Investigating Algorithmic Misconceptions in a Media Context: Source of a New Digital Divide?

Open Access Journal | ISSN: 2183-2439

Article | Open Access

Investigating Algorithmic Misconceptions in a Media Context: Source of a New Digital Divide?


  • Brahim Zarouali Amsterdam School of Communication Research, University of Amsterdam, The Netherlands
  • Natali Helberger Institute for Information Law, University of Amsterdam, The Netherlands
  • Claes H. de Vreese Amsterdam School of Communication Research, University of Amsterdam, The Netherlands


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Abstract:  Algorithms are widely used in our data-driven media landscape. Many misconceptions have arisen about how these algorithms work and what they can do. In this study, we conducted a large representative survey (N = 2,106) in the Netherlands to explore algorithmic misconceptions. Results showed that a significant part of the general population holds (multiple) misconceptions about algorithms in the media. We found that erroneous beliefs about algorithms are more common among (1) older people (vs. younger people), (2) lower-educated people (vs. higher-educated), and (3) women (vs. men). In addition, it was found that people who had no specific sources to inform themselves about algorithms, and those relying on their friends/family for information, were more likely to have algorithmic misconceptions. Conversely, media channels, school, and having one’s own (online) experiences were found to be sources associated with having fewer algorithmic misconceptions. Theoretical implications are formulated in the context of algorithmic awareness and the digital divide. Finally, societal implications are discussed, such as the need for algorithmic literacy initiatives.

Keywords:  algorithms; algorithmic awareness; digital divide; misconceptions; technology

Published:   18 November 2021


DOI: https://doi.org/10.17645/mac.v9i4.4090


© Brahim Zarouali, Natali Helberger, Claes H. de Vreese. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0), which permits any use, distribution, and reproduction of the work without further permission provided the original author(s) and source are credited.