Texas Death Row

Texas Death Row


Have you ever wondered how people would feel in the moment before their death?


Each particle represents an individual inmate. Upon clicking one, it will show 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 narratives of their own from the data at hand.


Design Process

Data Collection

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The data set used in this project was sourced from the Texas Department of Criminal Justice. It is managed by Texas government. 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 ran a sentiment analysis using IBM Watson Tone Analyzer to extract emotional data for each statement. The Tone Analyzer identifies sentences with stronger tones in context or sorted by score. Highlighted sentences indicate the likelihood of a tone present.

Data Merge + Refinement

Extracted emotion datasets are merged with the list of inmates on death row and the final dataset is translated in a way the program can handle most efficiently. If specific datasets are not included but remain essential to create a program, then having them in the final sheet would be more efficient to reduce build-time and optimization in code.



I came up with an image of a rotating wheel consist of particles which are suitable to visualize massive data points. I colored each particles with one of five colors: red, blue, green, yellow, purple, and grey. Each color represents a dominant emotion found from individual final statements. The size and opacity of particles represent intensity of the emotion. 


Interactivity is one of the most important parts of Texas Death Row It helps viewers being able to not just “see” the data, but makes them analyze it faster and more effective. Also it allows users to immerse themselves in the story behind those numbers. I designed the project to allow users to look at different parts of the dataset through filters with each combination generating its own unique visuals.




Key Screenshots