Keep Factually independent
Whether you agree or disagree with our analysis, these conversations matter for democracy. We don't take money from political groups - even a $5 donation helps us keep it that way.
How does Ground News moderate user-submitted news sources?
Executive Summary
Ground News accepts user suggestions for new outlets and handles them through a review process that relies heavily on third‑party bias and credibility ratings rather than internal editorial judgments. The platform aggregates links, displays political bias and factuality labels from firms like AllSides, Ad Fontes Media, and Media Bias/Fact Check, and uses AI‑generated summaries and team review to decide whether to add a suggested source, but the company does not publish a step‑by‑step moderation workflow or a fixed timeline for inclusion [1] [2] [3].
1. How users can propose outlets — the path from suggestion to review
Ground News provides multiple user pathways to propose a new outlet: an in‑app Settings → Support → Suggest News Source option and an email channel (feedback@ground.news) for direct submissions. These mechanisms are described in company help pages and FAQs as the formal entry points for user requests, which include the outlet name and URL; the platform treats these as queued suggestions for staff review. The company’s public materials highlight that user submissions are welcomed and recorded, but they do not reveal the internal triage criteria, staffing levels, or average processing times for those suggestions, leaving an operational black box that users must accept when they submit a request [1] [2].
2. The rating framework that governs acceptance decisions
Ground News does not primarily create original credibility judgments; instead it assigns or displays bias and factuality ratings by aggregating evaluations from third‑party organizations—AllSides, Ad Fontes Media, and Media Bias/Fact Check—which produce the political‑leaning labels shown alongside sources. The platform’s own “rating system” documentation states that these external ratings drive how outlets are presented and compared across coverage clusters. As a result, inclusion appears conditioned on whether the outlet can be mapped to these external taxonomies, and any moderation decision is rendered through that externalized lens rather than a proprietary fact‑checking process [1] [3] [4].
3. What Ground News does with included sources — labels, aggregation, and tools
Once a source is in the database, Ground News aggregates its articles into event clusters and displays bias labels and geographic origin, and it runs AI‑generated summaries to surface how the outlet covered a story. Features like “Blindspot” highlight when stories are predominantly covered by one ideological side, and the platform’s map shows source distribution. This model focuses on contextual transparency rather than censorship: outlets with problematic factual histories can still appear if they cover a story, but they will carry the external rating that warns readers about probable bias or factual weakness [5] [6] [4].
4. Known gaps, criticisms, and paywall effects on transparency
Independent reviewers and critics have flagged limits in Ground News’ approach: aggregation and labelling do not substitute for active editorial verification, and important procedural details—such as whether a source must meet minimum credibility benchmarks or how often third‑party labels are updated—are not publicly documented. Reviewers also note that some of the platform’s deeper analytics and reconciliation reports are behind paywalls, which reduces external scrutiny of moderation decisions and creates asymmetry between paying and non‑paying users who wish to evaluate how sources are vetted [6] [7].
5. Reconciling company claims with independent observations and what remains unknown
Ground News’ public materials and help pages consistently state that the team reviews user submissions and relies on third‑party ratings to contextualize outlets; independent analyses corroborate this structure, noting AI summaries and bias labels drive inclusion and presentation. However, multiple sources agree on a persistent unknown: the precise internal moderation workflow, quality‑control checks on third‑party assessments, and timelines for processing or delisting sources are not disclosed. This leaves a hybrid system where transparency about methodology exists at the label level but operational transparency about moderation actions does not, producing legitimate questions about how disputes and contested outlets are resolved [1] [3] [5].