Terrorism has become a major concern over the years, making protecting individuals from violence and criminal activities a priority worldwide. The goal of this project is to analyze the dataset and bring out conclusions and try to recommend measures that can decrease/diminish terrorist activities.
The dataset is a compilation of terrorist activities over the globe. The timeline of the dataset is from the year 1970 to 2017. It includes systematic data on domestic as well as international terrorist happenings that have occurred over the years. There are around 180,000 observations in the dataset. The dataset is rich in variables, around 100 variables.
VARIABLES: >100 variables on location, tactics, perpetrators, targets, and outcomes
The dataset contains 181,692 rows and there are more than 100 variables.
The dataset had three columns for year, month and date. With the help of =DATE function, a new column was created which had all three in one.
- MISSING VALUES
Working on data with so many missing values was not efficient and therefore it required a lot of cleaning. The means adopted to clean the data was to filter out all the rows and columns which had missing values: blank and “NA” with a proportion of more than 50%. Excel was used to do this. This resulted in a comparatively cleaner dataset with a lot of columns deleted.
Microsoft Excel was used to clean and refine the dataset. The dataset was then used in Tableau Public to develop visualizations and analyze them further.
Visualizations and Analysis
Visualization 1: Attack Summaries
A world map that aims at giving a summary of each individual attack. The summary covers 4 categories –
- Country Name
- Attack Type
- Identified Terrorist Group
- Brief Summary of Attack
Visualization 2: Year-wise attacks
A line graph to see the increase and decrease in global terrorism over the years.
Over the last decade, terrorism has drastically increased. However, as the line graph suggests, the numbers have decreased since 2014.
Visualization 3: Region-wise terrorism trend
A line graph to see which regions have witnessed a higher rate of terrorism over the years. In order to make the visualization less confusing for the users, only the 2 regions that have experienced a hike in terrorist activities were made red, the rest is a neutral grey.
It is seen that the Middle East and North Africa have been affected by terrorist activities more than any region and measures need to be taken in these regions in order to diminish it.
Visualization 4: Type of attacks
The category of bombing surpasses every other category of attacking means. There have been nearly 90,000 cases of the bombing. The second to bombing is armed assault which is approx. 45,000.
Visualization 5: Terrorist Organisations
To understand which are the most terrifying terrorist groups based on the number of people killed.
The recent attacks by ISIL, which were highly motivated and more sophisticated in terms of execution, resulted in higher mortality counts. Taliban was formed in the 1970’s and has claimed a lot of lives since then. Afghanistan is still actively fighting against the Taliban.
Visualization 6: 10 most attacked countries
It can be seen that Iraq is the most prone to terrorism followed by Pakistan and Afghanistan.
Visualization 7: Target type
To see and observe the target types behind terrorist attacks.
To ensure that the visualizations are easy to understand and use, I conducted a task completion and interview with 2 users. Both the participants found it easy to use and find information from the dashboard. A couple of pointers from the user test included –
- Color coding the locations on the map
- Changing the region-wise graph to something easier and highlighting the 2 main observations.
- Using a consistent color palette for the dashboard.
- Making a list of terrorist organizations would be a helpful addition.
A deep red and black color palette was used to depict fear, anger, and violence.
Reflection and future direction
Handling this dataset was quite a task, in terms of cleaning it, figuring out what to focus on, from a huge list of variables but then it was very interesting and challenging. Now that I have performed analysis on this dataset and created visualizations, it can be used on similar datasets to find out interesting information and conclusions. An extended version of this analysis could be used by organizations which try to fight terrorism globally.
Although the dataset used was fairly accurate, a lot of the data for earlier years may or may not have been recorded. I would like to refine this project based on the conducted Ux research. I would also want to add to it by carrying out a comparative analysis of criminal activities in particular areas and regions. Further, I would like to study different terrorist groups and their motives. Overall, this assignment helped me improve my skills and made me very comfortable using tableau.