Designing social media content recommendation algorithms for societal good

In the face of mounting evidence for a relationship between social media platforms and detrimental societal outcomes such as polarization, the erosion of trust in institutions, and the spread of misinformation, this perspective argues for the design of alternative content recommendation algorithms that serve the societal good and a lively democratic discourse. We propose to approach the design of content recommendation algorithms through the lens of fostering a healthy civic discourse, which serves to identify dimensions of relevance to guide the development of content recommendation algorithms. This approach lends alternative content recommendation algorithms legitimacy by being rooted in the EU's novel Digital Services Act and by aligning content recommendation with democratic values. We explore the trade-off between interventions in content recommendation and freedom of expression and propose a research agenda that uses approaches from multistakeholder metric construction and scenario-based risk assessment to find situation-dependent just balances between individual rights and societal outcomes.

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Publication Details

Journal
Annals of the New York Academy of Sciences
Published
2025-05-05
DOI
https://doi.org/10.1111/nyas.15359
Citations
3
Primary Topic
Social Media and Politics
Type
article
Field-Weighted Citation Impact
11.59

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article

Designing social media content recommendation algorithms for societal good

Jana Lasser, Nikolaus Poechhacker
3 citations
Annals of the New York Academy of Sciences
Social Media and Politics
11.59
article

Designing social media content recommendation algorithms for societal good

Jana Lasser, Nikolaus Poechhacker
article en
3 citations

Abstract

In the face of mounting evidence for a relationship between social media platforms and detrimental societal outcomes such as polarization, the erosion of trust in institutions, and the spread of misinformation, this perspective argues for the design of alternative content recommendation algorithms that serve the societal good and a lively democratic discourse. We propose to approach the design of content recommendation algorithms through the lens of fostering a healthy civic discourse, which serves to identify dimensions of relevance to guide the development of content recommendation algorithms. This approach lends alternative content recommendation algorithms legitimacy by being rooted in the EU's novel Digital Services Act and by aligning content recommendation with democratic values. We explore the trade-off between interventions in content recommendation and freedom of expression and propose a research agenda that uses approaches from multistakeholder metric construction and scenario-based risk assessment to find situation-dependent just balances between individual rights and societal outcomes.

Annals of the New York Academy of SciencesVol. 1548(1)
University of Vienna (AT), University of Graz (AT), Complexity Science Hub (AT)
European Research Council
Openalex Percentile: Top 2%
Social Media and Politics
11.59
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Designing social media content recommendation algorithms for societal good — Jana Lasser, Nikolaus Poechhacker · Annals of the New York Academy of Sciences (2025) | TGRS Research Map | TGRS