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Bias 2023 : Fourth International Workshop on Algorithmic Bias in Search and Recommendation

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Link: https://biasinrecsys.github.io/ecir2023/
 
When Apr 2, 2023 - Apr 2, 2023
Where Dublin, Ireland (remote support)
Submission Deadline Jan 19, 2023
Notification Due Feb 16, 2023
Final Version Due Mar 2, 2023
Categories    bias   fairness   information retrieval   recommender systems
 

Call For Papers

Please accept our apologies in case of multiple receptions.
Please send to interested colleagues and students.


Call for Papers

Fourth International Workshop on Algorithmic Bias in Search and Recommendation (Bias 2023)

to be held as part of the 45th European Conference on Information Retrieval (ECIR 2023)

Workshop: April 2, 2023 - Dublin, Ireland (with support for remote attendance)

https://biasinrecsys.github.io/ecir2023/

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Important Dates

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Submissions: January 19, 2023 (extended deadline)

Notifications: February 16, 2023

Camera-Ready Contributions: March 2, 2023

Workshop: April 2, 2023 - Dublin, Ireland (with support for remote attendance)


All deadlines are 11:59pm, AoE time (Anywhere on Earth).

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Workshop Aims and Scope

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Creating efficient and effective search and recommendation algorithms has been the main objective of industry practitioners and academic researchers over the years. However, recent research has shown how these algorithms trained on historical data lead to models that might exacerbate existing biases and generate potentially negative outcomes. Defining, assessing and mitigating these biases throughout experimental pipelines is a primary step for devising search and recommendation algorithms that can be responsibly deployed in real-world applications. This workshop aims to collect novel contributions in this field and offer a common ground for interested researchers and practitioners.

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Workshop Keywords

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Information Retrieval · Recommender Systems · Data and Algorithmic Bias · Fairness

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Workshop Topics

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The workshop welcomes contributions in all topics related to algorithmic bias and fairness in search and recommendation, focused (but not limited) to:

Data Set Collection and Preparation:
- Studying the interplay between bias and imbalanced data or rare classes
- Designing methods for dealing with imbalances and inequalities in data
- Creating collection pipelines that lead to fair and less unbiased data sets
- Collecting data sets useful for the analysis of biased and unfair situations
- Designing collection protocols for data sets tailored to research on bias

Countermeasure Design and Development:
- Formalizing and operationalizing bias and fairness concepts
- Conducting exploratory analysis that uncover novel types of bias
- Designing treatments that mitigate biases in pre-/in-/post-processing
- Devising methods for explaining bias in search and recommendation
- Studying causal and counterfactual reasoning for bias and fairness

Evaluation Protocol and Metric Formulation:
- Performing auditing studies with respect to bias and fairness
- Conducting quantitative experimental studies on bias and unfairness
- Defining objective metrics that consider fairness and/or bias
- Formulating bias-aware protocols to evaluate existing algorithms
- Evaluating existing mitigation strategies in unexplored domains
- Comparative studies of existing evaluation protocols and strategies
- Analysing efficiency and 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

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Submission Details

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All submissions must be written in English. Authors should consult ECIR paper guidelines (https://www.bcs.org/membership/member-communities/information-retrieval-specialist-group/) and Fuhr’s guide to avoid common IR evaluation mistakes (https://sigir.org/wp-content/uploads/2018/01/p032.pdf), for preparing their papers. Authors should consult Springer’s authors’ guidelines (https://resource-cms.springernature.com/springer-cms/rest/v1/content/19242230/data/v9) and use their proceedings templates, either LaTeX (https://resource-cms.springernature.com/springer-cms/rest/v1/content/19238648/data/v4) or Word (https://resource-cms.springernature.com/springer-cms/rest/v1/content/19238706/data/v1).

Papers should be submitted as PDF files to https://easychair.org/conferences/?conf=bias2023.

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 or position papers (6 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. We plan to publish the workshop proceedings 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 (https://www.acm.org/special-interest-groups/volunteer-resources/acm-conflict-of-interest-policy) and the ACM’s Code of Ethics and Professional Conduct (https://www.acm.org/code-of-ethics).

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Attending

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The registration will be managed by the Main Conference organization at https://ecir2023.org. Registration is yet to open.

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Workshop Chairs

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Ludovico Boratto

https://www.ludovicoboratto.com/

University of Cagliari, Cagliari, Italy

Email: ludovico.boratto@acm.org



Stefano Faralli

Sapienza University of Rome, Rome, Italy

Email: stefano.faralli@uniroma1.it



Mirko Marras

http://www.mirkomarras.com/

University of Cagliari, Cagliari, Italy

Email: mirko.marras@acm.org



Giovanni Stilo

University of L’Aquila, L’Aquila, Italy

Email: giovanni.stilo@univaq.it


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Contacts

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For general enquiries on the workshop, please send an email to ludovico.boratto@acm.org, stefano.faralli@uniroma1.it, mirko.marras@acm.org, and giovanni.stilo@univaq.it.

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