Abstract
As people increasingly rely on online media and recommender systems to consume information,
engage in debates and form their political opinions, the design goals of online media and news
recommenders have wide implications for the political and social processes that take place online
and offline. Current recommender systems have been observed to promote personalization and
more effective forms of informing, but also to narrow the user’s exposure to diverse content.
Concerns about echo-chambers and filter bubbles highlight the importance of design metrics that
can successfully strike a balance between accurate recommendations that respond to individual
information needs and preferences, while at the same time addressing concerns about missing out
important information, context and the broader cultural and political diversity in the news, as
well as fairness. A broader, more sophisticated vision of the future of personalized recommenders
needs to be formed–a vision that can only be developed as the result of a collaborative effort by
different areas of academic research (media studies, computer science, law and legal philosophy,
communication science, political philosophy, and democratic theory). The proposed workshop
will set first steps to develop such a much needed vision on the role of recommender systems
on the democratic role of the media and define the guidelines as well as a manifesto for future
research and long-term goals for the emerging topic of fairness, diversity, and personalization in
recommender systems.
diversity, fairness, frontpage, Mediarecht, personalisatie, recommender systems
Bibtex
Article{Bernstein2020,
title = {Diversity, Fairness, and Data-Driven Personalization in (News) Recommender System},
author = {Bernstein, A. and Vreese, C.H. de and Helberger, N. and Schulz, W. and Zweig, K.A.},
url = {https://www.ivir.nl/publicaties/download/dagrep_v009_i011_p117_19482.pdf},
doi = {https://doi.org/10.4230/DagRep.9.11.117},
year = {0402},
date = {2020-04-02},
journal = {Dagstuhl Reports},
volume = {9},
number = {11},
pages = {117-124},
abstract = {As people increasingly rely on online media and recommender systems to consume information,
engage in debates and form their political opinions, the design goals of online media and news
recommenders have wide implications for the political and social processes that take place online
and offline. Current recommender systems have been observed to promote personalization and
more effective forms of informing, but also to narrow the user’s exposure to diverse content.
Concerns about echo-chambers and filter bubbles highlight the importance of design metrics that
can successfully strike a balance between accurate recommendations that respond to individual
information needs and preferences, while at the same time addressing concerns about missing out
important information, context and the broader cultural and political diversity in the news, as
well as fairness. A broader, more sophisticated vision of the future of personalized recommenders
needs to be formed–a vision that can only be developed as the result of a collaborative effort by
different areas of academic research (media studies, computer science, law and legal philosophy,
communication science, political philosophy, and democratic theory). The proposed workshop
will set first steps to develop such a much needed vision on the role of recommender systems
on the democratic role of the media and define the guidelines as well as a manifesto for future
research and long-term goals for the emerging topic of fairness, diversity, and personalization in
recommender systems.},
keywords = {diversity, fairness, frontpage, Mediarecht, personalisatie, recommender systems},
}