Misinformation interventions and online sharing behaviour : lessons learned from two pre-registered field studies
| dc.contributor.author | Roozenbeek, Jon | |
| dc.contributor.author | Lasser, Jana | |
| dc.contributor.author | Marks, Malia | |
| dc.contributor.author | Qin, Tianzhu | |
| dc.contributor.author | Garcia, David | |
| dc.contributor.author | Goldberg, Beth | |
| dc.contributor.author | Debnath, Ramit | |
| dc.contributor.author | van der Linden, Sander | |
| dc.contributor.author | Lewandowsky, Stephan | |
| dc.date.accessioned | 2026-02-02T15:28:18Z | |
| dc.date.available | 2026-02-02T15:28:18Z | |
| dc.date.issued | 2025-11 | |
| dc.description.abstract | The spread of misinformation on social media continues to pose challenges. While prior research has shown some success in reducing susceptibility to misinformation at scale, how individual-level interventions impact the quality of content shared on social networks remains understudied. Across two pre-registered longitudinal studies, we ran two Twitter/X ad campaigns, targeting a total of 967 640 Twitter/X users with either a previously validated ‘inoculation’ video about emotional manipulation or a control video. We hypothesized that Twitter/X users who saw the inoculation video would engage less with negative-emotional content and share less content from unreliable sources. We do not find evidence for our hypotheses, observing no meaningful changes in posting or retweeting post-intervention. Our findings are most likely compromised by Twitter/X’s ‘fuzzy matching’ policy, which introduced substantial noise in our data (approx. 7.5% of targeted individuals were actually exposed to the intervention). Our findings are thus probably the result of treatment non-compliance rather than ‘true’ null effects. Importantly, we also demonstrate that different statistical analyses and time windows (looking at the intervention’s effects over 1 h versus 6 h or 24 h, etc.) can yield different and even opposite significant effects, highlighting the risk of interpreting noise from field studies as signal. | |
| dc.description.version | published | deu |
| dc.identifier.doi | 10.1098/rsos.251377 | |
| dc.identifier.ppn | 1963117581 | |
| dc.identifier.uri | https://kops.uni-konstanz.de/handle/123456789/76098 | |
| dc.language.iso | eng | |
| dc.rights | Attribution 4.0 International | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject.ddc | 320 | |
| dc.title | Misinformation interventions and online sharing behaviour : lessons learned from two pre-registered field studies | eng |
| dc.type | JOURNAL_ARTICLE | |
| dspace.entity.type | Publication | |
| kops.citation.bibtex | @article{Roozenbeek2025-11Misin-76098,
title={Misinformation interventions and online sharing behaviour : lessons learned from two pre-registered field studies},
year={2025},
doi={10.1098/rsos.251377},
number={11},
volume={12},
journal={Royal Society Open Science},
author={Roozenbeek, Jon and Lasser, Jana and Marks, Malia and Qin, Tianzhu and Garcia, David and Goldberg, Beth and Debnath, Ramit and van der Linden, Sander and Lewandowsky, Stephan},
note={Article Number: 251377}
} | |
| kops.citation.iso690 | ROOZENBEEK, Jon, Jana LASSER, Malia MARKS, Tianzhu QIN, David GARCIA, Beth GOLDBERG, Ramit DEBNATH, Sander VAN DER LINDEN, Stephan LEWANDOWSKY, 2025. Misinformation interventions and online sharing behaviour : lessons learned from two pre-registered field studies. In: Royal Society Open Science. Royal Society of London. 2025, 12(11), 251377. eISSN 2054-5703. Verfügbar unter: doi: 10.1098/rsos.251377 | deu |
| kops.citation.iso690 | ROOZENBEEK, Jon, Jana LASSER, Malia MARKS, Tianzhu QIN, David GARCIA, Beth GOLDBERG, Ramit DEBNATH, Sander VAN DER LINDEN, Stephan LEWANDOWSKY, 2025. Misinformation interventions and online sharing behaviour : lessons learned from two pre-registered field studies. In: Royal Society Open Science. Royal Society of London. 2025, 12(11), 251377. eISSN 2054-5703. Available under: doi: 10.1098/rsos.251377 | eng |
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<dcterms:abstract>The spread of misinformation on social media continues to pose challenges. While prior research has shown some success in reducing susceptibility to misinformation at scale, how individual-level interventions impact the quality of content shared on social networks remains understudied. Across two pre-registered longitudinal studies, we ran two Twitter/X ad campaigns, targeting a total of 967 640 Twitter/X users with either a previously validated ‘inoculation’ video about emotional manipulation or a control video. We hypothesized that Twitter/X users who saw the inoculation video would engage less with negative-emotional content and share less content from unreliable sources. We do not find evidence for our hypotheses, observing no meaningful changes in posting or retweeting post-intervention. Our findings are most likely compromised by Twitter/X’s ‘fuzzy matching’ policy, which introduced substantial noise in our data (approx. 7.5% of targeted individuals were actually exposed to the intervention). Our findings are thus probably the result of treatment non-compliance rather than ‘true’ null effects. Importantly, we also demonstrate that different statistical analyses and time windows (looking at the intervention’s effects over 1 h versus 6 h or 24 h, etc.) can yield different and even opposite significant effects, highlighting the risk of interpreting noise from field studies as signal.</dcterms:abstract>
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| kops.sourcefield.plain | Royal Society Open Science. Royal Society of London. 2025, 12(11), 251377. eISSN 2054-5703. Available under: doi: 10.1098/rsos.251377 | eng |
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