SentinelAlun PreeceIrena SpasićDavid Rogers

Cardiff School of Computer Science & Informatics

Analytic services Decision maker

Data-to-decisions

Data sourceData sources

An open, flexible, scalable suite of technologies intended to support situation understanding and provide actionable intelligence from social data. Sentinel applies semantic models of crime and social reaction to data collected in real-time from a variety of social media sources. The data is analyzed using text mining techniques, enabling Sentinel to deliver interpretations of events via a customizable set of apps. Sentinel is a result of collaboration between the Universities Police Science Institute and the School of Computer Science & Informatics at Cardiff University.

Sentinel

Sentinel core services & models

Data collection servicesExpression & term recognition

Customizable apps

Semantic APIs: who, what, when, where, why

Signal Crimes Conflict

Extremist Narrative

s

5 Ws

Analytic servicesidentify significant

terms

Decision maker

“Bottom-up” issue identification

Data sourceData sources

Analytic servicesmatch data toontology terms

Decision maker

“Top-down” issue identification

Data sourceData sources

data + knowledge = information

we interpret text data using our knowledge of both language & world

data

unprocessed facts

no context or purposeful meaning

information

organized collection of facts

processed data that have meaning & context

information is a joint function of data & knowledge

Ontology

How can we represent knowledge?

ontology

machine readable knowledge representation

models concepts in a domain & their relationships

supports shared understanding between both humans & computers

supports reasoning about the domain

Concepts

a concept represents a class of entities within a domain

each concept is represented by:

ID name(s) definition type

Types

concepts are organized into a hierarchy using is–a (or kind–of) relationship

we can now search by type

... and navigate up & down the hierarchy

Relationships

associative relationships relate concepts across the type hierarchy

we can now search by associations

Current state

448 concepts

357 additional synonyms

121 associations

ontology will continue to evolve in order to:

expand the coverage of the domain

reflect the changes in the domain

Applications

semantic search

keyword to concept mapping

generalization

e.g.

query automatically expanded:improvised explosive device OR car bomb OR truck bomb OR explosive belt OR suicide vest ORpetrol bomb OR Molotov cocktail OR Molotov OR fire bomb OR pipe bomb

Applications

semantic interpretation

annotation

classification

qualitative analysis

Wonderful. Jewish and Muslim folks get together to protect Stoke Newington mosque from hate crime

SENTINEL:0000089:hate crime

SENTINEL:0000119:MuslimSENTINEL:0000121:Jewish

SENTINEL:0000211:mosque

Applications

inference through machine learning

ontology supports features based on meaning (not just words)

infer meaning based on annotated concepts

@Official_EDL: EDL leader Tommy Robinson on way to Woolwich now, Take to the streets peeps ENOUGH IS ENOUGH

stance: hard support

subject side: far right extremism

routine: reacting

dynamic: mobilising

Thanks for listening!