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Training a classifier on Black news headlines to streamline positive, relevant news

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Blews Not Blues

Using Natural Language Processing to classify sentiment and category of Black News

Highlights

Collect 3000 News headlines from newsapi

Process text and build a classifier using NLP to predict sentiment of news headlines

It is no secret that the relationship between Black Americans and the news industry is marred by misrepresentation. Black American news consumption is also unique in that Television is a primary source of news [1] and the majority of African-Americans prefer to read print versus digital news [2]

Streamlining access to positive Black news can be one way to increase positive representation and reach an untapped demographic in the digital news market space.

The purpose of this project is to use Machine Learning to take as input, an article headline, and predict the category and sentiment of Black news articles. The web application can be found [here] and further details about the project can be viewed [here]

In this repository are the following:

  • Notebook used to collect news headlines
  • Associated labeled dataset
  • Notebook for preprocessing and using NLP to classify article headlines
  • Resulting pipelines

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Training a classifier on Black news headlines to streamline positive, relevant news

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