New Directions for News Recommender Systems: ACM TORS Special Issue (CfP)
Update 2026-03-08: The submission deadline is extended to April 17th, 2026.
News is more important than ever—and yet, if we’re honest, the state of the art in news recommendation is still… kind of disappointing. That’s exactly why ACM Transactions on Recommender Systems (ACM TORS) is running a Special Issue on New Directions for News Recommender Systems.
We’re incredibly good at optimizing clicks on fast-expiring content, but much less good at the things that actually matter in the news domain: balancing relevance with recency, novelty, diversity, and serendipity; coping with permanent cold-start; making sense of rich language and multimodal signals; and dealing with “invisible feedback” when a headline is read but never clicked. And that’s before we even touch the societal responsibilities: avoiding filter bubbles, reducing misinformation spread, and supporting an informed public while still respecting users’ niche interests and the public nature of news as shared experience.
We’re looking for work that moves beyond “just rank the feed” and tackles what makes news uniquely hard and uniquely consequential: GenAI for personalization (and its pitfalls), news recommendation on social media, multimodal signals, fake news mitigation, richer user modeling, context-aware recommendation, healthier interactions around news (without inviting the worst corners of the internet), and—crucially—evaluation and metrics, especially user and field studies.
And if you need a hint that this topic is having a “moment”: it might not be a coincidence that Joseph (Joe) Konstan—quite literally one of the fathers of recommender systems—is serving as a guest editor for the special issue, alongside Özlem Özgöbek and Edward Malthouse. When people like Joe invest their time here, it’s a signal: this problem matters, and it’s time to tackle it seriously.
ACM TORS welcomes technical research, industry papers, surveys, and opinion/perspective pieces. Journal extensions of top conference papers are also welcome (with at least 30% new content). Submissions go through Manuscript Central, and accepted papers will be published online as soon as they’re accepted.
If you’ve been sitting on a bold idea, a hard-earned dataset, a careful field study, or a metrics paper that finally treats news recommendation like the multi-objective, high-stakes problem it is: now’s the time.
Important dates:
- Submission deadline:
March 15, 2026April 17, 2026 - Author notifications: June 15, 2026
- Revisions due: August 15, 2026
- Final notification: October 15, 2026
Call for Papers (PDF): https://dl.acm.org/pb-assets/static_journal_pages/tors/pdf/ACM-TORS-CfP-New-Directions-News-Recommender-Systems-1764960204737.pdf
The “ACM Transactions on Recommender Systems” (ACM TORS) is revealed during the ACM RecSys Conference 2021
ACM TORS Call for Papers: Special Issue on Recommender Systems for Good
ACM TORS August/September ’25 Roundup
About The Author
Joeran Beel
I am the founder of Recommender-Systems.com and head of the Intelligent Systems Group (ISG) at the University of Siegen, Germany https://isg.beel.org. We conduct research in recommender-systems (RecSys), personalization and information retrieval (IR) as well as on automated machine learning (AutoML), meta-learning and algorithm selection. Domains we are particularly interested in include smart places, eHealth, manufacturing (industry 4.0), mobility, visual computing, and digital libraries. We founded or maintain, among others, LensKit-Auto, Darwin & Goliath, Mr. DLib, and Docear, each with thousand of users; we contributed to TensorFlow, JabRef and others; and we developed the first prototypes of automated recommender systems (AutoSurprise and Auto-CaseRec) and Federated Meta Learning (FMLearn Server and Client).