Use Cases

Real-world applications of Semantic Substrates for attribute-based network analysis

Use Cases

Semantic substrates are particularly powerful when node attributes are central to your analysis and you want positions to convey meaning. Here are key application areas:

Organizational Network Analysis

Scenario: Understanding communication or collaboration patterns across departments, roles, and locations.

Semantic substrates reveal:

  • How departments interact with each other
  • Whether silos exist between organizational units
  • Key connectors bridging different groups
  • Differences in connectivity patterns by role level

Example: Placing employees in regions by department, showing collaboration edges to reveal cross-functional relationships and isolated teams.


Citation & Knowledge Networks

Scenario: Analyzing academic citation patterns across disciplines, time periods, or institutions.

Semantic substrates reveal:

  • Cross-disciplinary knowledge flows
  • Which fields cite each other heavily
  • Temporal evolution of research connections
  • Institutional collaboration patterns

Example: Arranging papers by research field, with citation edges showing how knowledge transfers between disciplines.


Social Network Analysis by Demographics

Scenario: Understanding social connections across demographic groups (age, location, interests).

Semantic substrates reveal:

  • Homophily patterns (connections within groups)
  • Bridge individuals connecting different communities
  • Isolated demographic segments
  • Strength of inter-group connections

Example: Positioning users by age group and geographic region, showing friendship edges to reveal generational and regional connection patterns.


Supply Chain by Geography & Type

Scenario: Mapping supplier-manufacturer-customer relationships across regions and product categories.

Semantic substrates reveal:

  • Geographic concentration of supply chain stages
  • Cross-regional dependencies
  • Category-specific supply chain structures
  • Vulnerability points in the network

Example: Arranging companies by region (columns) and supply chain role (rows), showing transaction edges to reveal geographic flow patterns.


Security & Intelligence Analysis

Scenario: Analyzing communication or association networks across entity types and time periods.

Semantic substrates reveal:

  • Relationships between different entity types (people, organizations, locations)
  • Temporal patterns in network activity
  • Entities bridging otherwise separate groups
  • Changes in network structure over time

Example: Placing entities in regions by type and time period, showing connections to understand how networks evolve.


Healthcare Provider Networks

Scenario: Understanding referral patterns across specialties and healthcare facilities.

Semantic substrates reveal:

  • Referral flows between specialties
  • Which facilities are well-connected vs isolated
  • Specialty-specific referral patterns
  • Geographic referral preferences

Example: Arranging providers by specialty (rows) and facility (columns), showing referral edges to understand care coordination patterns.


Software Architecture Analysis

Scenario: Visualizing dependencies between code modules by layer, package, or component type.

Semantic substrates reveal:

  • Layer violations (unexpected cross-layer dependencies)
  • Tightly coupled module groups
  • Interface modules connecting different layers
  • Dependency patterns by component type

Example: Placing modules in regions by architectural layer, showing import dependencies to reveal architecture compliance and coupling.


Financial Transaction Networks

Scenario: Analyzing payment or transaction flows across account types, risk categories, or time periods.

Semantic substrates reveal:

  • Transaction patterns between account types
  • High-risk connection patterns
  • Temporal transaction flow changes
  • Accounts bridging different network segments

Example: Arranging accounts by type and risk score, showing transaction edges to identify unusual cross-category patterns.