Algorithmic news selection and personalisation: policy and regulatory option for ensuring news diversity
Research project ‘Algorithmic news selection and personalisation: policy and regulatory option for ensuring news diversity’
Promotor: prof. dr. Eva Lievens
Researcher: Judith Vermeulen
Short description
The subject of this research relates to how policy makers and regulators can guarantee news diversity in times where news is increasingly consumed online as the result of algorithmic selection processes. Thereto it is studied, first of all, whether news personalization as such can be considered a lawful, legitimate and desirable practice, and if so – under which circumstances. Second, it is important to understand how news diversity can be conceptualized as a public policy goal. Third, research will be conducted concerning whether, and if so – how, the use of a personalization algorithm for ensuring/enhancing news diversity should be regulated in view of concerns regarding the transparency and liability/accountability for the deployment of such technologies. Finally, it will be considered which regulatory mechanisms could be used to impose and/or encourage the use of a diversity-enhancing algorithm.
This research is part of a larger, interdisciplinary (computer sciences, communication sciences, linguistics (NLP), law) four-year CRA-project, called #NewsDNA, which is funded by the UGent Special Research Fund. Its primary aim is to develop and test an algorithm that uses diversity as a key driver for personalized recommendations. More information is available at the website of #NewsDNA..