← DOOMRADAR
METHODOLOGY

How DoomRadar works

DoomRadar combines automated data collection, multilingual similarity analysis and AI-assisted classification to build an event-level risk feed.

1. Collection

DoomRadar monitors publicly available news metadata and reporting from external publishers. Source URLs are preserved and displayed on event pages.

2. Event clustering

Multilingual semantic embeddings are used to identify reports that may describe the same underlying event. Additional similarity checks reduce accidental grouping of unrelated stories.

3. Relevance

Events are screened for meaningful wider risk or disruption. Routine entertainment, sports, lifestyle, minor local incidents and other low-impact stories are normally excluded from the public feed.

4. Doom Score

The Doom Score ranges from 0 to 100 and represents an estimate of potential severity and wider impact.

0–20 Limited21–40 Localized41–60 Meaningful61–80 Serious81–100 Exceptional

It is not a probability that an event will happen, a prediction of casualties, or a forecast of financial losses.

5. For Me

Country-specific analysis estimates possible practical transmission channels such as travel disruption, energy costs, supply chains, security or infrastructure.

6. Market Impact

Market analysis describes plausible directional pressure on selected assets or sectors. It does not predict prices, returns or trading outcomes and is not investment advice.

Limitations

Automated systems can misunderstand reports, merge unrelated stories, miss important coverage or assign imperfect scores. Readers should verify important information using the linked original sources.