Violence, Sectarianism
and Patterns of
Communication in Yemen
MURI Presentation
Christia, Dahleh, Jadbabaei, Leskovec,
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Question
• What is the effect of violence on a society’s structure of
communication?
• Examine effects of exogenous violent shocks indigenous
violent events on patterns of communication in Yemen.
• Specifically, look at the effects of drone strikes and Arab
spring protests on cell phone communication.
• For the Arab spring protests we can also look at the effect of
communications on protest activity
• Builds on recent work that uses CDRs to examine the
change in social networks of communication after rapidly
evolving and transient events such as emergencies.
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Patterns of Communication
• 3 years of call records metadata from January 2010-January
2013
• Anonymized data on:
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•
•
•
•
Caller
Location
Date and time of call
Duration of call
Call or sms
• Increase in cell phone penetration from roughly 40% to over
70% in that time span.
• No 3G in Yemen and only 15% internet penetration.
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Users and Calls per Day
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Data on Violent Incidents
Exogenous: 73 Drone Strikes
Indigenous: 432 Arab Spring Events
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11
6
1
Jan-Dec 2010
Jan-Dec 2011
Jan-Dec 2012
Jan-13
5
Drone Strikes Jan 20
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Bulk of Strikes in 20
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Analytical Approach
• Address our question by looking at:
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•
•
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•
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Volume of calls
Timing of calls
Direction of calls (incoming vs. outgoing)
Duration of calls
Mobility effect in calls
Individual level network connections.
• Also look at how violent events compare to other important
but largely peaceful events
• Look at whether phone data reveals the country’s divisions.
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Day of Week Call Patterns
Friday Prayer
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First Strike: 24 May 2010
Tower 2: 3.7
miles from
strike
Tower 1: 0.6
Miles from
strike
Ma’rib: Approximately 17,000 people, 2,200 unique numbers
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Ma’rib Strike May 24th 2010
Entire Country
Tower 0.6 miles from strike
Spike
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Direction of Call Traffic May 24th 2010
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Duration vs. Time
• Plotted Average Call Duration vs. Time of day
• Slight decrease in average call duration right after strike
• i.e. people make shorter phone calls
• This decrease only happens in outgoing calls
Average duration is
a lot longer at night
than during the day
(2 mins vs. ~5 mins)
After drone strike,
average duration is
much shorter than the
“average” at that time
of day
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Duration After Strike
• Calls in the 1 hour after the strike happened
• Red – “normal” night, long-tailed, Blue – May 24th, narrow-bands
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Al-Awlaki Strike
• September 30th, 2011 in the middle of nowhere
• He had “pulled over for breakfast” on side of road
Drone
Strike
37 Miles
Away
34 Miles
Away
Nothing for 30
miles here…
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Al-Awlaki Strike
• No spike at all at the 2 nearest towers
Note the standard
pattern on Friday,
even on the day
Awlaki was killed
The day of the
strike was quite
calm
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Another Strike - Lawdar
• Lawdar – 1/30/2012, Killed 15 militants
• Arab Spring happening in the same time period
Just one set
of towers in
town, 0.3
miles away
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Lawdar
• Large differences in total volume for Mondays over just a 2 month
interval (not monotonically increasing each week)
• To zero out influence of strike, normalized call volume
• Probably not a good idea in the long run, but helps here
• Important next step: Distinguish drone strikes in war-torn vs. peaceful areas
Power
outage
The “outlier”
on January
30th
A jump in calls around
11:00PM, consistent with
other “spikes”
(incoming/outgoing/within
tower/duration), but not
too large comparatively...
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Measurable Strikes
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•
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73 are between Jan 2010 and Jan 2013
10 in Zinjibar, where antennas were shut off as under Al Qaeda control; for 1 no location data
Of the remaining 62:
33 strikes less than 2.5 miles from a tower, 41 less than 5 miles, 51 less than 10 miles
Remaining 11 greater than 10 miles (unlikely to see a spike)
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Anecdotal (so far) findings
• Based on the handful of cases we have looked at:
• Drone strike effect on communications appears very
localized and quite contained in terms of time.
• Hits appear to happen at night which probably helps
with keeping the effect more contained.
• Strike seems to have shortening effect in terms of
duration of outgoing calls.
• There also appears to be an increase in incoming
calls.
• But all this very tentative as based only on a few
cases.
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Next Steps
• See if we could predict the time of a strike by a spike/deviation from the
standard level for that day of the week for the towers near the strike for
all 62 strikes in the dataset.
• Look for “missing strikes.”
• Quantify local spikes for other activities such as religious holidays,
celebrations, other cultural events, and leverage them in connection to
violent events.
• Look at whether tower outages are in any consistent way linked to
drone strikes.
• Look at individual level data (who called whom).
• Do the same analysis for Arab Spring events. There, also look at whether
there is any network behavior that seems to affect events.
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