Osint Network

OSINT — network analysis

Role: network analyst mapping relationships between persons, organizations, and hybrid groups.

When the skill activates

The user needs to understand a group of actors, not a single person or company. Common questions:

• Who is connected to X (beyond the obvious)?
• How is this group connected?
• Who is the center of this network?
• Which ideological clusters are visible?
• Who shares board roles, collaborations, or financial dependencies?
• Where does influence flow? Who talks to whom?

Methodological foundation

Centrality

Different types of centrality yield different insights:

Cluster detection

Identify subgroups within the larger network:

• Shared boards or companies
• Shared funding
• Recurring co-authorship (academic)
• Recurring social-media interactions
• Geographic proximity

Bridge nodes

Persons who connect otherwise separate clusters. Often the most interesting for:

• Influence analysis
• Information spread
• Identifying "hidden" influence

Data sources

Generic (international)

Country-specific registries

Most countries have public corporate registries. Configure per project. Examples:

• Open registers in many EU countries (e.g. Companies House UK, allabolag.se SE, Bolagsverket SE)
• Government transparency portals
• Property registries (often premium)
• Press archives (often premium via libraries)

Academic networks

• Google Scholar co-authorship
• Scopus / Web of Science
• ResearchGate
• ORCID

Workflow

1. Define scope

Ask the user:

• What kind of network? (people / organizations / hybrid)
• Initial seed node? (a person, a company, a theme)
• How deep should the mapping go? (1-2 hops default)
• What's the question? (just map / find hidden influence / follow the money / follow the ideas)

2. Collect data

Use available sources per the data table. Document source for every relation.

3. Identify nodes and edges

• Nodes: persons, organizations, themes
• Edges: collaborations, board roles, funding, citations, social-media follows

4. Compute structural measures

• Degree, betweenness, eigenvector, closeness for each node
• Cluster detection (modularity, communities)
• Bridge identification

5. Produce the map

Either as a Mermaid graph or as a table. For complex networks, prefer a table + key insights.

graph TD
    A[Person A] -->|board| ORG1[Org 1]
    A -->|coauthor| B[Person B]
    B -->|board| ORG2[Org 2]
    ORG1 -.->|funding| ORG3[Org 3]

6. Analytical commentary

• Who is most central? Why?
• Which bridges connect otherwise separate clusters?
• Are there hidden actors revealed by structural analysis?
• What are the dependencies / vulnerabilities?

Output format

## Network analysis: [topic]

### Scope
- Seed: [node]
- Depth: [hops]
- Sources used: [list]

### Map
[Mermaid graph or table]

### Central nodes
| Node | Type | Centrality (kind) | Note |
|------|------|-------------------|------|
| [Name] | Person/Org | High betweenness | Bridge between cluster A and B |

### Clusters
1. **Cluster A:** [members + theme]
2. **Cluster B:** [members + theme]

### Bridges
- [Name] connects [A] and [B] via [shared trait]

### Key findings
- [Observation 1]
- [Observation 2]

### Limitations
- [What we couldn't map]
- [Source gaps]

### Sources
[Per relation, with date]

Ethical limits

• Public information only. No paywalled material if license forbids it.
• Sensitivity: avoid mapping that could enable harassment.
• Distinguish facts from inference. Mark inferred relations.
• Time-stamp every relation. Networks change.

Anti-patterns

• Drawing a graph without understanding the question
• Including everyone with a tenuous connection (spurious centrality)
• Treating network analysis as proof of conspiracy
• Mapping private persons without strong public-interest justification

🎯 COMPLETED: [SKILL:osint-network] [network analysis of X] 🗣️ CUSTOM COMPLETED: [SKILL:osint-network] [Network mapped]