Terrorism Statistics

(1 comment)

There is a lot of garbage about terrorism online.

I wanted to look at things for myself so I aggregated the data from the Global Terrorism Database at the University of Maryland.

Please note that a lot of political affiliations are blurry. I encourage you to rerun the scripts with different classifications according to your liking. Consider that ecoterrorism is largely a left-wing concept but at the same time it doesn't really have anything directly to do with left-wing progressive positions. It certainly has nothing to do with the new guard of revolutionary France. Black Hebrew Israelites are very arguably right-wing and plenty of right-wing Libertarians would be anti-police.

DATE OTHER.FATALITIES ISLAMIC.FATALITIES LEFT.WING.FATALITIES RIGHT.WING.FATALITIES
2016 2 53 13 0
2015 1 25 0 18
2014 0 6 2 11
2013 15 6 1 1
2012 0 0 0 7
2011 0 0 0 0
2010 1 0 0 3
2009 0 14 0 2
2008 0 0 0 2
2007 0 0 0 0
DATE OTHER.INJURED ISLAMIC.INJURED LEFT.WING.INJURED RIGHT.WING.INJURED
2016 3 109 21 6
2015 2 24 0 25
2014 1 3 0 2
2013 151 280 1 4
2012 0 0 1 6
2011 NA 0 0 0
2010 0 0 0 17
2009 5 35 0 NA
2008 5 0 0 8
2007 0 0 0 0
DATE OTHER.INCIDENTS ISLAMIC.INCIDENTS LEFT.WING.INCIDENTS RIGHT.WING.INCIDENTS
2016 35 9 10 7
2015 20 6 1 12
2014 7 5 2 12
2013 7 4 2 7
2012 3 1 1 14
2011 9 0 0 1
2010 8 6 1 2
2009 3 3 1 2
2008 11 0 2 5
2007 2 0 4 3

Canada Statistics

DATE OTHER.INCIDENTS ISLAMIC.INCIDENTS LEFT.WING.INCIDENTS RIGHT.WING.INCIDENTS
2016 3 2 0 1
2015 4 0 1 0
2014 0 2 1 0
2013 3 0 1 0
2012 3 0 0 0
2011 0 0 0 0
2010 1 0 1 0
2009 4 0 0 0
2008 5 0 0 0
2007 0 0 0 0
DATE OTHER.INJURED ISLAMIC.INJURED LEFT.WING.INJURED RIGHT.WING.INJURED
2016 32 2 0 0
2015 2 0 0 0
2014 0 4 2 0
2013 0 0 0 0
2012 0 0 0 0
2011 0 0 0 0
2010 0 0 0 0
2009 0 0 0 0
2008 9 0 0 0
2007 0 0 0 0
DATE OTHER.FATALITIES ISLAMIC.FATALITIES LEFT.WING.FATALITIES RIGHT.WING.FATALITIES
2016 0 1 0 0
2015 0 0 0 0
2014 0 4 3 0
2013 0 0 0 0
2012 0 0 0 0
2011 0 0 0 0
2010 0 0 0 0
2009 0 0 0 0
2008 0 0 0 0
2007 0 0 0 0

Methodology

Data was copy and pasted from the Global Terrorism Database into a CSV for each country. Then a R lang script like the following was run.

## See http://www.start.umd.edu/gtd/search/Results.aspx?page=2&casualties_type=b&casualties_max=&start_yearonly=2014&end_yearonly=2016&dtp2=all&country=217&count=100&expanded=no&charttype=line&chart=overtime&ob=GTDID&od=desc#results-table
terror <- read.csv(file="terror.csv", header=TRUE, sep=",")

terror.2016 <- terror[grepl("2016-", terror$DATE, fixed = TRUE),]
terror.2015 <- terror[grepl("2015-", terror$DATE, fixed = TRUE),]
terror.2014 <- terror[grepl("2014-", terror$DATE, fixed = TRUE),]
terror.2013 <- terror[grepl("2013-", terror$DATE, fixed = TRUE),]
terror.2012 <- terror[grepl("2012-", terror$DATE, fixed = TRUE),]
terror.2011 <- terror[grepl("2011-", terror$DATE, fixed = TRUE),]
terror.2010 <- terror[grepl("2010-", terror$DATE, fixed = TRUE),]
terror.2009 <- terror[grepl("2009-", terror$DATE, fixed = TRUE),]
terror.2008 <- terror[grepl("2008-", terror$DATE, fixed = TRUE),]
terror.2007 <- terror[grepl("2007-", terror$DATE, fixed = TRUE),]

total.fatalities <- sum(terror$FATALITIES)

other <- c(
"Unknown",
"Court Reform extremists",
"Animal Liberation Front (ALF)",
"Veterans United for Non-Religious Memorials",
"Students For Insurrection"
)
islamic <- c(
"Jihadi-inspired extremists",
"Muslim extremists",
"Iraqi extremists",
"Tehrik-i-Taliban Pakistan (TTP)",
"Al-Qaida in the Arabian Peninsula (AQAP)"
)
left.wing <- c(
"Anti-White extremists",
"Anti-Police extremists",
"Black Hebrew Israelites (suspected)",
"Anti-Trump extremists",
"Anarchists",
"Pro-LGBT Rights extremists",
"The Justice Department",
"Earth Liberation Front (ELF)",
"Animal Liberation Front (ALF) (suspected)",
"Revolutionary Cells-Animal Liberation Brigade",
"Earth Liberation Front (ELF) (suspected)"
)
right.wing <- c(
"Anti-Semitic extremists",
"Anti-Muslim extremists",
"Anti-Muslim extremists (suspected)",
"White extremists (suspected)",
"White extremists",
"Citizens for Constitutional Freedom",
"Anti-Abortion extremists",
"Sovereign Citizen,White extremists",
"Anti-Sikh extremists",
"Right-wing extremists",
"Anti-Government extremists",
"Sovereign Citizen (suspected)",
"Sovereign Citizen",
"United Aryan Empire",
"Anti-Gun Control extremists",
"Anti-Government extremists (suspected)",
"Anti-Semitic extremists (suspected)",
"Neo-Nazi extremists",
"Anti-Liberal extremists",
"Anti-Abortion extremists (suspected)"
)

dates <- c("2016", "2015", "2014", "2013", "2012", "2011", "2010", "2009", "2008", "2007")

fatalities <- data.frame("DATE" = dates)
injured <- data.frame("DATE" = dates)
incidents <- data.frame("DATE" = dates)

for (ii in 1:length(dates)) {
switch (ii,
{
the.terror <- terror.2016
},
{
the.terror <- terror.2015
},
{
the.terror <- terror.2014
},
{
the.terror <- terror.2013
},
{
the.terror <- terror.2012
},
{
the.terror <- terror.2011
},
{
the.terror <- terror.2010
},
{
the.terror <- terror.2009
},
{
the.terror <- terror.2008
},
{
the.terror <- terror.2007
}
)
other.terror <- the.terror[the.terror$PERPETRATOR %in% other,]
fatalities[ii, "OTHER.FATALITIES"] <- sum(other.terror$FATALITIES)
injured[ii, "OTHER.INJURED"] <- sum(other.terror$INJURED)
incidents[ii, "OTHER.INCIDENTS"] <- nrow(other.terror)

islamic.terror <- the.terror[the.terror$PERPETRATOR %in% islamic,]
fatalities[ii, "ISLAMIC.FATALITIES"] <- sum(islamic.terror$FATALITIES)
injured[ii, "ISLAMIC.INJURED"] <- sum(islamic.terror$INJURED)
incidents[ii, "ISLAMIC.INCIDENTS"] <- nrow(islamic.terror)

left.wing.terror <- the.terror[the.terror$PERPETRATOR %in% left.wing,]
fatalities[ii, "LEFT.WING.FATALITIES"] <- sum(left.wing.terror$FATALITIES)
injured[ii, "LEFT.WING.INJURED"] <- sum(left.wing.terror$INJURED)
incidents[ii, "LEFT.WING.INCIDENTS"] <- nrow(left.wing.terror)

right.wing.terror <- the.terror[the.terror$PERPETRATOR %in% right.wing,]
fatalities[ii, "RIGHT.WING.FATALITIES"] <- sum(right.wing.terror$FATALITIES)
injured[ii, "RIGHT.WING.INJURED"] <- sum(right.wing.terror$INJURED)
incidents[ii, "RIGHT.WING.INCIDENTS"] <- nrow(right.wing.terror)
}

For Canada the following classifications were used:

other <- c(
"Unknown",
"Anti-Gentrification Front",
"Force Etudiante Critique"
)
islamic <- c(
"Jihadi-inspired extremists",
"Muslim extremists"
)
left.wing <- c(
"Animal Liberation Front (ALF)",
"Fighting For Freedom Coalition (FFFC-Ottawa)",
"Anti-Government extremists"
)
right.wing <- c(
"Anti-Muslim extremists"
)

Notes

Some of the boundaries between political affiliations are blurry. Some people might want to tweak definitions. Also there are a significant number of unknown attackers. Another interesting data source people might want to look at is http://extremism.ca/ although it only goes up to 2014. One key point that the Global Terrorism Database doesn't catch is that many Islamic militants are motivated to emigrate outside of countries they are citizens of and commit terrorism elsewhere. For example, the extremism.ca database shows that there were 91 fatalities (in total) from Canadian citizens outside of Canada.

Update: New Information

So, I got my approval to access the Tevus database here: https://tap.cast.uark.edu/ just today and did a quick tally up of terrorist events. 

Left Wing

Left Wing - Anarchism

Year Events
2004 9
2005 16
2006 13
2007 10
2008 6
2009 2
2010 5
2011 1
2013 1
2015 1

Right Wing

Right Wing Antigov

Right Wing Soveriegn Citizen

Year Event
2004 1
2005 2
2006 3
2007 6
2009 2
2010 13
2012 1
2013 3
2014 5
2015 1
2016 1

Religious - Muslim

Religious - Muslim Sunni

Religious - Muslim Shia

Year Events
2004 33
2005 3
2006 61
2007 85
2008 19
2009 77
2010 288
2011 133
2012 22
2013 68
2014 105
2015 223
2016 16

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