Inspiration The increasing spread of fake news and misinformation has led to a growing need for tools that can help people determine the political bias of an article. With Political Bias Detector, we aim to provide a simple and effective solution to this problem.
What it does Political Bias Detector is a machine learning project that analyzes the text of an article and compares it to a database of keywords and their political affiliations. The result is a clear determination of whether the article is left-wing or right-wing.
How we built it We used natural language processing techniques to extract the text from an article URL, preprocess the text, and compare it to a database of keywords and their political affiliations. The database of keywords and affiliations was created using a CSV file. The algorithm then uses a simple counting approach to determine the political leaning of the article based on the presence and frequency of keywords.
Challenges we ran into One of the biggest challenges was preprocessing the text to remove irrelevant information and improve the accuracy of our model. Another challenge was finding a reliable source of keywords and their political affiliations.
Accomplishments that we're proud of We're proud of successfully creating a model that can accurately classify articles based on their political bias. This is a complex problem and we're proud of the results we were able to achieve.
What we learned We learned about the importance of preprocessing text data and the challenges that come with it. We also learned about the different techniques and algorithms used in natural language processing.
What's next for Political Bias Detector In the future, we hope to improve the accuracy of our model by using more advanced techniques and algorithms. We also hope to make the project more accessible to a wider audience by creating a user-friendly web application.
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