Workshop Aims and Scope
The goal is hence to favor a community-wide dialogue on new research perspectives through a workshop having the following objectives:
- Increase awareness of the algorithmic bias problem in IR.
- Identify dimensions influenced by algorithmic bias in IR.
- Solicit contributions addressing algorithmic bias in IR.
- Gain insights into recent advances and open issues in IR.
- Familiarize the IR community with current field practices.
- Uncover gaps in academic and industry research in IR.
Workshop Topics
The workshop welcomes contributions on topics about algorithmic bias in search and recommendation, focused (but not limited) to:
- Data Set Collection and Preparation:
- Studying the interplay between bias and imbalanced data.
- Designing methods for dealing with imbalances in data.
- Creating data pipelines for less biased data sets.
- Collecting data sets for the analysis of biased situations.
- Designing protocols for data sets tailored to bias analysis.
- Countermeasure Design and Development:
- Formalizing and operationalizing bias concepts.
- Conducting exploratory analysis that uncover bias.
- Designing treatments that mitigate biases.
- Devising methods for explaining biases.
- Studying causal and counterfactual reasoning for bias.
- Evaluation Protocol and Metric Formulation:
- Performing auditing studies with respect to bias.
- Conducting experimental studies on bias.
- Defining objective metrics that consider bias.
- Formulating bias-aware protocols to evaluate models.
- Evaluating mitigation strategies in unexplored domains.
- Comparative studies of existing evaluation protocols.
- Analysing scalability issues of debiasing methods.
- Case Study Exploration:
- E-commerce platforms.
- Educational environments.
- Entertainment websites.
- Healthcare systems.
- Social media.
- News platforms.
- Digital libraries.
- Job portals.
- Dating platforms.
Important Dates
TBD
Submission Details
We invite authors to submit unpublished original papers, written in English. Submitted papers should not have been previously published or accepted for publication in substantially similar form in any peer-reviewed venue, such as journals, conferences, or workshops.
The authors should consult the Springer’s authors’ guidelines and use their proceedings templates, either LaTeX or Word.
Papers should be submitted as PDF files to Easychair at https://easychair.org/conferences/?conf=bias2024.
We will consider three different submission types:
- Full papers (12 pages) should be clearly placed with respect to the state of the art and state the contribution of the proposal in the domain of application, even if presenting preliminary results. In particular, research papers should describe the methodology in detail, experiments should be repeatable, and a comparison with the existing approaches in the literature should be made.
- Reproducibility papers (12 pages) should repeat prior experiments using the original source code and datasets to show how, why, and when the methods work or not (replicability papers) or should repeat prior experiments, preferably using the original source code, in new contexts (e.g., different domains and datasets, different evaluation and metrics) to further generalize and validate or not previous work (reproducibility papers).
- Short paper (6 pages) or position papers (4 pages) should introduce new point of views in the workshop topics or summarize the experience of a group in the field. Practice and experience reports should present in detail real-world scenarios in which search and recommender systems are exploited.
Submissions should not exceed the indicated number of pages, including any diagrams and references.
All submissions will go through a double-blind review process and be reviewed by at least three reviewers on the basis of relevance for the workshop, novelty/originality, significance, technical quality and correctness, quality and clarity of presentation, quality of references and reproducibility.
Submitted papers will be rejected without review in case they are not properly anonymized, do not comply with the template, or do not follow the above guidelines.
The accepted papers and the material generated during the meeting will be available on the workshop website. It is planned to send the workshop proceedings for consideration for inclusion as a Springer's Communications in Computer and Information Science (CCIS) revised post-proceedings volume, indexed on Google Scholar, DBLP and Scopus. The authors of selected papers may be invited to submit an extended version in a journal special issue.
Please be aware that at least one author per paper needs to register and attend the workshop to present the work.
We expect authors, the program committee, and the organizing committee to adhere to the ACM’s Conflict of Interest Policy and the ACM’s Code of Ethics and Professional Conduct.
Keynote Speakers
TBD
Program
- TBD
Organization
Workshop Chairs
- Alejandro Bellogin , Universidad Autonoma de Madrid (Spain)
- Ludovico Boratto, University of Cagliari (Italy)
- Styliani Kleanthous, Open University of Cyprus (Cyprus)
- Elisabeth Lex, Graz University of Technology (Austria)
- Francesca Maridina Malloci, University of Cagliari (Italy)
- Mirko Marras, University of Cagliari (Italy)
Program Committee
- TBC
Register
Related Workshops
We also invite you to check out the three related workshops:
- 5th International Workshop on Algorithmic Bias in Search and Recommendation (Bias@SIGIR2024)
- 4th International Workshop on Algorithmic Bias in Search and Recommendation (Bias@ECIR2023)
- 3rd International Workshop on Algorithmic Bias in Search and Recommendation (Bias@ECIR2022)
- 2nd International Workshop on Algorithmic Bias in Search and Recommendation (Bias@ECIR2021)
- 1st International Workshop on Algorithmic Bias in Search and Recommendation (Bias@ECIR2020)
Contacts
For general enquiries on the workshop, please send an email to alejandro.bellogin@uam.es, ludovico.boratto@acm.org, s.kleanthous@cyens.org.cy, elisabeth.lex@tugraz.at, francescam.malloci@unica.it, mirko.marras@acm.org.