Skip to content
/ fake-fews Public

Candidate solution for Facebook's fake news problem using machine learning and crowd-sourcing. Takes form of a Chrome extension. Developed in under 24 hours at 2017 Crimson Code hackathon at Washington State University.

Notifications You must be signed in to change notification settings

argx/fake-fews

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

46 Commits
 
 
 
 
 
 
 
 

Repository files navigation

FakeFews

Facebook Fake News Classifier! (Currently experiencing 95% testing accuracy using k-fold cross validation)

Summary

Candidate solution for Facebook's fake news problem using machine learning and crowd-sourcing. Takes form of a Chrome extension. Developed in under 24 hours at 2017 Crimson Code hackathon at Washington State University.

Some notes:

  • Python secure server (with classifier and training data) lies in ./server
  • Chrome extension lies in ./client
  • Server, along with training data, is currently stored locally. Plans are to host these on external server soon.
  • Chrome extension is not yet available on Chrome App Store - this is in the works!

Example

Here's an example classification of fake news, as would appear in your Facebook feed:


Contributions

This was a great and challenging project, and we plan on taking this further. Of course, this couldn't have been completed without the rest of team SlickBits:

These guys have talent and persistence.


This work is under a Non-commercial Creative Commons license under the group SlickBits. If you use any part of this code, please add attribution to our team.

License: CC BY-NC 4.0

About

Candidate solution for Facebook's fake news problem using machine learning and crowd-sourcing. Takes form of a Chrome extension. Developed in under 24 hours at 2017 Crimson Code hackathon at Washington State University.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published