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Author
J. Möller
D. Trilling
N. Helberger
B. van Es
Year
2018
Title
Do not blame it on the algorithm
Subtitle
An empirical assessment of multiple recommender systems and their impact on content diversity
Journal
Information Communication and Society
Volume | Issue number
21 | 7
Pages (from-to)
959-977
Document type
Article
Faculty
Faculty of Social and Behavioural Sciences (FMG)
Faculty of Law (FdR)
Institute
Amsterdam School of Communication Research (ASCoR)
Institute for Information Law (IViR)
Abstract

In the debate about filter bubbles caused by algorithmic news recommendation, the conceptualization of the two core concepts in this debate, diversity and algorithms, has received little attention in social scientific research. This paper examines the effect of multiple recommender systems on different diversity dimensions. To this end, it maps different values that diversity can serve, and a respective set of criteria that characterizes a diverse information offer in this particular conception of diversity. We make use of a data set of simulated article recommendations based on actual content of one of the major Dutch broadsheet newspapers and its users (N=21,973 articles, N=500 users). We find that all of the recommendation logics under study proved to lead to a rather diverse set of recommendations that are on par with human editors and that basing recommendations on user histories can substantially increase topic diversity within a recommendation set.

URL
go to publisher's site
Other links
Link to publication in Scopus
Language
English
Note
In special issue: Digital Media, Political Polarization and Challenges to Democracy
Permalink
http://hdl.handle.net/11245.1/4242e2e0-3beb-40a0-a6cb-d8947a13efb4
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  • Do not blame it on the algorithm

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