17 citations · 33 across the 8 of their papers we have counts for
8 papers
Unified Browsing Models for Linear and Grid Layouts
Amifa Raj, Michael Ekstrand
Many information access systems operationalize their results in terms of rankings, which are then displayed to users in various ranking layouts such as linear lists or grids. User…
Towards Measuring Fairness in Grid Layout in Recommender Systems
Amifa Raj, Michael D. Ekstrand
There has been significant research in the last five years on ensuring the providers of items in a recommender system are treated fairly, particularly in terms of the exposure the…
Patterns of gender-specializing query reformulation
Amifa Raj, Bhaskar Mitra, Nick Craswell +1
Users of search systems often reformulate their queries by adding query terms to reflect their evolving information need or to more precisely express their information need when th…
Overview of the TREC 2022 Fair Ranking Track
Michael D. Ekstrand, Graham McDonald, Amifa Raj +1
The TREC Fair Ranking Track aims to provide a platform for participants to develop and evaluate novel retrieval algorithms that can provide a fair exposure to a mixture of demograp…
Much Ado About Gender: Current Practices and Future Recommendations for Appropriate Gender-Aware Information Access
Christine Pinney, Amifa Raj, Alex Hanna +1
Information access research (and development) sometimes makes use of gender, whether to report on the demographics of participants in a user study, as inputs to personalized result…
Fire Dragon and Unicorn Princess; Gender Stereotypes and Children's Products in Search Engine Responses
Amifa Raj, Michael D. Ekstrand
Search engines in e-commerce settings allow users to search, browse, and select items from a wide range of products available online including children's items. Children's products…
Pink for Princesses, Blue for Superheroes: The Need to Examine Gender Stereotypes in Kid's Products in Search and Recommendations
Amifa Raj, Ashlee Milton, Michael D. Ekstrand
In this position paper, we argue for the need to investigate if and how gender stereotypes manifest in search and recommender systems.As a starting point, we particularly focus on…
Comparing Fair Ranking Metrics
Amifa Raj, Michael D. Ekstrand
Ranked lists are frequently used by information retrieval (IR) systems to present results believed to be relevant to the users information need. Fairness is a relatively new but im…