Americas
29Caribbean
Central America
North America
South America
๐ฆ๐ทargentinaSouth America
๐ง๐ดboliviaSouth America
๐ง๐ทbrazilSouth America
๐จ๐ฑchileSouth America
๐จ๐ดcolombiaSouth America
๐ช๐จecuadorSouth America
๐ฌ๐พguyanaSouth America
๐ต๐พparaguaySouth America
๐ต๐ชperuSouth America
๐ธ๐ทsurinameSouth America
๐บ๐พuruguaySouth America
๐ป๐ชvenezuelaSouth AmericaEurope
43Balkans
Eastern Europe
Northern Europe
๐ฉ๐ฐdenmarkNorthern Europe
๐ช๐ชestoniaNorthern Europe
๐ซ๐ฎfinlandNorthern Europe
๐ฎ๐ธicelandNorthern Europe
๐ฎ๐ชirelandNorthern Europe
๐ฑ๐ปlatviaNorthern Europe
๐ฑ๐นlithuaniaNorthern Europe
๐ณ๐ดnorwayNorthern Europe
๐ธ๐ชswedenNorthern Europe
๐ฌ๐งunited kingdomNorthern EuropeSouthern Europe
Middle East
14Anatolia
Arabian Peninsula
Gulf States
Iran
Mesopotamia
Africa
9Central Africa
North Africa
Southern Africa
Asia
23Central Asia
East Asia
South Asia
Oceania
4Australia & New Zealand
Other
1Other / Unspecified
In this dashboard, online OSINT refers to public, web-published material that is typically edited, attributed, and time-stampedโsuch as reputable local and international news reporting, official government statements and press releases, and other public reports that appear in web-indexed publication feeds. This product does not ingest social media.
Each document is grouped into stability themes (by domain) and summarized using volume- and tone-based indicators. The goal is not to โvote countโ opinions, but to detect sustained shifts in what is being reported and how it is being framed over time.
Signals are organized into six strategically relevant domains: Governance, Economy, Society, National Defense, Health, and Psychological Strain. A Composite index integrates these domains into one country-normalized stability measure.
The dashboard separates domestic (in-country) content from external (rest-of-world) coverage so you can see whether shifts are driven by local conditions, external framing, or both. This is especially useful when international events (sanctions, security incidents, diplomatic disputes) change external attention even if domestic conditions are steady.
- Country-normalized: values are scaled to this countryโs own historical baseline (not cross-country rankings).
- Higher = more stable relative to this countryโs norm; lower = more stressed/volatile narratives vs its norm.
- Use for direction & thresholds: focus on trend, momentum, and threshold crossings (Watch/Stress), not absolute comparisons between countries.
The baseline signal is MA14 (a 14โday moving average) to reduce dayโtoโday noise. Shortโterm momentum uses MA7 (7โday moving average) to surface emerging shifts earlier. When MA7 drops below MA14, momentum is deteriorating.
Not every move is equally โwell supported.โ The Evidence sections show document volume, external attention share, and tone gap to help you judge confidence. Multiโday feed outages are detected and statistically imputed to avoid false drops to zeroโhowever, when evidence is thin, treat sharp changes cautiously and corroborate.
The Currency (FOREX) section integrates country financial series where available. Currency movement is analyzed alongside OSINT stability trends to highlight potential stress signals (e.g., sustained depreciation coinciding with rising economic pressure narratives), or perception-vs-fundamentals gaps when the two diverge.
Sources, scope, and limitations
- Sources: public online publications (news, official statements/press releases, and other web-indexed reports) plus optional internal datasets where configured.
- External context is intentionally included: international attention is retained when it helps explain, shape, or coincide with stability shifts.
- Blackout handling: multi-day outages are detected and statistically imputed to prevent false signal collapses in charts.
- Intended use: situational awareness, indications-and-warning (I&W), scenario development, and planning support (decision aid, not an alarm system).
- Limitations: public-source coverage varies by country and time; correlation is not causation; treat outputs as decision-support inputs and corroborate when stakes are high.
Glossary of key indicators
Analytical metrics used in this dashboard
- Sentiment / Tone: a standardized numerical measure of positive vs negative language in online publication text, used to track narrative pressure over time.
- Document volume: the number of matched documents; higher volume usually means stronger evidence behind a movement.
- Moving Averages (MA): smoothed signals (e.g., MA14 baseline, MA7 momentum) that reduce noise and highlight sustained shifts.
- Momentum (MA7 โ MA14): a short-vs-baseline comparison that signals early acceleration or deterioration.
- MoM / YoY / 24M: month-over-month, year-over-year, and 24-month context comparisons used in tables and KPI cards.
- External attention share: the share of total volume attributable to external sources; rising share can signal growing international focus.
- Tone gap (External vs Domestic): shows when outside framing is more positive/negative than domestic framing.
- Watch/Stress thresholds: practical reference lines used for triage (guidance, not alarms).
- Blackout detection & imputation: multi-day source outages are detected and statistically filled so charts donโt falsely drop to zero; low evidence still warrants caution.
- Correlation (r): measures whether two series move together (association, not causation).
- Trend screening (ฯ, slope): non-parametric trend direction (Kendallโs ฯ) and robust slope estimates to separate drift from noise.
- p-value: indicates whether an observed relationship is unlikely to be random; lower suggests stronger statistical support.
- q-value (FDR): p-value adjusted for multiple comparisons to reduce false positives when many relationships are tested.
- VAR / Granger-style screening: leadโlag models that test whether past values of one series help predict another (decision support, not proof of true causality).
- Lag length (AIC-selected): the number of days the model looks back, chosen to balance fit and simplicity.
- Impulse Response (IRF): model tool showing how a โshockโ in one series can propagate into another across time.
- Stationarity / differencing: statistical conditions and transformations used to make time-series modeling more reliable.
- Forecast fan & threshold probabilities: simulated ranges (p10โp90) plus the probability of Watch/Stress within 30/60/90 days for planning purposes.
Frequently asked questions
1) Where does the OSINT content come from?
2) Does โmore negative toneโ mean the public opposes the government?
3) Why are the scores on a 0โ100 scale?
4) What does MA14 mean, and why is it used?
5) What does โMomentum (MA7 vs MA14)โ tell me?
6) Whatโs the difference between domestic and external sources?
7) What is โExternal Coverage Shareโ used for?
8) What is โTone Gap (External vs Domestic)โ?
9) Why do some charts mention โEvidence Strengthโ?
10) Why do you impute blackouts / outages?
11) What should I do when a category crosses Watch or Stress?
12) What do the Outlook Range charts represent?
13) Does correlation mean one topic causes the other?
14) What does the Leading Signals table mean in practice?
15) What is the Drivers section (Stress vs Resilience) telling me?
16) How should I interpret the FOREX section?
17) How often is the dashboard updated?
18) What is the main value of this dashboard?
๐ธ๐ฆsaudi arabiaArabian Peninsula
๐ท๐ธserbiaBalkans
๐ธ๐ฌsingaporeSoutheast Asia
๐ธ๐ฐslovakiaEastern Europe
๐ธ๐ฎsloveniaBalkans
๐ช๐ธspainSouthern Europe
๐ฑ๐ฐsri lankaSouth Asia
๐ธ๐ทsurinameSouth America
๐ธ๐ชswedenNorthern Europe
๐จ๐ญswitzerlandWestern Europe
๐ธ๐พsyriaLevant


























































































