Submission Instructions

Submissions of research papers must be in English, in PDF format, written in the latest ACM SIG proceedings template with the double-column format. All submissions must present original and unpublished work, i.e., the research should not have been previously published or concurrently submitted to another venue. All submissions will be peer reviewed by the program committee based on the quality of the work, its fit to the workshop themes, and its potential to convey interesting ideas and stimulate engaging discussions.

Submission should be submitted electronically through EasyChair: link to be provided for the workshop.

At least one author of each accepted paper is required to register for the workshop and present the paper in person.

Accepted papers will be published in CEUR-WS proceedings.

Submission Types

Scientific Papers (Long and short papers): We will accept scientific contributions in the form of long and short papers. Long papers must be 8 pages (including figures, tables, proofs, appendixes, acknowledgments, and any content except references) with 2 additional pages for references. Short papers must not exceed 4 pages (including figures, tables, proofs, appendixes, acknowledgments, and any content except references) with 2 additional pages for references.

Demo Papers: We accept papers demonstrating technical advances in news personalization and analytics. Demo papers must not exceed 4 pages, with 2 additional pages for references.

Idea Papers: We accept papers introducing new ideas that can foster discussions. Idea papers must not exceed 4 pages, with 2 additional pages for references.

We encourage authors to release any code and/or datasets associated with their paper, although it is not required.

Anonymity Policy

• The review process for long, short, and idea papers is double-blind. Authors are required to prepare their submissions in an anonymous format to facilitate the double-blind review process.
• The review process for demo papers is single-blind, hence authors can list their names and affiliations. Since anonymizing external resources such as code and datasets can be challenging, authors are not required to anonymise these materials for demo papers. If a resource is provided, a link to the resource must be provided in the submission and available to anyone.