Political Bias Detection in News using Deep Learning

Traditional sentiment analysis typically uses abstract labels like 'positive,' 'negative,' or 'neutral.' However, for political news articles, it is crucial to capture more nuanced information that represents the specific political orientation of the content. In this paper, we categorize political bias into three labels: Left, Center, and Right to provide a more ideological understanding of the bias present in news articles. We utilize a deep learning model to classify news articles based on political ideological bias. Various methods and techniques are employed to enhance the model's efficiency and performance, ultimately improving its ability to provide a clearer, more detailed representation of the political stance in news content. This will result in a more lucid understanding of the news articles on different types of political ideological biases subtly used in writing the news articles.