| Vol-4056 urn:nbn:de:0074-4056-X Copyright © 2025 for the individual papers by the papers' authors. Copyright © 2025 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# INRA 2025
News Recommendation and Analytics 2025

### Proceedings of the 13th International Workshop on News Recommendation and Analytics
co-located with the 2025 ACM Conference on Recommender Systems (RecSys 2025)

### Prague, Czech Republic, September 26, 2025.

Edited by

### Andreea Iana1
Célina Treuillier2
Vandana Yadav3
Benjamin Kille3
Andreas Lommatzsch 4
Özlem Özgöbek3

1 University of Mannheim, Data and Web Science Group, 68159 Mannheim, Germany
2 University of Fribourg, Human-IST Institute, 1700 Fribourg, Switzerland
3 Norwegian University of Science and Technology, Department of Computer Science, 7034 Trondheim, Norway
4 Berlin Institute of Technology, DAI Lab, 10587 Berlin, Germany

## Table of Contents

- Preface
  Summary: There were 17 papers submitted for peer-review to this workshop. Out of these, 10 papers were accepted for this volume, 5 as regular papers and 5 as short papers.

- More of the Same? A Longitudinal Evaluation of Two Similarity-based Approaches in a News Recommender System
  Gloria Anne Babile Kasangu, Alain D. Starke Christoph Trattner
- News, With a Twist: Using Contrastive Learning to Improve User Embeddings for Diverse News Recommendations
  Zijie Tang, Manel Slokom
- Leveraging Media Frames to Improve Normative Diversity in News Recommendations
  Sourabh Dattawad, Agnese Daffara, Tanise Ceron
- Using Large Language Models to ‘Lighten the Mood’: Satirically Reframing News Recommendations to Reduce News Avoidance
  Tobias Jovall Wessel, Christoph Trattner, Alain D. Starke
- Hope, Fear, or Anger? How Emotional Framing in a News Recommender System Guides User Preferences
  Jørgen Eknes-Riple, Jia-Hua Jeng, Alain D. Starke Khadiga Seddik, Christoph Trattner
- Segment-Aware Analytics for Real-Time Editorial Support in Media Groups
  Martin Spišák, Rodrigo Alves, Thomas Kelleher Jason Sheppard, Ondřej Fiedler Ergys Kosovrasti, Vojtěch Vančura Petr Kasalický, Pavel Kordík
- News Recommendation with Category Description by a Large Language Model
  Yuki Yada, Hayato Yaman
- Clickbait Mitigation in Industrial Recommender System
  Václav Blahut, Karel Koupil Michal Chudoba, Radek Tomšů
- Evaluating Image Trust Labels in a News Recommender System
  Svenja Lys Forstner, Yelyzaveta Lysova Alain Starke, Christoph Trattner
- Towards Multi-Aspect Diversification of News Recommendations Using Neuro-Symbolic AI for Individual and Societal Benefit
  Markus Reiter-Haas, Elisabeth Lex

2025-09-22: submitted by Célina Treuillier, metadata incl. bibliographic data published under Creative Commons CC0
2025-10-06: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|