INTELLIGENCE_ANALYTICS
Network metrics | Community detection | Pattern analysis--
NETWORK NODES
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RELATIONSHIPS
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COMMUNITIES
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GRAPH DENSITY
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TOTAL FLIGHTS
CONNECT TWO PEOPLE -- SHORTEST PATH FINDER
Find the shortest chain of connections between any two people. Like "six degrees of separation" — this shows how many intermediaries connect Person A to Person B through shared flights.
NETWORK CENTRALITY RANKINGS
Centrality metrics reveal who holds the most power and influence in the network. Higher scores = more central to the web of connections.
DEGREE CENTRALITY
DEGREE = number of direct connections. A high degree means this person flew with many different people — they're a social hub.
| # | Entity | Score |
|---|---|---|
| Computing... | ||
BETWEENNESS CENTRALITY
BETWEENNESS = how often someone sits on the shortest path between others. High betweenness means they're a gatekeeper — remove them, and parts of the network become disconnected.
| # | Entity | Score |
|---|---|---|
| Computing... | ||
PAGERANK
PAGERANK = importance based on who you're connected to. Being linked to other well-connected people boosts your score. Originally used by Google to rank web pages.
| # | Entity | Score |
|---|---|---|
| Computing... | ||
CLOSENESS CENTRALITY
CLOSENESS = how quickly someone can reach everyone else. A high closeness score means this person is never far from anyone in the network — they have efficient access to all parts of it.
| # | Entity | Score |
|---|---|---|
| Computing... | ||
COMMUNITY DETECTION (LOUVAIN)
Communities are tightly-knit groups detected by the Louvain algorithm. People within a community share more connections with each other than with outsiders. This reveals hidden clusters and inner circles.
Detecting communities...
PATTERN-OF-LIFE FLIGHT HEATMAP
A calendar heatmap showing when flights occurred. Brighter green = more flights that month. Red cells mark statistical anomalies — months with unusually high activity (more than 2 standard deviations above average).
Loading flight data...
BENFORD'S LAW FINANCIAL ANALYSIS
Benford's Law says that in naturally-occurring financial data, the digit "1" appears as the first digit ~30% of the time, "2" about 17%, and so on. If the observed distribution significantly deviates from this pattern, it may indicate fabricated or manipulated numbers.
Analyzing financial data...
ANALYSIS RESULT
Computing...
FREQUENCY DISTRIBUTIONS
Histograms showing how flight counts and connection counts are distributed across all entities. A heavy right tail (skewness > 2) suggests a "power law" — most people have few flights/connections, but a small elite has dramatically more.
FLIGHT COUNT DISTRIBUTION
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CONNECTION COUNT DISTRIBUTION
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RISK LEVEL DISTRIBUTION
Count of entities by assigned risk level. Risk scoring factors in number of documented connections, flight frequency, involvement in legal proceedings, and association with known high-risk individuals.
EVIDENCE TYPE COVERAGE
How many persons have each type of evidence on record. Flight records are the primary dataset; email, court document, and testimony data significantly increase confidence in entity involvement.