This article analyses the ethical aspects of multistakeholder recommendation systems (RSs). Following the most common approach in the literature, we assume a consequentialist framework to introduce the main concepts of multistakeholder recommendation. We then consider three research questions: who are the stakeholders in a RS? How are their interests taken into account when formulating a recommendation? And, what is the scientific paradigm underlying RSs? Our main finding is that multistakeholder RSs (MRSs) are designed and theorised, methodologically, according to neoclassical welfare economics. We consider and reply to some methodological objections to MRSs on this basis, concluding that the multistakeholder approach offers the resources ...
Social and socioeconomic interactions and transactions often require trust. In digital spaces, the m...
Typically, recommender systems focus solely on individual preferences of users or small groups of us...
International audienceDifferent sociotechnical recommender systems (personalized advertising engines...
This article analyses the ethical aspects of multistakeholder recommendation systems (RSs). Followin...
This article presents the first, systematic analysis of the ethical challenges posed by recommender ...
In a hyperconnected world, recommendation systems (RS) are one of the most widespread commercial app...
<p>Recommender systems are ubiquitously used by online vendors as profitable tools to boost sales an...
Recommendation systems (RSs) predict what the user likes and recommend it to them. While at the onse...
The goal of our study is to provide a holistic view on various ethical challenges that complicate th...
The rise of digital libraries and the pertinent problem of information overload have contributed to ...
Recommender systems have become an integral part of virtually every e-commerce application on the we...
A Recommendation or Suggestion System (RSS) helps on-demand digital content and social media platfor...
Recommender systems are one of the most widely used services on several online platforms to suggest ...
Recommender Systems as an algorithmic class hide lurking risks despite their prevalence in academic ...
Recommender systems are algorithmic tools that assist users in discovering relevant items from a wid...
Social and socioeconomic interactions and transactions often require trust. In digital spaces, the m...
Typically, recommender systems focus solely on individual preferences of users or small groups of us...
International audienceDifferent sociotechnical recommender systems (personalized advertising engines...
This article analyses the ethical aspects of multistakeholder recommendation systems (RSs). Followin...
This article presents the first, systematic analysis of the ethical challenges posed by recommender ...
In a hyperconnected world, recommendation systems (RS) are one of the most widespread commercial app...
<p>Recommender systems are ubiquitously used by online vendors as profitable tools to boost sales an...
Recommendation systems (RSs) predict what the user likes and recommend it to them. While at the onse...
The goal of our study is to provide a holistic view on various ethical challenges that complicate th...
The rise of digital libraries and the pertinent problem of information overload have contributed to ...
Recommender systems have become an integral part of virtually every e-commerce application on the we...
A Recommendation or Suggestion System (RSS) helps on-demand digital content and social media platfor...
Recommender systems are one of the most widely used services on several online platforms to suggest ...
Recommender Systems as an algorithmic class hide lurking risks despite their prevalence in academic ...
Recommender systems are algorithmic tools that assist users in discovering relevant items from a wid...
Social and socioeconomic interactions and transactions often require trust. In digital spaces, the m...
Typically, recommender systems focus solely on individual preferences of users or small groups of us...
International audienceDifferent sociotechnical recommender systems (personalized advertising engines...