News bias classifier

This is a page to track issues related to the news bias classifier project on this repo: www.github.com/N2ITN/newscraper The project is part of D4D but is hosted in the original repo location, to view the code, clone the project, and for more documentation visit the repo. The webapp is accessible to the public at www.areyoufakenews.com

Project leads

Lead: Slack - "@Zach Estela", Github - @N2ITN

Project Description

In an era of misinformation and polarized politics, it's important for internet users to have context for what's on their screen. This microservice uses natural language processing and deep learning to analyze patterns of bias on any news website in real time. Each time a url is submitted, dozens of the most recent articles are collected and analyzed for a variety of factors, from political bias to journalistic accuracy. The results are displayed in charts for the user.

Getting Started

This project has existed for a few months, but is new to D4D (as of Jan 2018). Issues will be posted with required skills and estimated difficulty/time.

If you haven't already, read this first. Then:

Things you should know about

• "First-timers" are welcome! Whether you're trying to learn data science, hone your coding skills, or get started collaborating over the web, we're happy to help. (Sidenote: with respect to Git and GitHub specifically, our github-playground repo and the #github-help Slack channel are good places to start.)

• We've got (GitHub) Issues. Ready to dive in and do some good? Check out our issues board. Issues are how we officially keep track of the work we're doing, what we've done, and what we'd like to do next. If you'd like to work on something, comment on the issue and/or ping a lead on Slack so we can make assignments.

  You can identify different issue types by their tags. If you're new to either Github or data science, pay special attention to:

  • first-pr: smaller issues to cut your teeth on as a first-time contributor
  • beginner-friendly: issues suitable for those with less experience or in need of mentorship
• We believe good code is reviewed code. All commits to this repository are approved by project maintainers and/or leads (listed above). The goal here is not to criticize or judge your abilities! Rather, sharing insights and achievements this way ensures that we all continue to learn and grow. Code reviews help us continually refine the project's scope and direction, as well as encourage the discussion we need for it to thrive.
• This README belongs to everyone. If we've missed some crucial information or left anything unclear, edit this document and submit a pull request. We welcome the feedback! Up-to-date documentation is critical to what we do, and changes like this are a great way to make your first contribution to the project.

Currently utilized skills

Take a look at this list to get an idea of the tools and knowledge we're leveraging. If you're good with any of these, or if you'd like to get better at them, this might be a good project to get involved with!

• Python 3 (scripting, analysis, web scraping, MongoDB interface, deep learning, visualization)
• Linux/Bash (scripting, server management)
• Flask/Jinja 2/HTML templating (front end stack)
• JavaScript (front end, and soon for interactive data visualization)
• AWS EC2 & AWS Lambda (backend infrastructure)
• MongoDB (NoSQL database)
• TensorFlow/Keras (deep learning)