# Graph Analytics **Entity class:** Computational method family **Domain:** Data science / network analysis / intelligence **Maturity:** Developed ## Definition **Graph analytics** applies algorithms to entities and typed relationships. Common tasks include path finding, connected components, centrality, community detection, similarity, temporal motif detection, anomaly detection, and link prediction. It can operate on a property graph or knowledge graph whose edges preserve source, time, direction, and confidence. In counterterrorism, graph analytics can reveal hidden bridges across communication, travel, finance, location, and identity layers. Its output is probabilistic and collection-dependent. A high score is a prioritization signal, not legal proof, and entity-resolution errors can create convincing but false networks. ## Relationships - **formal basis:** [[wiki/Social Network Analysis|Social Network Analysis]]. - **input preparation:** [[wiki/Entity Resolution|Entity Resolution]]. - **methods:** [[wiki/Community Detection|Community Detection]] and [[wiki/Link Prediction|Link Prediction]]. - **streaming form:** [[wiki/Real-Time Observability|Real-Time Observability]]. - **historical application:** [[wiki/ICEPIC|ICEPIC]]. ## Sources / Provenance - [[research/Immigration and Customs Enforcement Pattern Analysis and Information Collection (ICEPIC)|ICEPIC research dossier]] - [Oxford Journal of Conflict and Security Law — social-network analysis in counterterrorism](https://academic.oup.com/jcsl/article/29/1/165/7603867)