Mobile with Spotify music app

Considerate and Accurate Multi-party Recommender Systems for Constrained Resources

Focus Areas: News and Media, Transport and Mobility, Health, and Social Services
Research Program: Machines

This project will create a next generation recommender system that enables equitable allocation of constrained resources. The project will produce novel hybrid socio-technical methods and resources to create a Considerate and Accurate REcommender System (CARES), evaluated with social science and behavioural economics lenses.

CARES will transform the sharing economy by delivering systems and methods that improve user and non-user experiences, business efficiency, and corporate social responsibility.


Participate in an online user study on multi-party fair recommendations

We are looking for users of the Spotify music application to complete a brief online study. In the study, you are expected to browse music recommendations and answer a set of questions.

The study will take less than 10 minutes, and you will be entered into a draw for a $30 (AUD) online gift card (1 win for every 10 participants).

You will need to have an active Spotify account with at least 6 months of listening history to take part.

To verify your eligibility and participate in the study, please fill out this form.


ADM+S Chief Investigator Mark Sanderson

Prof Mark Sanderson

Lead Investigator

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ADM+S Chief Investigator Christopher Leckie

Prof Christopher Leckie

Chief Investigator

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Julian Thomas

Prof Julian Thomas

Chief Investigator

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Jeffrey Chan

Dr Jeffrey Chan

Associate Investigator

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Danula Hettiachchi

Dr Danula Hettiachchi

Research Fellow

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Indigo Holcombe-James Headshot

Dr Indigo Holcombe-James

Research Fellow

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ADM+S Investigator Flora Salim

Prof Flora Salim

Associate Investigator

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University of Amsterdam

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