📰 News Intelligence (NEWSINT)
Media Reporting as an Intelligence Source
Information
Sources
6
5 no-auth
Mission domains
7
reach
Data points
5
covered
Related INT
4
disciplines
🔌 Sources for News Intelligence (6)
| Source | Category | Auth | Format | |
|---|---|---|---|---|
| DOJ Press Releases (financial fraud) DOJ financial-crime prosecutions. | Enforcement | NONE | json | home↗ api↗ |
| GDELT DOC 2.0 (adverse media) Global news monitoring for adverse media. | Adverse Media | NONE | json | home↗ api↗ |
| Global Terrorism Database Kidnapping/hostage incident dataset (START). | Kidnap & Extortion | NONE | html | home↗ api↗ |
| ReliefWeb (OCHA) Humanitarian situation & disaster feed. | Conflict & Humanitarian | NONE | json | home↗ api↗ |
| START Terrorism Research Radicalization & terrorism datasets (PIRUS/GTD). | Extremism | NONE | html | home↗ api↗ |
| ACLED Conflict Events Geocoded political-violence & kidnapping events. | Kidnap & Extortion | KEY | json | home↗ api↗ |
🎯 Mission Domains served
🔍 Lookup
📊 Pre-built Queries · News Intelligence
🔄 Live Datasets & APIs (3 key-free · ingestible)
📜 Playbook — News Intelligence collection
- Direction — frame the requirement for News Intelligence: what decision does this support, by when?
- Collection — collect from the 6 mapped sources (5 free) — filter the catalog by NEWSINT; capture provenance and observe OPSEC.
- Processing — normalize, de-duplicate and enrich the collected data.
- Analysis — correlate against local holdings; apply ACH; assign confidence.
- Dissemination — open a case, draft a report, share via STIX/MISP.
- Feedback — set an alert rule / watchlist to monitor for change.
⚡ AI Skills & Automation
Automate unattended via the cron pipeline (collect → ingest → resolve → enrich → score → alert).
🧩 Advanced Capabilities
🔗 Pivot to related disciplines
✨ Enrichment pathways
🎯 Mission
NEWSINT monitors global news and media to extract events, entities, and sentiment for early warning and situational awareness. It answers what happened, where and when, who is involved, and how coverage and tone are trending.
📡 Collection methods
- Global multilingual news aggregation with geocoded event extraction
- Named-entity recognition and CAMEO-style event coding of actors and actions
- Sentiment, tone, and framing analysis compared across outlets
- Machine translation and cross-source deduplication of the same story
- Media-bias and source-reliability tagging for weighting
- Breakout and anomaly detection on coverage volume for alerting
📚 Key sources & datasets
🎫 Data points produced
🔧 Tools & frameworks
- GDELT Analysis tools
- Media Cloud
- spaCy
- newspaper3k
- QGIS
- Elasticsearch/Kibana
📜 News Intelligence Tradecraft
- Collect: ingest multilingual news feeds and RSS scoped to watch topics
- Process: extract entities, geocode events, translate, and deduplicate
- Analyze: score sentiment and detect coverage breakouts against baseline
- Attribute: link events to actors, locations, and prior reporting threads
- Disseminate: publish a geocoded news brief with trend lines and citations
- Action: fire alerts and cue collection in other disciplines
📊 Dashboard KPIs
Articles ingestedEvents geocodedSentiment indexBreakout alertsSources covered
🔍 Pre-built queries
🔗 Cross-discipline pivots
🧩 Advanced Capabilities
Workstation · Copilot · AI Skills · Automation · Playbooks · Lookups · Docs · Reports
🤖 AI Copilot
⚡ AI Skills
🔍 Lookup & Enrich
📚 Docs & Reports
💡 Recommendations
- Explore related tools below
- Automate recurring work via cron