"A Pretty Blunt Approach": Meta's Political Content Reduction Policy and Italian Parliamentarians' Facebook Visibility

In February 2021, Meta announced it would reduce the distribution of political content in users' News Feeds, implementing the policy globally by July 2022 before reversing course in January 2025. Despite the significance of these changes for democratic communication, no independent research has quantified their effects on elected officials. This study examines Meta's political content reduction policy using a dataset of over 2.5 million Facebook posts from Italian parliamentarians, prominent politicians, and political extremist accounts spanning 2021–2025, collected via the Meta Content Library API. Employing a discovery-validation design with structural breakpoint detection methods, the analysis identifies three cross-validated breakpoints that reveal policy effects emerged in Italy approximately ten months before Meta's announced global implementation. The findings document a 72% reduction in average reach for re-elected Members of Parliament, declining from approximately 53,000 views per post before the policy to 15,000 at the trough. Although Meta's January 2025 reversal produced a significant rebound, post-reversal reach recovered to only 65% of pre-policy levels. A robustness check reveals asymmetric effects: while mainstream politicians experienced substantial visibility losses, extremist accounts' high posting volume more than compensated for modest per-post declines, resulting in increased total weekly reach during the policy period. These findings expose significant transparency deficits in Meta's policy communication while also demonstrating the research value of the transparency infrastructure that made this study possible.

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Publication Details

Published
2025-12-30
DOI
https://doi.org/10.31235/osf.io/8dqag_v2
Primary Topic
Misinformation and Its Impacts
Type
article
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article

"A Pretty Blunt Approach": Meta's Political Content Reduction Policy and Italian Parliamentarians' Facebook Visibility

Fabio Giglietto
Misinformation and Its Impacts
article

"A Pretty Blunt Approach": Meta's Political Content Reduction Policy and Italian Parliamentarians' Facebook Visibility

Fabio Giglietto
article en

Abstract

In February 2021, Meta announced it would reduce the distribution of political content in users' News Feeds, implementing the policy globally by July 2022 before reversing course in January 2025. Despite the significance of these changes for democratic communication, no independent research has quantified their effects on elected officials. This study examines Meta's political content reduction policy using a dataset of over 2.5 million Facebook posts from Italian parliamentarians, prominent politicians, and political extremist accounts spanning 2021–2025, collected via the Meta Content Library API. Employing a discovery-validation design with structural breakpoint detection methods, the analysis identifies three cross-validated breakpoints that reveal policy effects emerged in Italy approximately ten months before Meta's announced global implementation. The findings document a 72% reduction in average reach for re-elected Members of Parliament, declining from approximately 53,000 views per post before the policy to 15,000 at the trough. Although Meta's January 2025 reversal produced a significant rebound, post-reversal reach recovered to only 65% of pre-policy levels. A robustness check reveals asymmetric effects: while mainstream politicians experienced substantial visibility losses, extremist accounts' high posting volume more than compensated for modest per-post declines, resulting in increased total weekly reach during the policy period. These findings expose significant transparency deficits in Meta's policy communication while also demonstrating the research value of the transparency infrastructure that made this study possible.

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Misinformation and Its Impacts
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"A Pretty Blunt Approach": Meta's Political Content Reduction Policy and Italian Parliamentarians' Facebook Visibility — Fabio Giglietto · (2025) | TGRS Research Map | TGRS