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Mining for Bias

Team Members: Serena Behera (behera3), Amith Hiremath (amithph2), Riya Jain (riyaj3), Michal Juscinski (michalj2), Bryan Ge (bryanjg2), Aditya Joshi (adityaj4)

Team PM: Aileen Long (linjial2)

Background

Problem: Articles that attempt to feed you a particular narrative/contain bias.

Solution: Take an article and use sentiment analysis to output an evaluation of the bias in the article based on its content and any accompanying image(s).

  • Python (Google Colab, Jupyter Notebook, VSCode)
  • HTML
  • CSS

Building the Project

The webpage was developed on React using React Hooks and Parallax and implemented Flask.

Setting up Flask

Download Flask by running the following line of code in your Terminal:

pip install Flask

For more information on Flask installation, go to [https://flask.palletsprojects.com/en/1.1.x/installation/](https://flask.palletsprojects.com/en/1.1.x/installation/.]

Running the Project

First, open your Terminal or Command-Line and navigate to the my-app project. Then, type the following code to prepare the Flask app:

export FLASK_APP=test.py
flask run

Next, open the “my-app” project in VSCode and open a Terminal window. Type the following code to run the React app:

npm start

Usage

Paste a news article URL into the URL textbox and click on the “Start” button to receive your subjectivity score. The lower the percentage, the less bias there is in the article.

Core Features of Model

  • The ability to scrape news articles and compile a neutral version of the news
  • A bias score for an article
  • Output the web link with the lowest bias score

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