Literature Database Entry
finarelli2025balancing
Laura Finarelli, Johan Rochel, Florian Evéquoz and Gianluca A. Rizzo, "Balancing Personalization and Public Values: Legitimacy and Design of Algorithmic News Recommendations in Public Service Media," Proceedings of 11th EAI International Conference on Smart Objects and Technologies for Social Good (Goodtechs 2025), Rạch Giá, Vietnam, December 2025.
Abstract
This paper addresses the normative challenges of algorithmic recommendation systems in public service media (PSM), proposing a framework that aligns democratic mandates with digital engagement via user needs categorization. Institutions like Radio France and the BBC use algorithms to counter news avoidance and filter bubbles through civically weighted content and discoverability features. Yet, their non-commercial missions create tensions between user autonomy, transparency, and societal value. The study introduces a paradigm shift: modeling user behavior through why-oriented needs (e.g., civic awareness, informational gaps) rather than how-focused engagement metrics. A 2023 case study with Switzerland’s RTS develops three nudging scenarios using community detection and needs-based clustering. These inform a tripartite legitimacy framework: 1) alignment with public service duties, 2) ethical user guidance, and 3) systemic risk mitigation via participatory design. Findings show that needs-aware systems require multidimensional profiling balancing explorability and explainability, distinct from commercial logic. Bridging data science and nudging ethics, this work advances interdisciplinary strategies for operationalizing PSM’s dual mandate: respecting individual agency while fostering democratic citizenship.
Quick access
Contact
Laura Finarelli
Johan Rochel
Florian Evéquoz
Gianluca A. Rizzo
BibTeX reference
@inproceedings{finarelli2025balancing,
author = {Finarelli, Laura and Rochel, Johan and Ev{\'{e}}quoz, Florian and Rizzo, Gianluca A.},
title = {{Balancing Personalization and Public Values: Legitimacy and Design of Algorithmic News Recommendations in Public Service Media}},
publisher = {EAI},
address = {Rạch Gi{\'{a}}, Vietnam},
booktitle = {11th EAI International Conference on Smart Objects and Technologies for Social Good (Goodtechs 2025)},
month = {12},
year = {2025},
}
Copyright notice
Links to final or draft versions of papers are presented here to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or distributed for commercial purposes without the explicit permission of the copyright holder.
The following applies to all papers listed above that have IEEE copyrights: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
The following applies to all papers listed above that are in submission to IEEE conference/workshop proceedings or journals: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.
The following applies to all papers listed above that have ACM copyrights: ACM COPYRIGHT NOTICE. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept., ACM, Inc., fax +1 (212) 869-0481, or permissions@acm.org.
The following applies to all SpringerLink papers listed above that have Springer Science+Business Media copyrights: The original publication is available at www.springerlink.com.
This page was automatically generated using BibDB and bib2web.





