Instagram

Report September 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, we did not introduce any new measures in the reporting period. 
If yes, list these implementation measures here
N/A
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, we do not plan to put further implementation measures in place in the next 6 months.
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 (which, for the avoidance of doubt, has not been rolled out in the EEA during the reporting period).
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) penalise repeat offenders. 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.

When content has been rated by fact-checkers, we add a notice to it so people can read additional context. 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 and Stories on Instagram. We dramatically reduce the distribution of False and Altered posts, and reduce the distribution of Partly False to a lesser extent. Meta does not suggest content to users once it is rated by a fact-checker, which significantly reduces the number of people who see it.

Repeat offenders. Instagram accounts 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 and removing their ability to monetise and advertise.

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 (labelling, 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 programme 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 between 01/01/2026 and 30/06/2026: 

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 01/01/2026 and 30/06/2026:
2. Number of distinct articles written by 3PFCs that were used on Instagram to apply an inform treatment to a content between 01/01/2026 and 30/06/2026:*

These two metrics together show both the scale and impact of fact-checking.

*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 (119,000). This is expected.

**Owing to a number of technical issues, data was not captured for 53 days during this reporting period, primarily from 21 January to 6 March 2026. As a result, the affected metrics should be interpreted as a lower bound of the true volumes.
Content viewed on Instagram and treated with fact-checks, due to a falsity assessment by third-party fact-checkers between 01/01/2026 and 30/06/2026: Number of Articles written by third-party fact-checkers to justify rating on Instagram between 01/01/2026 and 30/06/2026:
Austria 22,762 4,858
Belgium 25,473 5,213
Bulgaria 9,350 2,754
Croatia 8,737 2,799
Cyprus 11,011 2,803
Czech Republic 13,270 3,611
Denmark 13,298 3,407
Estonia 3,408 1,395
Finland 11,332 3,227
France 62,427 8,541
Germany 95,585 11,682
Greece 18,316 4,378
Hungary 9,363 2,735
Ireland 17,697 4,474
Italy 71,244 9,739
Latvia 3,925 1,629
Lithuania 4,966 1,829
Luxembourg 4,265 1,677
Malta 3,890 1,506
Netherlands 34,844 6,296
Poland 22,764 5,180
Portugal 34,253 6,466
Romania 14,839 3,663
Slovakia 8,288 2,655
Slovenia 5,280 1,879
Spain 85,359 10,239
Sweden 24,163 5,059
Iceland 2,259 983
Liechtenstein 329 215
Norway 12,859 3,466
Total 655,556 124,358
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 01/01/2026 and 30/06/2026. 
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 01/01/2026 to 30/06/2026. 

*Owing to a number of technical issues, data was not captured for 53 days during this reporting period, primarily from 21 January to 6 March 2026. As a result, the affected metrics should be interpreted as a lower bound of the true volumes.

Content viewed on Instagram and treated with fact-checks, due to a falsity assessment by third-party fact-checkers between 01/01/2026 and 30/06/2026. % of reshares attempted that were not completed on treated content - Instagram between 01/01/2026 and 30/06/2026.
Austria 22,762 62.13%
Belgium 25,473 61.67%
Bulgaria 9,350 64.36%
Croatia 8,737 59.15%
Cyprus 11,011 61.02%
Czech Republic 13,270 55.71%
Denmark 13,298 60.53%
Estonia 3,408 57.76%
Finland 11,332 61.81%
France 62,427 61.47%
Germany 95,585 62.85%
Greece 18,316 68.09%
Hungary 9,363 58.62%
Ireland 2,259 85.11%
Italy 71,244 62.48%
Latvia 3,925 60.25%
Lithuania 4,966 57.58%
Luxembourg 4,265 60.24%
Malta 3,890 65.19%
Netherlands 34,844 61.27%
Poland 22,764 60.27%
Portugal 34,253 63.39%
Romania 14,839 60.92%
Slovakia 8,288 61.42%
Slovenia 5,280 59.85%
Spain 85,359 64.33%
Sweden 24,163 59.24%
Iceland 2,259 85.11%
Liechtenstein 329 75.00%
Norway 12,859 56.94%
Total 655,556
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 01/01/2026 and 30/06/2026.
There have been no significant updates in methodology since the last submitted report.
Between 1 January - 30 June 2026, there were a total of approximately 297 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.