INRA 2023: 11th International Workshop on News Recommendation and Analytics in Conjunction with ACM RecSys 2023
Daily news consumption has crucial importance where it affects personal beliefs, decision making, political voting and world views in general. The news ecosystem has experienced drastic changes over the last decade. News consumption has shifted online and increasingly towards social media. On digital platforms such as news portals and social media, where personalization has more importance, the news is filtered and ranked even without users’ awareness. Therefore, we encounter challenges such as lack of transparency, diversity, and other ethical considerations while trying to generate the most suitable personalized recommendations for the users. In addition, the emergence of powerful Large Language Models presents a challenge for news organisation and consumers alike.
The 11th International Workshop on News Recommendation and Analytics (INRA 2023 in conjunction with ACM RecSys 2023) invites scholars from diverse disciplines to discuss topics related to news recommendation, including but not limited to technical, societal, and ethical aspects.
This workshop invites contributions in the realm of news recommendation and analytics. In addition to technical papers, we welcome interdisciplinary submissions. In this year’s edition, we mainly focus on three themes: news personalization, news analytics, and the effect of Large Language Models (LLMs) on the news eco-system. Topics of interest for this workshop can be found here.
| Submission Deadline | |
| Author Notification | 27 August 2023 |
| Camera-ready Deadline | 10 September 2023 |
| Workshop Date | tbd |
All submissions should be made through the EasyChair Conference System and must be written in English and formatted according to the latest ACM SIG proceedings template with a single column. All submissions will be peer reviewed (single-blind) by the program committee based on the quality of the work and its fit to the workshop themes. Please note that at least one of the authors of each accepted paper must register for the workshop and present the paper.
The details of submission types can be found here .
INRA is organized by:
Benjamin Kille, PostDoc, NorwAI, NTNU
Andreas Lommatzsch, PostDoc, DAI Lab, TU Berlin
Özlem Özgöbek, Associate Professor, NTNU
Peng Liu, PostDoc, NorwAI, NTNU
Lemei Zhang, PostDoc, NorwAI, NTNU
Simen Eide, Schibsted
We invite researchers and practitioners to contribute high-quality articles focusing on efficient user modeling and advanced machine learning techniques in various aspects of news personalization and analytics.
The overall goal of this task is to better understand the relationship the textual content of the articles (including text body, and headlines) and to understand the impact of these elements on readers’ interest in the news (measured by the number of views).
The work presented here highlights the diversity of research performed across the entire breadth of Recommender Systems research and presents advances in theory, experiment, and methodology with applications to compelling problems.