-
-
Search for a specific topic
-
Results page example 1
-
Results page example 2
-
Chrome extension example 1
-
Chrome extension example 2
Inspiration
After seeing how news about the pandemic and election differed so much these last few months, we knew we wanted to work on a project focused on this large variation in information. We initially considered ideas that would help identify which news articles were the most accurate, then realized we could instead build a project to help reduce the increasing polarization caused by these divides. Voila Project Neutral! A project built to break our bubbles and bring other viewpoints into our feeds.
What it does
Project Neutral is a webapp and related Chrome extension that suggests a balanced set of news articles across a spectrum of political viewpoints. When given a topic, our webpage provides articles from left-leaning, center, and right-leaning news sources. The Chrome extension works with individual news articles, providing information about their political bias and then suggesting similar articles from different viewpoints.
How we built it
The Project Neutral website was built in React. The Chrome extension was built in javascript. Both components of the project use the Google Custom Search API to source articles from a spectrum of political viewpoints.
Challenges we ran into
Figuring out which API to use, setting up React and resolving conflicts across different local environments.
Accomplishments that we're proud of
We were able to build a multi-part project in a short-time span!
What we learned
How to develop a Chrome extension! We also learnt more about building a multi-part project and that the Google Custom Search API is really cool :)
What's next for Project Neutral
Our next step for Project Neutral is to create an image misclassification tool, which determines whether the images used in a news article have been used out of context or not. We also want to provide more information about the news articles with the extension, such as news source reliability or semantic analysis of the article's text.
Log in or sign up for Devpost to join the conversation.