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20162021
most citedExploring Artist Gender Bias in Music Recommendation

25 citations · 101 across the 9 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.SI2019

EviDense: a Graph-based Method for Finding Unique High-impact Events with Succinct Keyword-based Descriptions

Oana Balalau, Carlos Castillo, Mauro Sozio

Despite the significant efforts made by the research community in recent years, automatically acquiring valuable information about high impact-events from social media remains chal…

cs.SI20198 cited

Modeling Human Annotation Errors to Design Bias-Aware Systems for Social Stream Processing

Rahul Pandey, Carlos Castillo, Hemant Purohit

High-quality human annotations are necessary to create effective machine learning systems for social media. Low-quality human annotations indirectly contribute to the creation of i…

cs.IR2019

FairSearch: A Tool For Fairness in Ranked Search Results

Meike Zehlike, Tom Sühr, Carlos Castillo +1

Ranked search results and recommendations have become the main mechanism by which we find content, products, places, and people online. With hiring, selecting, purchasing, and dati…

cs.CY2019

Affirmative Action Policies for Top-k Candidates Selection, With an Application to the Design of Policies for University Admissions

Michael Mathioudakis, Carlos Castillo, Giorgio Barnabo +1

We consider the problem of designing affirmative action policies for selecting the top-k candidates from a pool of applicants. We assume that for each candidate we have socio-demog…

cs.IR201918 cited

SciLens: Evaluating the Quality of Scientific News Articles Using Social Media and Scientific Literature Indicators

Panayiotis Smeros, Carlos Castillo, Karl Aberer

This paper describes, develops, and validates SciLens, a method to evaluate the quality of scientific news articles. The starting point for our work are structured methodologies th…