Explore Global Terrorist Attack
The Gloabl Terrorism database (GDS) is an open-source database including information on terrorist attacks around the world from 1970 through 2015. The dataset I am using contains more than 150,000 terrorism attacks worldwide from 1970 to 2015 except 1993.
## [1] 156772 137## 'data.frame': 156772 obs. of 137 variables:
## $ eventid : num 1.97e+11 1.97e+11 1.97e+11 1.97e+11 1.97e+11 ...
## $ iyear : int 1970 1970 1970 1970 1970 1970 1970 1970 1970 1970 ...
## $ imonth : int 0 0 1 1 1 1 1 1 1 1 ...
## $ iday : int 0 0 0 0 0 1 2 2 2 3 ...
## $ approxdate : chr "" "" "" "" ...
## $ extended : int 0 0 0 0 0 0 0 0 0 0 ...
## $ resolution : chr "" "" "" "" ...
## $ country : int 58 130 160 78 101 217 218 217 217 217 ...
## $ country_txt : chr "Dominican Republic" "Mexico" "Philippines" "Greece" ...
## $ region : int 2 1 5 8 4 1 3 1 1 1 ...
## $ region_txt : chr "Central America & Caribbean" "North America" "Southeast Asia" "Western Europe" ...
## $ provstate : chr "" "" "Tarlac" "Attica" ...
## $ city : chr "Santo Domingo" "Mexico city" "Unknown" "Athens" ...
## $ latitude : num 18.5 19.4 15.5 38 33.6 ...
## $ longitude : num -70 -99.1 120.6 23.7 130.4 ...
## $ specificity : int 1 1 4 1 1 1 1 1 1 1 ...
## $ vicinity : int 0 0 0 0 0 0 0 0 0 0 ...
## $ location : chr "" "" "" "" ...
## $ summary : chr "" "" "" "" ...
## $ crit1 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ crit2 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ crit3 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ doubtterr : int 0 0 0 0 -9 0 0 1 0 0 ...
## $ alternative : int NA NA NA NA NA NA NA 2 NA NA ...
## $ alternative_txt : chr "." "." "." "." ...
## $ multiple : int 0 0 0 0 0 0 0 0 0 0 ...
## $ success : int 1 1 1 1 1 1 0 1 1 1 ...
## $ suicide : int 0 0 0 0 0 0 0 0 0 0 ...
## $ attacktype1 : int 1 6 1 3 7 2 1 3 7 7 ...
## $ attacktype1_txt : chr "Assassination" "Hostage Taking (Kidnapping)" "Assassination" "Bombing/Explosion" ...
## $ attacktype2 : int NA NA NA NA NA NA NA NA NA NA ...
## $ attacktype2_txt : chr "." "." "." "." ...
## $ attacktype3 : int NA NA NA NA NA NA NA NA NA NA ...
## $ attacktype3_txt : chr "." "." "." "." ...
## $ targtype1 : int 14 7 10 7 7 3 3 21 4 2 ...
## $ targtype1_txt : chr "Private Citizens & Property" "Government (Diplomatic)" "Journalists & Media" "Government (Diplomatic)" ...
## $ targsubtype1 : int 68 45 54 46 46 22 25 107 28 21 ...
## $ targsubtype1_txt : chr "Named Civilian" "Diplomatic Personnel (outside of embassy, consulate)" "Radio Journalist/Staff/Facility" "Embassy/Consulate" ...
## $ corp1 : chr "" "Belgian Ambassador Daughter" "Voice of America" "" ...
## $ target1 : chr "Julio Guzman" "Nadine Chaval, daughter" "Employee" "U.S. Embassy" ...
## $ natlty1 : int 58 21 217 217 217 217 218 217 217 217 ...
## $ natlty1_txt : chr "Dominican Republic" "Belgium" "United States" "United States" ...
## $ targtype2 : int NA NA NA NA NA NA NA NA NA NA ...
## $ targtype2_txt : chr "." "." "." "." ...
## $ targsubtype2 : int NA NA NA NA NA NA NA NA NA NA ...
## $ targsubtype2_txt : chr "." "." "." "." ...
## $ corp2 : chr "" "" "" "" ...
## $ target2 : chr "" "" "" "" ...
## $ natlty2 : int NA NA NA NA NA NA NA NA NA NA ...
## $ natlty2_txt : chr "." "." "." "." ...
## $ targtype3 : int NA NA NA NA NA NA NA NA NA NA ...
## $ targtype3_txt : chr "." "." "." "." ...
## $ targsubtype3 : int NA NA NA NA NA NA NA NA NA NA ...
## $ targsubtype3_txt : chr "." "." "." "." ...
## $ corp3 : chr "" "" "" "" ...
## $ target3 : chr "" "" "" "" ...
## $ natlty3 : int NA NA NA NA NA NA NA NA NA NA ...
## $ natlty3_txt : chr "." "." "." "." ...
## $ gname : chr "MANO-D" "23rd of September Communist League" "Unknown" "Unknown" ...
## $ gsubname : chr "" "" "" "" ...
## $ gname2 : chr "" "" "" "" ...
## $ gsubname2 : chr "" "" "" "" ...
## $ gname3 : chr "" "" "" "" ...
## $ ingroup : int 3629 3330 -9 -9 -9 2373 623 -9 100003 100003 ...
## $ ingroup2 : int NA NA NA NA NA NA NA NA NA NA ...
## $ ingroup3 : int NA NA NA NA NA NA NA NA NA NA ...
## $ gsubname3 : chr "" "" "" "" ...
## $ motive : chr "" "" "" "" ...
## $ guncertain1 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ guncertain2 : int NA NA NA NA NA NA NA NA NA NA ...
## $ guncertain3 : int NA NA NA NA NA NA NA NA NA NA ...
## $ nperps : int NA 7 NA NA NA -99 3 -99 1 1 ...
## $ nperpcap : num NA NA NA NA NA -99 NA -99 1 1 ...
## $ claimed : int NA NA NA NA NA 0 NA 0 1 0 ...
## $ claimmode : int NA NA NA NA NA NA NA NA 1 NA ...
## $ claimmode_txt : chr "." "." "." "." ...
## $ claim2 : int NA NA NA NA NA NA NA NA NA NA ...
## $ claimmode2 : int NA NA NA NA NA NA NA NA NA NA ...
## $ claimmode2_txt : chr "." "." "." "." ...
## $ claim3 : int NA NA NA NA NA NA NA NA NA NA ...
## $ claimmode3 : int NA NA NA NA NA NA NA NA NA NA ...
## $ claimmode3_txt : chr "." "." "." "." ...
## $ compclaim : int NA NA NA NA NA NA NA NA NA NA ...
## $ weaptype1 : int 13 13 13 6 8 5 5 6 8 8 ...
## $ weaptype1_txt : chr "Unknown" "Unknown" "Unknown" "Explosives/Bombs/Dynamite" ...
## $ weapsubtype1 : int NA NA NA 16 NA 5 2 16 19 20 ...
## $ weapsubtype1_txt : chr "." "." "." "Unknown Explosive Type" ...
## $ weaptype2 : int NA NA NA NA NA NA NA NA NA NA ...
## $ weaptype2_txt : chr "." "." "." "." ...
## $ weapsubtype2 : int NA NA NA NA NA NA NA NA NA NA ...
## $ weapsubtype2_txt : chr "." "." "." "." ...
## $ weaptype3 : int NA NA NA NA NA NA NA NA NA NA ...
## $ weaptype3_txt : chr "." "." "." "." ...
## $ weapsubtype3 : int NA NA NA NA NA NA NA NA NA NA ...
## $ weapsubtype3_txt : chr "." "." "." "." ...
## $ weaptype4 : int NA NA NA NA NA NA NA NA NA NA ...
## $ weaptype4_txt : chr "." "." "." "." ...
## $ weapsubtype4 : int NA NA NA NA NA NA NA NA NA NA ...
## $ weapsubtype4_txt : chr "." "." "." "." ...
## [list output truncated]There are 137 variables in the dataset, to make it neat, I will have to do some subsetting, only keep the columns I need.
Terrorist Attack Trends
Globally, terrorist attacks have increased dramatically since 2010,
Central America was very unstable starting from the late 1970’s, it got better with time, and it has been stablized since around 1995.
Western Europe had a rough past, experienced many attacks until early 2000s.
South America had the similar pattern, was very dangerous since early 1980 until just before 2000s.
Middle East, North Africa and South Asia had a relative quiet past unitl around 1980, the terrorist attacks in those regions had a steady increase from 1980s to around 2005, and had surged dramatically since then.
A small fraction of the terrorist attacks happened in the Western countries. Most attacks were heavily concentrated geographically in Middle East, North Africa and South Asia.
Let’s look at the countries.
## # A tibble: 10 × 2
## country_txt n
## <chr> <int>
## 1 Iraq 18770
## 2 Pakistan 12768
## 3 India 9940
## 4 Afghanistan 9690
## 5 Colombia 8077
## 6 Peru 6085
## 7 Philippines 5576
## 8 El Salvador 5320
## 9 United Kingdom 4992
## 10 Turkey 3557
Iraq, Afghanistan and pakistan, India have suffered the most from terrorism. Surprisingly, United Kingdom tops the list in Europe, with almost 5000 attackes from 1970 to 2015.
Tactics and Weapons
The most commonly used attack tactic from 1970 to 2015 involved bomb and explosives, followed by armed assault.
Let’s look at the most recent year - 2015.
Casualties
To obtain more detailed death information, I went to US Department of State Website download a small dateset with casualty information.
The total number of people killed in terrorist attacks peaked in April and July 2015, and the months with the most combined deaths and injuries were June, July, August, and September, January and May had the most kidnaps.
Perpetrators
Because there were so many unknown values in the original dataset, I have to fetch data again from US Department of State Website about terrorist group information.
Along with the number of terrorist attacks they carried out, these five terrorist groups were responsible for the most terrorist attacks in 2015. Among those five groups, Islamic State of Iraq and the Levant (ISIL) is world’s deadliest terrorist organization and responsible for more than 6000 deaths in 2015.
Who are they targeting?
## # A tibble: 22 × 2
## targtype1_txt n
## <chr> <int>
## 1 Private Citizens & Property 4050
## 2 Military 2923
## 3 Police 2101
## 4 Government (General) 1145
## 5 Business 1114
## 6 Unknown 938
## 7 Religious Figures/Institutions 396
## 8 Transportation 384
## 9 Terrorists/Non-State Militia 318
## 10 Educational Institution 286
## # ... with 12 more rows
Which countries/cities were the most dangerous in 2015?
## Source: local data frame [20 x 3]
## Groups: country_txt [10]
##
## country_txt city n
## <chr> <chr> <int>
## 1 Iraq Baghdad 999
## 2 Bangladesh Dhaka 210
## 3 Afghanistan Unknown 160
## 4 Libya Benghazi 150
## 5 Pakistan Karachi 143
## 6 Yemen Aden 101
## 7 Egypt Arish 97
## 8 Yemen Sanaa 93
## 9 Somalia Mogadishu 92
## 10 Yemen Taizz 91
## 11 Yemen Unknown 91
## 12 Iraq Ramadi 87
## 13 Syria Damascus 86
## 14 Pakistan Quetta 84
## 15 Syria Aleppo 83
## 16 Afghanistan Kabul 80
## 17 Egypt Sheikh Zuweid 74
## 18 Burundi Bujumbura 73
## 19 Libya Sirte 69
## 20 Iraq Madain 65Baghdad was the most dangerous city in 2015, with approximately 1000 terrorist attacks in one year, but since when it became dangerous?
Baghdad once was a prestigious learning and cultural center. Since the coalition invasion in 2003, it has become one of the most dangerous cities on Earth.
A heatmap of terrorist attack deaths worldwide 2015
## 96 codes from your data successfully matched countries in the map
## 1 codes from your data failed to match with a country code in the map
## 147 codes from the map weren't represented in your data