Project made @ ITP - December 2021
Erasing News was created as a final for a class called Introduction to Computational Media by Allison Parrish.
- NYTimes API
Erasing News uses the New York Times API to pull today’s headlines, tags it under categories, and creates a representation of the type of news today.
In this project, I explored the type of news consumed on a daily basis and the effects of information overload. What kind of news are we consuming daily? How can we make the news more accessible? And how is the news misrepresented?
Therefore, erasing news takes the daily headlines and the metadata, grouping categories into broader categories of health, finance, politics, media, environment, religion, and more.
This piece is an artifact of the time when it was created. Reelign from the pandemic, the news was dominated with health scares and updates on the coronavirus. In the US, 2021 was a fraught politically charged time. The overcrowded news represents the information overload and consequent fatigue individuals felt. As the artifact continues to evolve, it becomes a living library of the change in mood and sentiment as depicted by one of the leading publications in the United States.
Source code. (includes use of a deprecated library - update June 17th 2023)
Inspiration + Process
The idea germinated from erasure poetry. Thinking about erasures in images and the news, led to combining into the images produced by Erasing News.
In looking at the data produced by the New York Times API, I noticed the “facets” tag. I began to track facets over a few days to see the different types of news dominating during November and December of 2021. With those assets, I plotted them and color coded them to understand the broader types of information through thematic analysis.