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Core functionality of COAST

Project description Documentation Status

COAST_CORE is a tool designed for aiding the credibility assessment of online articles. It is a collection of modules that are useful for assessing various aspects of credibility.


COAST_CORE is made up of several modules for:


The tool is built in Python 3 and tested in versions 3.5 and 3.6.

There are two methods of named entity detection included as part of COAST_CORE. For running the Stanford named entity detection, you will need Java installed.


To install COAST_CORE, run this command in your terminal:

$ pip install coast_core

This is the preferred method to install COAST_CORE, as it will always install the most recent stable release.

If you don’t have pip installed, this Python installation guide can guide you through the process.

To install from source, visit our documentation.




April 2016

Research on credibility begins, some initial scripts are written as part of various studies

First half of 2017

Adrien Aucher joins UC as an intern and works with Ashley Williams on the first version of this tool. It is only used internally at this point.

April 2018

Yann Le Norment joins UC as an intern and works on a first public release.

May 2018

First public release!

August 2018

Version 0.1.2 released; fixing bugs and making things stable.

November 2018

Stefan Hall joins the project to work on the first release. Version 1.0.0 released.

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