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Tackling Peer-to-Peer Discrimination in the Sharing Economy

Publications associées (40)

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Human biases in body measurement estimation

Robert West, Venkata Rama Kiran Garimella

Body measurements, including weight and height, are key indicators of health. Being able to visually assess body measurements reliably is a step towards increased awareness of overweight and obesity and is thus important for public health. Nevertheless it ...

SPRINGER2020

Can Who-Edits-What Predict Edit Survival?

Matthias Grossglauser, Lucas Maystre, Victor Kristof

As the number of contributors to online peer-production systems grows, it becomes increasingly important to predict whether the edits that users make will eventually be beneficial to the project. Existing solutions either rely on a user reputation system o ...

ACM2018

Selection Bias in News Coverage: Learning it, Fighting it

Karl Aberer, Jérémie Rappaz

News entities must select and filter the coverage they broadcast through their respective channels since the set of world events is too large to be treated exhaustively. The subjective nature of this filtering induces biases due to, among other things, res ...

2018

Computable Bounds on the Exploration Bias

Michael Christoph Gastpar, Ibrahim Issa

Adaptive data analysis is known to introduce bias in reported measurements. Russo and Zou [1] recently introduced an information-theoretic framework to study this problem. Herein, this framework is adopted and new dependence measures are introduced to boun ...

2018

Exploring Selection Bias by Causal Frailty Models

Mats Julius Stensrud

Counter-intuitive associations appear frequently in epidemiology, and these results are often debated. In particular, several scenarios are characterized by a general risk factor that appears protective in particular subpopulations, for example, individual ...

2017

AnonRep: Towards Tracking-Resistant Anonymous Reputation

Bryan Alexander Ford, Ennan Zhai

Reputation systems help users evaluate information quality and incentivize civilized behavior, often by tallying feedback from other users such as "likes" or votes and linking these scores to a user’s long-term identity. This identity linkage enables user ...

USENIX2016

Probing the Limits of Social Data

Alexandra Olteanu

Online social data has been hailed to provide unprecedented insights into human phenomena due to its ability to capture human behavior at a scale and level of detail, both in breadth and depth, that is hard to achieve through conventional data collection t ...

EPFL2016

The consequences of not accounting for background selection in demographic inference

Jeffrey David Jensen, Gregory Bruce Ewing

Recently, there has been increased awareness of the role of background selection (BGS) in both data analysis and modelling advances. However, BGS is still difficult to take into account because of tractability issues with simulations and difficulty with no ...

Wiley-Blackwell2016

Quantifying the Bullwhip Effect Using Two-Echelon Data: A Cross-Industry Empirical Investigation

Ralf Seifert, Olov Isaksson

The bullwhip effect denotes the phenomenon whereby demand variability is amplified from a downstream site (buyer) to an upstream site (supplier) in the supply chain. This paper contributes to the literature that empirically investigates the bullwhip effect ...

Elsevier2016

Origin and nature of measurement bias in catadioptric parallel goniophotometers

Marilyne Andersen, Boris Clément Karamata

We briefly categorize and compare parallel goniophotometers, which are instruments capable of simultaneously measuring the far-field distribution of light scattered by a surface or emitted by a source over a large solid angle. Little is known about the acc ...

2014