Data Journalism

1 of 5 teammates, Jan - March 2022

Challenge

The team was tasked with the challenge to create a set of data visualizations that communicate a dataset of timely, societal information. My teammates decided to explore the rise of anti-asian sentiments specifically in California (our location at the time) during COVID .

Skills

Technical: Data visualization (CodePen, Tableau, Excel, HTML/CSS/JAVASCRIPT), data manipulation, data cleaning/filtering.

Outcome

Team approached the task by creating a set of data visualizations (timelines, animations, graphs, etc) that told a coherent story. The AAPI community has been historically victims of injustice since the 1850s, which coincides with the influx of AAPI population in California. However, there was a rise during the COVID-19 pandemic, which can be analyzed through Twitter posts. Visualized in the shape of a funnel, there’s a plethora of personal accounts of asian hate, but a much smaller subset of news coverage and a minuscule quantity reported crimes. We then mapped the average news cycle of AAPI hate crimes and their reports from Google News, showcasing shorter, less engaged timelines. It was later calculated based off article keywords that with a quantitatively higher reported AAPI crime like the Atlanta spa shooting, the sentiments towards the AAPI population skewed negative.

Process Highlight

the team process was the most notable component of the work process. Thorough research was conducted, synthesized, and cleaned quickly and efficiently; this helped us focus on creating meaningful visuals. While I contributed to all visuals, I personally created the AAPI discrimination timeline visual. Each visual is documented below:

Project Learnings

About myself as an Designer:

  • Data is one of the most powerful design tools if communicated effectively.

  • Finding reliable, timely, and clean datasets can be a pain, especially when accessing public/government data. If I’m ever creating a large dataset myself, usability will be a top priority.

  • Learning is core to understanding. Addressing a topic like AAPI hate is a nuanced discussion that requires a high volume of understanding, and the more I learned, the more I understood. This can seem obvious, but even getting one layer deeper can go a long way.