On the Democratic Role of News Recommenders

By Natali Helberger. Algorithms, Automation, and News, 2019

347 citations recorded by the source corpus.

Abstract Are algorithmic news recommenders a threat to the democratic role of the media? Or are they an opportunity, and, if so, how would news recommenders need to be designed to advance values and goals that we consider essential in a democratic society? These are central questions in the ongoing academic and policy debate about the likely implications of data analytics and machine learning for the democratic role of the media and the shift from traditional mass-media modes of distribution towards more personalised news and platforms Building on democratic theory and the growing body of literature about the digital turn in journalism, this article offers a conceptual framework for assessing the threats and opportunities around the democratic role of news recommenders, and develops a typology of different ‘democratic recommenders’.

Subfields: Communication, General Social Sciences

View Paper: https://www.semanticscholar.org/paper/0f671892c69f428b0d9c90b30e94033f3bb03ffc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Communication

1. Fabio Giglietto
2. Axel Bruns
3. Jonathan Stray

In General Social Sciences

1. Fabio Giglietto
2. Axel Bruns
3. Jonathan Stray
4. Katrin Weller
5. Katharina E. Kinder-Kurlanda

Citations in the corpus

• Aligning AI Optimization to Community Well-Being (2020, background): “News recommendation algorithms can have societal consequences (Helberger 2019) but it is not clear how to manage such algorithms for community well-being.”
• Nathaniel Persily e Joshua A. Tucker (a cura di). Social Media and Democracy. The State of the Field, Prospects for Reform (2021, background): “interested in discussing the democratic implications of digital media are drawing on similar theoretical models, asking what we would want algorithmic curation to look like from different idealistic starting points, whether participatory or deliberative (Helberger 2019).”
• Filter bubble (2019, background): “…connect online in spite of considerable geographical distance, as it enables groups of participants with special interests to share relevant information with each other, or as it enables the members of vulnerable minorities in society to provide mutual support to one another (cf. Helberger, 2019).”