Instagram

Report March 2026

Submitted
Commitment 31
Relevant Signatories commit to integrate, showcase, or otherwise consistently use fact-checkers' work in their platforms' services, processes, and contents; with full coverage of all Member States and languages.
We signed up to the following measures of this commitment
Measure 31.1 and 31.2
In line with this commitment, did you deploy new implementation measures (e.g. changes to your terms of service, new tools, new policies, etc)?
No
If yes, list these implementation measures here
There have been no updates since the last submitted report.


Do you plan to put further implementation measures in place in the next 6 months to substantially improve the maturity of the implementation of this commitment?
No
If yes, which further implementation measures do you plan to put in place in the next 6 months?
As currently drafted, this chapter covers the current practices for Facebook and Instagram in the EU. In keeping with Meta’s public announcements on 7 January 2025, we will continue to assess the applicability of this chapter to Facebook and Instagram and we will keep under review whether it is appropriate to make alterations in light of changes in our practices, such as the deployment of Community Notes.
Measure 31.1 and 31.2
31.1: Relevant Signatories that showcase User Generated Content (UGC) will integrate, showcase, or otherwise consistently use independent fact-checkers’ work in their platforms’ services, processes, and contents across all Member States and across formats relevant to the service. Relevant Signatories will collaborate with fact-checkers to that end, starting by conducting and documenting research and testing. 31.2: Relevant Signatories that integrate fact-checks in their products or processes will ensure they employ swift and efficient mechanisms such as labelling, information panels or policy enforcement to help increase the impact of fact-checks on audiences.
Instagram
QRE 31.1.1 (for Measures 31.1 and 31.2)
Relevant Signatories will report on their specific activities and initiatives related to Measures 31.1 and 31.2, including the full results and methodology applied in testing solutions to that end.
When content has been rated by fact-checkers, we take action to (1) label it and (2) ensure fewer people see it, and (3) sanction repeat offenders. Specifically, Meta's technology is designed to detect content that is the same or nearly identical to content rated by fact-checkers, applying notices and reduced distribution automatically. This integration operates across all content formats relevant to the service, including public posts, ads, articles, photos, videos, Reels, and text-only posts on both Facebook and Instagram. 

Labeling. When content has been rated by fact-checkers, we add a notice to it so people can read additional context. Content rated Satire or True won't be labeled but a fact-check article will be appended to the post on Facebook. We also notify people before they try to share this content or if they shared it in the past. We use our technology to detect content that is the same or almost exactly the same as that rated by fact-checkers, and add notices to that content as well. 

Ensuring fewer people see misinformation. Once a fact-checker has rated a piece of content as False, Altered or Partly false, or we detect it as near identical, it will appear lower in Feed on Facebook. We dramatically reduce the distribution of False and Altered posts, and reduce the distribution of Partly false to a lesser extent. 

Repeat offenders. Pages, groups, profiles, and websites that repeatedly share content rated False or Altered will be put under some restrictions for a given time period. This includes removing them from the recommendations we show people, reducing their distribution, removing their ability to monetize and advertise, and removing their ability to register as a news Page. 

Detection. Meta's systems support fact-checkers' work through a signals-based detection approach, which uses various inputs - including user flags reporting "false information" - to identify and enqueue content for fact-checker review. Fact-checkers ultimately decide what to review and rate. Once content is rated, Meta applies automated enforcement actions (labeling, reduced distribution, ad rejection) and extends these actions to near-identical content detected through matching technology. 

In terms of AI-generated content, fact-checkers may rate AI-generated media under our fact-checking program policies. They often rely on AI experts and visual techniques to aid in the detection of this content. 
SLI 31.1.1
Member State level reporting on use of fact-checks by service and the swift and efficient mechanisms in place to increase their impact, which may include (as depends on the service): number of fact-check articles published; reach of fact-check articles; number of content pieces reviewed by fact-checkers.
Filtered to content created on Instagram in EEA Member State countries from 01/07/2025 to 31/12/2025:: 

1. Number of distinct pieces of content viewed on Instagram that were treated with a fact-checking label due to a falsity assessment by third party fact-checkers between 01/07/2025 to 31/12/2025:.
2. Number of distinct articles written by 3PFCs that were used on Instagram to apply an inform treatment to a content from 01/07/2025 to 31/12/2025:*

*This metric shows the number of distinct fact-checking articles written by Meta’s 3PFC partners and utilised to label content in each EEA Member State. As articles may be used in multiple countries, and several articles may be used to label a piece of content, the total sum of articles utilised for all Member States exceeds the number of distinct articles created in the EEA (24,000). This is expected.
Content viewed on Instagram and treated with fact checks, due to a falsity assessment by third party fact checkers between 01/07/2025 to 31/12/2025: % of reshares attempted that were not completed on treated content - Instagram between 01/07/2025 to 31/12/2025.
Austria Over 22,000 61.40%
Belgium Over 26,000 63.90%
Bulgaria Over 9,500 63.70%
Croatia Over 10,000 63.70%
Cyprus Over 9,800 69.00%
Czech Republic Over 13,000 58.30%
Denmark Over 14,000 61.80%
Estonia Over 3,900 51.20%
Finland Over 12,000 61.30%
France Over 60,000 67.10%
Germany Over 92,000 60.90%
Greece Over 19,000 67.90%
Hungary Over 9,500 62.50%
Ireland Over 20,000 64.50%
Italy Over 73,000 63.90%
Latvia Over 4,400 80.00%
Lithuania Over 5,500 59.70%
Luxembourg Over 4,700 66.50%
Malta Over 4,300 74.80%
Netherlands Over 35,000 58.00%
Poland Over 24,000 65.00%
Portugal Over 34,000 65.50%
Romania Over 15,000 59.40%
Slovakia Over 9,000 51.70%
Slovenia Over 5,900 58.80%
Spain Over 69,000 67.40%
Sweden Over 25,000 59.00%
Iceland Over 2,600 60.80%
Liechtenstein Over 310 62.50%
Norway Over 13,000 58.20%
Total EU Over 280,000
SLI 31.1.2
An estimation, through meaningful metrics, of the impact of actions taken such as, for instance, the number of pieces of content labelled on the basis of fact-check articles, or the impact of said measures on user interactions with information fact-checked as false or misleading.
1.  Number of distinct pieces of content viewed on Instagram that were treated with a fact-checking label due to a falsity assessment by third party fact checkers between 01/07/2025 to 31/12/2025.

2. Rate of reshare non-completion among the unique attempts by users to reshare a content on Instagram that was treated with a fact-checking label in EU Member State countries from 01/07/2025 to 31/12/2025.
Content viewed on Instagram and treated with fact checks, due to a falsity assessment by third party fact checkers between 01/07/2025 to 31/12/2025. % of reshares attempted that were not completed on treated content - Instagram between 01/07/2025 to 31/12/2025.
Austria Over 22,000 61.40%
Belgium Over 26,000 63.90%
Bulgaria Over 9,500 63.70%
Croatia Over 10,000 63.70%
Cyprus Over 9,800 69.00%
Czech Republic Over 13,000 58.30%
Denmark Over 14,000 61.80%
Estonia Over 3,900 51.20%
Finland Over 12,000 61.30%
France Over 60,000 67.10%
Germany Over 92,000 60.90%
Greece Over 19,000 67.90%
Hungary Over 9,500 62.50%
Ireland Over 20,000 60.80%
Italy Over 73,000 63.90%
Latvia Over 4,400 62.50%
Lithuania Over 5,500 59.70%
Luxembourg Over 4,700 66.50%
Malta Over 4,300 74.80%
Netherlands Over 35,000 58.00%
Poland Over 24,000 65.00%
Portugal Over 34,000 65.50%
Romania Over 15,000 59.40%
Slovakia Over 9,000 51.70%
Slovenia Over 5,900 58.80%
Spain Over 69,000 67.40%
Sweden Over 25,000 59.00%
Iceland Over 2,600 64.50%
Liechtenstein Over 300 80.00%
Norway Over 13,000 58.20%
Total EU Over 280,000
SLI 31.1.3
Signatories recognise the importance of providing context to SLIs 31.1.1 and 31.1.2 in ways that empower researchers, fact-checkers, the Commission, ERGA, and the public to understand and assess the impact of the actions taken to comply with Commitment 31. To that end, relevant Signatories commit to include baseline quantitative information that will help contextualise these SLIs. Relevant Signatories will present and discuss within the Permanent Task-force the type of baseline quantitative information they consider using for contextualisation ahead of their baseline reports.
Average of monthly active users on Instagram in the European Union between 01/07/2025 to 31/12/2025.

There have been no significant updates since the last submitted report.

Over a 6-month period, ending 31 December 2025 (i.e., 1 July 2025 - 31 December 2025), there were a total of approximately 289 million average monthly active users on Instagram in the EU. For monthly active user numbers at a Member State level, please refer to our most recent Instagram DSA transparency report.