Too long; didn't read.

Sakura, Liza, Nicole

TL;DR is a text summarization tool to help people understand news articles without having to read the entire article. It provides a text summarization feature, which condenses the article into the most important sentences. The length of the summary can be specified by the user. The keyword detection feature lists the common people, places, organizations, and events mentioned in the article. The topic analysis feature lists the adjectives that the author uses to describe each keyword and entity, to help the user get a contextual understanding of each entity. In addition, it lists topics related to the article for further reading.

It’s a well-known fact that millennials like to skim articles. They don’t have the luxury of sitting down to read dozens of articles at a time and because news is released every second of the day, it is problematic. If people aren’t able to keep up with the news, they will be uniformed and lack the ability to make an educated decision.

We realized that a tool needed to be created that would assist people in staying in the loop and we decided that the solution was a text summarization tool. Our group created a website where you could input an article and a summarization of it would be outputted. The program uses a scoring system based on common words in the article and it returns the highest scoring sentences as well as various entities with different characteristics. We hope the tool we created will assist in enlightening millennials on world happenings without having it consume their lives.

One technical problem we faced was trying to upload our Python scripts to our webpage. At first we tried to use Brython allowed people to do just that but the specific API that we were using, SpaCy, was not compatible with this program. Ultimately we switched over to Django and then we were able to successfully embed our Python programs in our webpage.

This project was made by Girls Who Code Summer Immersion Program students at Twitter (San Francisco).