World Suicide Rates: A Visualization

This is a visualization made for an elective course held at Bucknell University led by Professor Evan Peck. In this assignment, we explore visualization strategies used to convey information and to persuade.

5 min readMar 2, 2019

Our Data Set: Suicide Statistics

Our team found a compiled dataset on Kaggle which holds information concerning suicide numbers across the world from the period of 1985 to 2015. Furthermore, the compiled dataset contains information on likely signals correlated to increased suicide rates among different countries and across different socio-economic levels. Specific categories of information include the sex, age, and the gross domestic product (GDP) of the country for the year of each suicide.

Click Here to Link to Our Visualization of World Suicide Rates…

Project Goal

Our research in suicide rates underlies our attempt to uncover reasons for suicide which can hopefully provide for better methods for suicide prevention by creating one persuasive visualization and three supplementary clear communication visualizations.

Persuasion Piece

For our persuasion visualization, we used a world-view geospatial graph to show the relationship between suicide rates among all different nations according to their development class. We describe the development level of a country as being delineated by the per capita GDP of $25,000. If a country has at least a per capita GDP of $25,000, it is classified as a developed country. Otherwise, the country is classified as a developing country.

It can be seen from our persuasion graph that countries are generally moving from a heavily red coloration towards a lighter red coloration. This can be explained by the general trend for countries to improve their economies over time.

In addition, when comparing the color value between developing and developed countries, we find that developed countries tend to have a lower color density, translating to a lower suicide rate, than that of the developing countries. This again shows that a disparity of wealth may play some part in influencing suicide rates across the world.

Figure 1: Comparing global suicide rates between developing countries on the left and developed countries on the right.

Our Process

While creating our graphs, we drew inspiration from many different sources which could be found on the internet. One of the many things we searched for inspiration was graphs which depicted either death or population size. More specifically for death, we focused on graphs which depicted the casualties sustained by countries during wars.

Geospatial Graph — Persuasion Visualization

World War II is a war which involved the loss of a great number of human lives. As a result, visualization of this period is especially vivid and was used as a resource to help us brainstorm ways we could visualize and communicate our suicide statistics. While looking online for WWII graphs, we found a geospatial graph which caught our eye. This graph categorized each major power of WWII as either an allied or axis power communicated by the color of its respective circle and made the number of military deaths that occurred in each power to scale in terms of the size of the power’s respective circle. We had hoped to incorporate something similar in the design of our graphs.

Similar to our World War II inspiration graph, our ultimate persuasion visualization that features the number of suicides per 100K population in multiple countries from 1985 to 2015 is a world-view geospatial graph and categorizes countries as either developed or developing. The goal of this graph is to persuasively communicate how suicides in developing countries number higher than suicides in developed countries.

Figure 2: The left side is our inspiration, while the right side is our rough draft of our future design.

Comparison Bar Graph — Communication Visualization

Our inspiration graph uses the bar graph comparison design to succinctly display information on multiple age groups between the male and female populations in Japan in 2015. We implemented this design in creating our graph which represents the number of suicides among different age groups separated between genders (male and female) in the USA. The goal of this graph is to clearly communicate how suicides differ among male/female populations and among different age groups.

Figure 3: The left side is our inspiration, while the right side is our rough draft of our future design.

Timeline — Communication Visualization

The timeline inspiration we found communicates the idea that specific events in history have large effects on the percentage of the US population in active US military duty. We believed that this graph’s design would show a more qualitative understanding of our information, rather than a purely quantitative one. Therefore, we implemented this design in our visualization by creating a timeline of Japan’s historical events from 1985 to 2015 while also indicating the Japanese suicide count for each year via a timeline to show how these events had an effect on the suicide count in Japan.

Figure 4: The left side is our inspiration, while the right side is our rough draft of our future design

User Experience Research

After we have finished our first few iterations, we also drew inspirations from our users. We conducted user research with 5 participants who looked at and interacted with our visualization. Then they told us what they thought of our graphs and interactions. From these feedbacks, which are mostly fine-tuning the details of our visualizations, we summarized their feedback and made changes accordingly.

Figure 5: User feedback was collected in the Bertrand Library at Bucknell University

Conclusion

From our dataset, we found very clear trends, such as high suicide rates among males in comparison to females in the USA. We also found that most suicides often occur among populations ranging in age from 35–54 years of age in the USA. Furthermore, there tends to be an inverse relationship between suicide rates and the GDP of each country such that when GDP grows, suicide rates tend to drop.