Detecting Bias in Climate Reporting in English and German Language News Media

This Omdena Local Chapter Challenge runs for 6 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world.

You will work on solving a local problem, initiated by the Cologne, Germany Chapter.

The problem

We will develop a user-friendly bias-rating system to rate the accuracy of climate-related reports in comparison with established facts in climate science and related areas. For this we will analyze English- and German-language news media using Natural Language Processing.

The goals

The overarching goals of the system would be:

• Check the content of written articles against credible sources of climate science.
• Calculate a biased score for each article.
• Highlight scientifically inaccurate assertions in written articles.
• Provide a credible source to the user in an easy-to-access format (e.g. through a Streamlit dashboard/app/website).

A credible source of information can be in any form, from satellite imagery of areas affected by climate-related incidents to graphical information in scientific papers and reports. Therefore, this object will also include elements of image recognition, data analysis, and data visualization.

Why join? The uniqueness of Omdena Local Chapter Challenges

Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level.

A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.

Read more on how Omdena´s Local Chapters work