Both tech companies and AI algorithms exercise immense power in today's globally interconnected world, which is based on big data and digital footprints of online users. This paper analyses the transfer of power from societies to tech companies and algorithms with the aim of examining whether recommender algorithms can be considered a public good. Deployed methods include content analysis and literature reviews. The study has found that control exercised over public opinion, decisions and moods of online users is unprecedented to such a high degree in human history. The above-mentioned control is based on the impact of both tech companies and algorithms. The limitation of this research is the lack of quantitative analysis. Future research s...
In a hyperconnected world, recommendation systems (RS) are one of the most widespread commercial app...
Recommender systems (RS) are on the rise in many domains. While they ofer great promises, they also ...
Increasingly, algorithms play an important role in everyday decision-making processes. Recommender s...
Recommender algorithms shape societies by individually exposing online users to everything they see,...
Transfer from social to semantic web brought us to an era of algorithmic society, placing issues su...
Internet-based services that build on automated algorithmic selection processes, for example search...
Recommender systems are a widespread type of online algorithm, which suggests personalised contents ...
This proposal describes a project lying at the intersection of Computer Science and Social Sciences ...
Algorithmic recommender systems are on the rise in various societal domains, including journalism. W...
Algorithmic agents permeate every instant of our online existence. Based on our digital profiles bui...
Recommender systems are algorithmic tools that assist users in discovering relevant items from a wid...
Promoting recommender systems in real-world applications requires deep investigations with emphasis ...
Transfer from social to semantic web brought us to an era of algorithmic society, placing issues su...
Social media and multiple online platforms are heavily relying on recommender systems to provide acc...
In a hyperconnected world, recommendation systems (RS) are one of the most widespread commercial app...
Recommender systems (RS) are on the rise in many domains. While they ofer great promises, they also ...
Increasingly, algorithms play an important role in everyday decision-making processes. Recommender s...
Recommender algorithms shape societies by individually exposing online users to everything they see,...
Transfer from social to semantic web brought us to an era of algorithmic society, placing issues su...
Internet-based services that build on automated algorithmic selection processes, for example search...
Recommender systems are a widespread type of online algorithm, which suggests personalised contents ...
This proposal describes a project lying at the intersection of Computer Science and Social Sciences ...
Algorithmic recommender systems are on the rise in various societal domains, including journalism. W...
Algorithmic agents permeate every instant of our online existence. Based on our digital profiles bui...
Recommender systems are algorithmic tools that assist users in discovering relevant items from a wid...
Promoting recommender systems in real-world applications requires deep investigations with emphasis ...
Transfer from social to semantic web brought us to an era of algorithmic society, placing issues su...
Social media and multiple online platforms are heavily relying on recommender systems to provide acc...
In a hyperconnected world, recommendation systems (RS) are one of the most widespread commercial app...
Recommender systems (RS) are on the rise in many domains. While they ofer great promises, they also ...
Increasingly, algorithms play an important role in everyday decision-making processes. Recommender s...