/NewsLens

Project NewsLens analyzes sentiment polarity from various news sources across topics based on past articles. This aggregated polarity highlights potential bias on specific topics. Users can explore articles, view sentiment, and receive alternative perspectives to form a more comprehensive opinion.

Primary LanguageJupyter Notebook

NewsLens

Data Driven approach for analyzing news article polarization