Mitigating Misinformation Sharing on Social Media through Personalised Nudging

The ongoing challenge of misinformation on social media motivates ongoing efforts to find effective countermeasures. In this study, we evaluated the potential of personalised nudging to reduce the sharing of misinformation on social media, as personalised support has been successfully applied in other areas of critical information handling. In an online experiment (N = 396) exposing users to social media posts, we assessed the degree of misinformation sharing between groups receiving (1) no nudges, (2) non-personalised nudges, and (3) personalised nudges. Personalisation was based on three psychometric dimensions - general decision-making style, consideration of future consequences, need for cognition - to assign the most appropriate nudge from a pool of five nudges. The results showed significant differences (p < .05) between all three groups, with the personalised nudge group sharing the least misinformation. Detailed analyses at the nudge level revealed that one nudge was universally effective and two nudges were effective only in their personalised form. The results generally confirm the potential of personalisation, although the effect is limited in scope. These findings shed light on the nuanced results of nudging studies, highlight the benefits of personalisation, and raise ethical considerations regarding the privacy implications of personalisation and those inherent in nudges.

Authors

Institutions

Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-05-02
DOI
https://doi.org/10.1145/3711034
Citations
2
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
8.40
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mitigating Misinformation Sharing on Social Media through Personalised Nudging

Katrin Hartwig, Christian Reuter, Tom Biselli
2 citations
Proceedings of the ACM on Human-Computer Interaction
Misinformation and Its Impacts
8.40
article

Mitigating Misinformation Sharing on Social Media through Personalised Nudging

Katrin Hartwig, Christian Reuter, Tom Biselli
article en
2 citations

Abstract

The ongoing challenge of misinformation on social media motivates ongoing efforts to find effective countermeasures. In this study, we evaluated the potential of personalised nudging to reduce the sharing of misinformation on social media, as personalised support has been successfully applied in other areas of critical information handling. In an online experiment (N = 396) exposing users to social media posts, we assessed the degree of misinformation sharing between groups receiving (1) no nudges, (2) non-personalised nudges, and (3) personalised nudges. Personalisation was based on three psychometric dimensions - general decision-making style, consideration of future consequences, need for cognition - to assign the most appropriate nudge from a pool of five nudges. The results showed significant differences (p < .05) between all three groups, with the personalised nudge group sharing the least misinformation. Detailed analyses at the nudge level revealed that one nudge was universally effective and two nudges were effective only in their personalised form. The results generally confirm the potential of personalisation, although the effect is limited in scope. These findings shed light on the nuanced results of nudging studies, highlight the benefits of personalisation, and raise ethical considerations regarding the privacy implications of personalisation and those inherent in nudges.

Proceedings of the ACM on Human-Computer InteractionVol. 9(2)
Technische Universität Darmstadt (DE)
Peace, Justice and strong institutions
Openalex Percentile: Top 3%
Misinformation and Its Impacts
8.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.