretical framework of Reputation Learning, informed by Affect-as-Information Theory and Affective Intelligence Theory, to explore the downstream effects of emotions as content and as process in shaping judgment formation and information processing. Specifically, we identify emotion-based components of bureaucratic reputation and examine how emotions influence audience decision-making processes and perceptions of government agencies. We conclude by outlining four key contributions of this framework to advancing the study of emotions in bureaucratic politics.
Text
Public Administration Review - 2025 - Maor - Emotions and Reputation Learning by Audience Networks A Research Agenda in
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Accepted/In Press date: 23 June 2025
e-pub ahead of print date: 2 July 2025
Published date: 19 January 2026
Keywords:
affect-as-information theory, affective intelligence theory, audience networks, emotions, government agencies, reputation learning
Identifiers
Local EPrints ID: 509631
URI: http://eprints.soton.ac.uk/id/eprint/509631
ISSN: 0033-3352
PURE UUID: ff99c6b7-e54c-4142-b819-293c14165227
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Date deposited: 27 Feb 2026 17:37
Last modified: 07 Mar 2026 04:18
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Contributors
Author:
Moshe Maor
Author:
Dovile Rimkute
Author:
Tereza Capelos
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