Have you ever wondered how people would feel in the moment before their death?
In Texas Death Row—an interactive data visualization explores various human emotion—each particle represents an individual inmate who were on death row in Texas prison. Upon clicking one, it shows you the information of executed inmates along with their final statements. The information can be reorganized by various filters at the top left and provides viewers with an immersive experience triggering viewer’s curiosity. By providing users with an intuitive way to collect and analyze information, viewers can play around with the data and discover unique narratives from the data at hand. The application is downloadable from this link (windows OS only).
Creating an Empathetic Data Visualization
The idea of the project started from the motivation of telling stories of the prisoners behind data. The main focuses on this project is 1) exploring a various way to process and present the data in a way people can relate themselves more deeply with the narrative found in, 2) delivering a moment to reflect on their life by putting themselves in other’s shoes. It is an experiment with data as a medium to create an empathetic interaction.
The data set used in this project was sourced from the Texas Department of Criminal Justice website, which is managed by the government of Teas. The website contains an up-to-date information on prisoners who had been executed or those currently on death row. The documents include name, age, race, hometown, date of execution, and last statement. I process the data set by running a sentiment analysis using IBM Watson Tone Analyzer. I was able to convert the last statements of executed inmates to quantitative data for each statement. The Tone Analyzer identifies sentences with stronger tones in context or sorted by score. IBM Watson Tone analyzer returns a likelihood of each emotion found in each text. Extracted emotion data set are merged with the list of inmates The final data is rearranged for the program to handle it in the most efficient way.
I came up with an image of a rotating wheel consist of particles which I think is suitable for visualizing massive data points. Each particle has one of five colors: red, blue, green, yellow, purple, and grey. Each color represents a dominant emotion that are found from individual final statement. The size and opacity of particles represent intensity of the emotion.
Interactivity is one of the most important parts of this visualization. It not only helps viewers to read the data more effectively, but also allows users to immerse themselves in the story behind those data. I designed the project to allow users to explore data set through filters. Each combination of filters generates unique data visualizations.