NPOV combines forensic journalism, structured data, and AI-enabled analysis to surface narrative manipulation that would otherwise remain hidden. Here's how we do it.
Narrative manipulation rarely announces itself. It arrives as a series of small, incremental changes — a phrase replaced, a source removed, a descriptor narrowed. No single edit appears decisive, but together they reshape how a subject is presented to readers, search engines, and AI systems. We start every investigation by identifying these patterns.
We analyze the complete revision history of targeted pages, identifying anomalous patterns in timing, frequency, and content of edits that suggest coordinated activity rather than organic editing.
Coordinated campaigns leave signatures: multiple editors arriving on a page simultaneously, identical sourcing strategies, and synchronized reversions. We use structured data analysis to surface these patterns at scale.
We map the relationships between editors who appear across the same articles, talk pages, and arbitration discussions — revealing networks that operate as coordinated groups rather than independent contributors.
Sophisticated campaigns don't just change text — they strategically swap, remove, or reinterpret sources. We track how sourcing changes over time to understand the editorial strategy behind the manipulation.
We don't rely on a single method. Our investigations combine the instincts of experienced journalists with purpose-built technology for the information environment. This hybrid approach allows us to operate at a level of depth and scale that neither traditional journalism nor automated tools can achieve alone.
Deep investigative reporting with source development, document analysis, and the editorial judgment to know what matters — and what's being hidden.
Proprietary tools that process edit histories, revision metadata, and cross-platform activity to detect patterns invisible to manual review.
Machine learning models trained on known manipulation patterns help us identify emerging campaigns earlier and trace their propagation across platforms.
Manipulation doesn't stay on one platform. A distorted Wikipedia article feeds into AI training data, shapes Google search results, gets cited by journalists, and propagates through Reddit and social media. We trace these narrative pathways to document the full scope of the campaign — from the initial edit to the downstream impact.
Wikipedia is a primary training source for every major AI system. We document how manipulated content enters AI models and becomes hard-coded into the answers billions of people rely on.
We track how narratives move from Wikipedia to Reddit, from Reddit to news coverage, and from news coverage back into Wikipedia — mapping the full amplification cycle.
Wikipedia dominates search rankings. We measure how manipulated content affects what appears when people search for the targeted individual, company, or topic.
Journalists routinely cite Wikipedia as background. We document instances where manipulated Wikipedia content enters mainstream media coverage, creating a feedback loop of distortion.
Every NPOV investigation culminates in evidence documented with the rigor needed for legal, media, and strategic decision-making. We don't just find manipulation — we build the case.
If you suspect your narrative is being manipulated on Wikipedia or across the web, we can help you find out — and fight back with evidence.