CfP - Seventh Workshop on Fairness in User Modeling, Adaptation, and Personalization (FairUMAP 2025) @ ACM UMAP 2025
Styliani Kleanthous
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CALL FOR PAPERS
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Seventh Workshop on Fairness in User Modeling, Adaptation, and Personalization (FairUMAP 2025)
At the ACM Conference on User Modeling, Adaptation, and Personalization (UMAP 2025)
June 16 — 19, 2025, New York, USA
Workshop website: https://fairumap.wordpress.com/
Conference website: https://www.um.org/umap2025/
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WORKSHOP DESCRIPTION
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Personalization has become a ubiquitous and essential part of systems that help users find relevant information in today’s highly complex information-rich online environments. Machine
learning, recommender systems, and user modeling are key enabling technologies that allow intelligent systems to learn from users and adapt their output to users’ needs and preferences. However, there has been a growing recognition that these underlying technologies raise novel ethical, policy, and legal challenges. It has become apparent that a single-minded focus on the users’ preferences has obscured other important and beneficial outcomes, such systems must be able to deliver. System properties such as fairness, transparency, balance, openness to diversity, and other social welfare considerations are not captured by typical metrics based on which data-driven personalized models are optimized. Widely used personalization systems in such popular sites, like Facebook, Google News, and YouTube, have been heavily criticized for personalizing information delivery too heavily at the cost of these other objectives. Bias and fairness in machine learning are topics of considerable recent research interest. However, more work is needed to expand and extend this work into algorithmic and modeling approaches where personalization is of primary importance.
The Workshop on Fairness in User Modeling, Adaptation, and Personalization 2025 aims to bring together experts from academia and industry to discuss ethical, social, and legal concerns related to personalization and user modeling to explore a variety of mechanisms and modeling approaches that help mitigate bias and achieve fairness in personalized systems.
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TOPICS OF INTEREST
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Topics of interest include, but are not limited to the following.
Bias and discrimination in user modeling, personalization and recommendation
Computational techniques and algorithms for fairness aware personalization
Definitions, metrics and criteria for optimizing and evaluating fairness-related aspects of personalized systems
Data preprocessing and transformation methods to address bias in training data
User modeling approaches that take fairness and bias into account
User studies to evaluate the impact of personalization on fairness, balance, diversity, and other social welfare criteria
Balancing needs of multiple stakeholders in recommender systems and other personalized systems
“Filter bubble” or “balkanization” effects of personalization
Transparent and accurate explanations for recommendations and other personalization outcomes
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IMPORTANT DATES
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Submission deadline: April 14, 2025
Notification of acceptance: April 28, 2025
Camera-ready due: May 5, 2025 (Mandatory for inclusion in UMAP Adjunct Proceedings)
All deadlines are 11:59 pm, AoE time (Anywhere on Earth)
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PAPER SUBMISSION
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Research papers reporting original results as well as position papers proposing novel and ground-breaking ideas pertaining to the workshop topics are solicited.
Manuscripts must be in English. Workshop papers till 6 pages (excluding references) will be considered as short papers, while workshop papers between 8 and 14 pages (excluding references) will be considered as full papers.
Papers must be formatted as a single-column manuscript according to the new workflow for ACM publications. The templates and instructions are available here: https://www.acm.org/publications/taps/word-template-workflow.
Available templates include:
Following the ACM Publication Workflow, all authors should submit manuscripts for review in the ACM double-column format. Instructions for authors are given below:
LaTeX: Please use the latest version of the Primary Article Template – LaTeX to create your submission. Start the document with the \documentclass[sigconf,review,anonymous]{acmart} command to generate the output in a double-column format. Please see the LaTeX documentation and ACM’s LaTeX best practices guide for further instructions, ignoring the single-column instructions. Do not use the “manuscript” option, otherwise, the document will not be compiled in double-column, as required. Check the sample-sigconf.tex file included in the template package for a formatting example. To ensure 100% compatibility with The ACM Publishing System (TAPS), please restrict the use of packages to the whitelist of approved LaTeX packages.
Overleaf: (use \documentclass[sigconf,review,anonymous]{acmart} for double-column). Please carefully follow the ACM’s instructions for preparing your article with Overleaf.
Word: Please carefully follow the ACM’s instructions for preparing your article with Microsoft Word, ignoring the single-column instructions and the single-column submission template. Please use the double-column Word template.
Papers will be submitted through EasyChair https://easychair.org/conferences/?conf=umap2025
by selecting the track: FairUMAP - 7th UMAP Workshop on Fairness in User Modeling, Adaptation, and Personalization.
Accepted papers will be presented at the workshop and included in the Adjunct proceedings of the conference.
At least one author of each accepted paper must attend the workshop and present the paper.
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WORKSHOP Organizing Committee
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Bamshad Mobasher, DePaul University, USA
Styliani Kleanthous, Open University of Cyprus, Cyprus
Robin Burke, University of Colorado, Boulder, USA
Tsvi Kuflik, University of Haifa, Israel
Avital Shulner-Tal, Braude College of Engineering, Karmiel, Israel