well being
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2022 ◽  
Vol 87 ◽  
pp. 102456
Author(s):  
Virginia Ballesteros-Arjona ◽  
Laura Oliveras ◽  
Julia Bolívar Muñoz ◽  
Antonio Olry de Labry Lima ◽  
Juli Carrere ◽  
...  

2022 ◽  
Vol 16 (2) ◽  
pp. 1-34
Author(s):  
Arpita Biswas ◽  
Gourab K. Patro ◽  
Niloy Ganguly ◽  
Krishna P. Gummadi ◽  
Abhijnan Chakraborty

Many online platforms today (such as Amazon, Netflix, Spotify, LinkedIn, and AirBnB) can be thought of as two-sided markets with producers and customers of goods and services. Traditionally, recommendation services in these platforms have focused on maximizing customer satisfaction by tailoring the results according to the personalized preferences of individual customers. However, our investigation reinforces the fact that such customer-centric design of these services may lead to unfair distribution of exposure to the producers, which may adversely impact their well-being. However, a pure producer-centric design might become unfair to the customers. As more and more people are depending on such platforms to earn a living, it is important to ensure fairness to both producers and customers. In this work, by mapping a fair personalized recommendation problem to a constrained version of the problem of fairly allocating indivisible goods, we propose to provide fairness guarantees for both sides. Formally, our proposed FairRec algorithm guarantees Maxi-Min Share of exposure for the producers, and Envy-Free up to One Item fairness for the customers. Extensive evaluations over multiple real-world datasets show the effectiveness of FairRec in ensuring two-sided fairness while incurring a marginal loss in overall recommendation quality. Finally, we present a modification of FairRec (named as FairRecPlus ) that at the cost of additional computation time, improves the recommendation performance for the customers, while maintaining the same fairness guarantees.


2022 ◽  
Vol 17 ◽  
pp. e00294
Author(s):  
Retno Ardianti ◽  
Martin Obschonka ◽  
Per Davidsson

2022 ◽  
Vol 28 (2) ◽  
pp. 100189
Author(s):  
Maria Bastida ◽  
Isabel Neira ◽  
Maricruz Lacalle-Calderon

2022 ◽  
Vol 25 ◽  
pp. 100369
Author(s):  
Muhammad Hassan Danish ◽  
Shahzada Muhammad Naeem Nawaz

2022 ◽  
Vol 11 (3) ◽  
pp. 0-0

Introduction: Healthcare workers face incomparable work and psychological demands that are amplified throughout the COVID-19 pandemic. Aim: This study aimed to investigate the psychological impact of the COVID-19 pandemic on health care workers in Jordan. Method: A cross-sectional design was used. Data was collected using an online survey during the outbreak of COVID-19. Results: Overall, of the 312 healthcare workers, almost 38% and 36% presented with moderate to severe anxiety and depression consecutively. Nurses reported more severe symptoms than other healthcare workers. And both anxiety and depression were negatively correlated with well-being. Getting infected was not an immediate worry among healthcare workers; however, they were worried about carrying the virus to their families. Implications for Practice: Stakeholders must understand the impact of COVID-19 on healthcare workers and plan to provide them with the required psychological support and interventions at an early stage.


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