Coriolan
Elite member
- Messages
- 216
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I saw this on the BBC and thought you should see it:
Can mapping conflict data explain, predict and prevent violence? - http://www.bbc.co.uk/news/world-42919593
"It was December 2015, and Dr Weisi Guo was having dinner and listening to the grimnews about the conflict in Syria.
Over the previous decade, Dr Guo had grown increasingly troubled by the amount of violence towards civilians. He had worked inUNHCR refugee camps in Algeria and seen the human cost at first hand.
His own expertise - as an academic specialising in communication networks and telecoms - seemed a world away. But as a physical scientist he wanted a model to helpunderstand the nature of conflict, and so a highly innovative approach began to take shape.
That night he looked at a map of where the Islamic State group was operating and noticed an overlap with locations on the old Silk Road - the route that had taken traders from China through Asia and the Middle Eastto the Mediterranean thousands of years ago.
"What I slowly started to notice was that a lotof these areas prone to repeated violence were along ancient trade routes. And I thought, 'Is there a reason to this?'"
That night he wrote an algorithm on his laptop that connected the locations of cities and towns, and mapped them against data about conflict sourced from The Global Terrorism Database and The Peace Research Institute Oslo (PRIO).
"The results were amazing," he says. His first reaction was to assume that he had mademistake, and so he tried again. The results were better. He asked a mathematician colleague to run an independent test, which generated the same answers.
Dr Guo's algorithm connected the world asmesh of towns and cities, and looked at the connections between them. In Dr Guo's graph, certain towns show up as larger circles signifying dense connections.
On a whiteboard he draws a map of connected cities, and points out that if a traveller from each city wanted to walk roundthe map they would collide 100 times more often at certain crossroads than other places.
They are the places you have to go through in order to get from one town to another andwhere there are few other routes - hence thecorrelation with the Silk Road.
What he found was that these correlated strongly with data on violence - including terrorism, war between states and gang violence. Crossroad towns and cities, it suggested, were inherently unstable.
When you think about it, big terrorist attacks in Europe consistently took place in major hubs like Paris, London, Brussels, Berlin or Barcelona.
Can mapping conflict data explain, predict and prevent violence? - http://www.bbc.co.uk/news/world-42919593
"It was December 2015, and Dr Weisi Guo was having dinner and listening to the grimnews about the conflict in Syria.
Over the previous decade, Dr Guo had grown increasingly troubled by the amount of violence towards civilians. He had worked inUNHCR refugee camps in Algeria and seen the human cost at first hand.
His own expertise - as an academic specialising in communication networks and telecoms - seemed a world away. But as a physical scientist he wanted a model to helpunderstand the nature of conflict, and so a highly innovative approach began to take shape.
That night he looked at a map of where the Islamic State group was operating and noticed an overlap with locations on the old Silk Road - the route that had taken traders from China through Asia and the Middle Eastto the Mediterranean thousands of years ago.
"What I slowly started to notice was that a lotof these areas prone to repeated violence were along ancient trade routes. And I thought, 'Is there a reason to this?'"
That night he wrote an algorithm on his laptop that connected the locations of cities and towns, and mapped them against data about conflict sourced from The Global Terrorism Database and The Peace Research Institute Oslo (PRIO).
"The results were amazing," he says. His first reaction was to assume that he had mademistake, and so he tried again. The results were better. He asked a mathematician colleague to run an independent test, which generated the same answers.
Dr Guo's algorithm connected the world asmesh of towns and cities, and looked at the connections between them. In Dr Guo's graph, certain towns show up as larger circles signifying dense connections.
On a whiteboard he draws a map of connected cities, and points out that if a traveller from each city wanted to walk roundthe map they would collide 100 times more often at certain crossroads than other places.
They are the places you have to go through in order to get from one town to another andwhere there are few other routes - hence thecorrelation with the Silk Road.
What he found was that these correlated strongly with data on violence - including terrorism, war between states and gang violence. Crossroad towns and cities, it suggested, were inherently unstable.
When you think about it, big terrorist attacks in Europe consistently took place in major hubs like Paris, London, Brussels, Berlin or Barcelona.