Group17 proposal

Proposal

Poster

Application

Research Paper

Overview

The growing menace of Terrorism has been a major issue in many parts of the world. An attack of terrorism in a country impacts its economy and the livelihood of the people impacted by the attack tremendously. The global death toll from terrorism over the past decade has increased by almost 5 times. There has been an average of over 21,000 people getting killed every year worldwide because of terrorism. Because of the growing concern of terrorism across the world in the past decade, we decided to choose this topic for the project. The scope of this project is to understand how the landscape of terrorism and various terrorist activities varies across the world and has changed over time.

Project Objectives

Although Global Terrorism Database (GTD) has made the data regarding all terrorist activities readily available, it is not in a form whereby different insights can be drawn in an interactive and user friendly manner. This project aims at delivering an R shiny app that takes into considerations various factors, such as, location, number of fatalities, attack type, weapon type, perpetuator's group name etc. The detailed description of these variables are shown in the Section:Data Description. Apart from that, a spatial analysis will be performed which would focus on the fatalities in different regions at different periods of time. The major incidents would then be delved deep into and linked to economic factors to assess the impact and core reason of the terrorists attacks.

The app is going to include a section on exploratory data analysis wherein the relationship of terrorism can be linked to various factors attributing to it. This will also include a time series analysis to look at the evolution of terrorism over the years. The next section would be the spatial temporal analysis would highlight the different regions where terrorism takes place on a very large scale and then these observations are going to be linked to the economic condition of the country.

Data Description

The database used for this project is derived from Global Terrorism Database (GTD) handled by the University of Maryland. The database is very comprehensive and includes the repository of terrorist activities starting from 1970 to 2015. For the purposes of this project, the dataset has been filtered to the years 2012 to 2015. Some of the important variables that have been taken into account for this analysis is as mentioned below:

Data Fields	Description	Example	Datatype
GTD ID	Incidents from the GTD follow a 12‐digit Event ID system, wherein first 8 numbers are for the date recorded and last 4 numbers for sequential case number for the given day (0001, 0002 etc).	199307250001	Numeric
iyear, imonth, iday	These fields contain the dates and hence will be merged to get the date field.	2011-02-03	Numeric
country	This field identifies the country or location where the incident occurred.	Afghanistan	Categorical
region	This field identifies the region in which the incident occurred.	North America	Categorical
latitude	This field records the latitude.	30.209423	Numeric
longitude	This field records the longitude.	67.018009	Numeric
attacktype1	This field captures the general method of attack and often reflects the broad class of tactics used.	Assassination	Categorical
weaptype1	This field records the general type of weapon used in the incident.	Biological	Categorical
targtype1	The target/victim type field captures the general type of target/victim.	Business	Categorical
gname	This field contains the name of the group that carried out the attack.	Al-Shabaab	Text variable
nkill	This field stores the number of total confirmed fatalities for the incident.	4	Numeric

Software Tools

• RStudio: https://rstudio.com/

Proposed R Packages

Packages	Purpose
plotly()	To help with creating visuals for exploratory analysis
ggplot2()	To create elegant data visualizations using grammar of graphics
trelliscope()	To create interactive trelliscope displays
tidyverse()	To do data manipulation and exploration with dplyr() etc
gganimate()	To create plots with animation
leaflet()	To create maps within the application
spatstat()	To analyse spatial data
ads()	To analyse geographical data for spatial point pattern analysis
GeoXB()	To create interactive spatial exploratory data analysis
Shiny()	To create interactive web application for the final product

Team Members

• Oishee Bhattacharyya
• Jaideep Ballani
• Denise Adele Chua Hui Shan