Information Integrity and Public Trust
The Global Risks Forum (GRF)
Misinformation is false or misleading content shared without intent to deceive; disinformation is spread deliberately, often in coordinated campaigns. Both exploit attention, emotion and gaps in trusted information. Responses range from labelling and prebunking to platform rules and law, and each carries risks to free expression. This page sets out how false information spreads and is countered, the records that measure it, and who decides.
GRF · In development · service level R0
Misinformation is false or misleading content shared without intent to deceive; disinformation is spread deliberately, often in coordinated campaigns. Both exploit engagement-driven ranking, coordination and information gaps. Legislatures, platforms, digital services regulators and electoral authorities hold the decisions on responses.
For misinformation and disinformation, in GRF's situational-awareness reading, the map opens on population density, night lights and flood water, framed on Eastern Europe; 3 further NASA layers wait in the list.
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Layers 3
People and exposure, for this page
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NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
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For misinformation and disinformation, in GRF's situational-awareness reading, the map opens on population density, night lights and flood water, framed on Eastern Europe; 3 further NASA layers wait in the list.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.
Layers and dates
Information harms and analytical limits. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Ranking systems that optimise for engagement favour emotive and novel content, which false claims often are. Reach grows faster than corrections can follow.
Networks of accounts, paid influencers and automated tools make fringe narratives look popular. Coordinated inauthentic behaviour is a pattern of conduct as much as a content problem.
Where official information is late, unclear or distrusted, people fill the gap with whatever circulates. Data voids on new topics are exploited quickly.
Laws against false information can be used against journalists and critics. Responses that target behaviour and transparency carry less risk to expression than bans on content.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Malinformation | Genuine information shared out of context or to cause harm, such as leaked private data. |
| Prebunking | Warning people in advance about manipulation techniques or likely false claims so they recognise them later. |
| Data void | A topic or search term for which little reliable content exists, which manipulators can fill. |
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Coordinated inauthentic behaviour networks removed | count by platform and origin | quarterly | Platform threat reports | REPORTED |
| Fact-checks published | count by country and topic | monthly | Fact-checking databases | REPORTED |
| Exposure to false content | share of users exposed | per study | Research audits and panels | ESTIMATED |
| Prevalence of misinformation in sampled content | share of sampled items | per study | Content audits | ESTIMATED |
| Laws penalising false information | count by country | on change | Legal databases | OFFICIAL |
| Self-reported concern about what is real online | share of respondents | annual | Digital News Report survey | ESTIMATED |
The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.
Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| EU Disinformation Code transparency centre reports | Signatories' reports on implementing commitments | Free to read, terms to check |
| Platform threat and coordinated behaviour reports | Networks removed and tactics observed | Free to read, terms per platform |
| Google Fact Check Explorer and ClaimReview data | Published fact-checks tagged with structured data | Free to access, terms to check |
| Reuters Institute Digital News Report | Survey of news use and concern about misinformation across many countries | Free to read, terms to check |
| EUvsDisinfo database | Cases of pro-Kremlin disinformation compiled by the EEAS East StratCom Task Force | Free to read, EU terms |
Information Integrity and Public Trust prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Legislatures | Whether and how law addresses false information without restricting expression | Comparative laws and their documented use |
| Platform trust and safety teams | Which behaviours and content to act on and how | Network analyses and transparency practice |
| Digital services regulators | Whether platforms assess and mitigate systemic risks adequately | Risk assessments, audits and researcher evidence |
| Electoral authorities | How to protect elections from manipulation | Lessons from past elections and platform reports |
Researchers on misinformation and disinformation ask questions that resist easy answers.
False content can spread through social networks, especially when it is novel, emotional or confirms existing beliefs. Network research shows that a small number of highly active accounts often account for much of the sharing. Coordinated campaigns, sometimes using automated or inauthentic accounts, can amplify narratives and make fringe views appear widespread.
Exposure does not translate simply into belief or action. Research suggests that effects are concentrated among those already predisposed, that people use many sources, and that distrust in institutions makes alternative narratives more attractive. Measuring harm is difficult, and estimates of prevalence depend heavily on definitions and data access. Overstating the problem can itself erode trust and justify disproportionate responses.
Tracing how content spreads using network science. Platform data access is limited and uneven.
Classifiers that flag likely false or coordinated content using machine learning. Error rates and biases need disclosure.
Testing effects of exposure and interventions with social and behavioural science. Lab settings may not reflect real behaviour.
Detailed study of specific campaigns. Attribution to actors is often uncertain.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.