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Real Time Geopolitical
Risk Analysis
by
@aeneaswiener
About
• Aeneas Wiener
• Co-Founder of Cytora
• Background in Computational
Physics / Electromagnetic
Invisibility Cloaking
Geopolitical Risk
Tactical: As an airline, tell me
every time there is a protest
outside one of the airports
frequented by my fleet.
Strategic: What were
some of the early warning
signals for the Ukrainian
crisis of 2013?
“By 2020 more than 90% of what is
knowable about the world will be in
open source intelligence sources.”
Definitions
• Geopolitical Risk



Risk of loss faced by society and businesses as a result of actions
taken by government or private actors such as protesters,
terrorists and activists.

• Event Extraction



Identification of real world events such as protests, suicide attacks
and insurgency, which can be delineated in space and time.
Event Extraction
• Problem statement
• Recognise 10+ event types from unstructured text
• Event information augmentation (geo, date)
• Event aggregation (group together mentions of same event)
• Two approaches
• Natural language processing (NLP) based pattern matching
• Machine learning (ML) based bag of words classifier
Date Type Lat Lon
04/11/14 Crme N 11° 5' 26'' E 11° 12' 56''
Event Extraction
User Interface
Stream Processing
• Problem statement
• Billions of sentences per day in real time
• Historical archives (10+ years)
• Context
• Micro-services (web crawling, social media crawling, filtering,
geo tagging, event extraction, entity extraction, translation, event
persisting)
Apache Kafka
• Characteristics
• Fault tolerant distributed message log
• Publish/subscribe semantics
• Can extent to queue and workers semantics
• Abstractions
• Topic
• Consumer
• Producer
Apache Kafka + Storm
• Characteristics
• Version controlled processing graph (Storm topology)
• Horizontal scaling within Storm cluster (good resource utilisation)
• Streamparse library for integration with Python
• Issues
• Harder to debug than standalone micro-services
9 June
Isis seize control of Mosul
1 June
ISIL 'kills 102-year-old man'
Event Correlation Analysis
Event Detection during 

2013 Ukraine Crisis
The Cytora platform identified unrest in the East of Ukraine weeks before
mainstream media and other providers.
Conclusions
• Events constitute a lens to observe the real world
• NLP / ML offer viable approaches for event extraction
• Apache Kafka + Storm enable event extraction at scale (It would
take a human 5 years to analyse all the documents the Cytora
system processes in a day.)
Senior Backend 

Engineer
Full-time

Skills:
Python
Distributed Systems
Machine Learning
Full-stack Engineer
Full-time

Skills:
Python
JavaScript
HTML/CSS
Jack Palfrey
Location:
113 Shoreditch High Street
Dev-ops Engineer
Full-time

Skills:
Fabric, Asible or Chef
PostgreSQL/ElasticSearch
Monitoring / log shipping
UNIX administration
Forward Deployed

Engineer
Full-time

Skills:
Python
Project management

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Cytora: Real-Time Political Risk Analysis

  • 1. Real Time Geopolitical Risk Analysis by @aeneaswiener
  • 2. About • Aeneas Wiener • Co-Founder of Cytora • Background in Computational Physics / Electromagnetic Invisibility Cloaking
  • 3. Geopolitical Risk Tactical: As an airline, tell me every time there is a protest outside one of the airports frequented by my fleet. Strategic: What were some of the early warning signals for the Ukrainian crisis of 2013?
  • 4. “By 2020 more than 90% of what is knowable about the world will be in open source intelligence sources.”
  • 5. Definitions • Geopolitical Risk
 
 Risk of loss faced by society and businesses as a result of actions taken by government or private actors such as protesters, terrorists and activists.
 • Event Extraction
 
 Identification of real world events such as protests, suicide attacks and insurgency, which can be delineated in space and time.
  • 6. Event Extraction • Problem statement • Recognise 10+ event types from unstructured text • Event information augmentation (geo, date) • Event aggregation (group together mentions of same event) • Two approaches • Natural language processing (NLP) based pattern matching • Machine learning (ML) based bag of words classifier
  • 7. Date Type Lat Lon 04/11/14 Crme N 11° 5' 26'' E 11° 12' 56'' Event Extraction
  • 9.
  • 10. Stream Processing • Problem statement • Billions of sentences per day in real time • Historical archives (10+ years) • Context • Micro-services (web crawling, social media crawling, filtering, geo tagging, event extraction, entity extraction, translation, event persisting)
  • 11. Apache Kafka • Characteristics • Fault tolerant distributed message log • Publish/subscribe semantics • Can extent to queue and workers semantics • Abstractions • Topic • Consumer • Producer
  • 12. Apache Kafka + Storm • Characteristics • Version controlled processing graph (Storm topology) • Horizontal scaling within Storm cluster (good resource utilisation) • Streamparse library for integration with Python • Issues • Harder to debug than standalone micro-services
  • 13. 9 June Isis seize control of Mosul 1 June ISIL 'kills 102-year-old man' Event Correlation Analysis
  • 14. Event Detection during 
 2013 Ukraine Crisis The Cytora platform identified unrest in the East of Ukraine weeks before mainstream media and other providers.
  • 15. Conclusions • Events constitute a lens to observe the real world • NLP / ML offer viable approaches for event extraction • Apache Kafka + Storm enable event extraction at scale (It would take a human 5 years to analyse all the documents the Cytora system processes in a day.)
  • 16. Senior Backend 
 Engineer Full-time
 Skills: Python Distributed Systems Machine Learning Full-stack Engineer Full-time
 Skills: Python JavaScript HTML/CSS Jack Palfrey Location: 113 Shoreditch High Street Dev-ops Engineer Full-time
 Skills: Fabric, Asible or Chef PostgreSQL/ElasticSearch Monitoring / log shipping UNIX administration Forward Deployed
 Engineer Full-time
 Skills: Python Project management