In an era of increasing political polarization, the language used by news media has become a crucial area of investigation. This study investigates the relationship between political bias and language usage in news articles, focusing on the use of emotional, moral, intergroup language, and sentiment. By analyzing a comprehensive dataset of 2,510,592 news articles from 234 publishers spanning the years 2010 to 2022, I seek to shed light on the linguistic strategies used by media outlets to influence public perception and opinion. My approach combines a novel Transformer-Dictionary Hybrid method for identifying emotional, moral, and intergroup content with sentiment analysis using the VADER tool. The study addresses two key research questions: 1) How does the usage of emotional, moral, and intergroup language differ among news publishers with different political biases? 2) Do news outlets employ this language differently during election years compared to non-election years? ANOVA and mixed linear model analyses reveal significant differences in the usage of emotional, moral, intergroup language, and sentiment across publishers with different political biases. Liberal publishers tend to use more emotional and moral language compared to left-leaning and neutral publishers. Intergroup language usage is significantly lower among neutral publishers compared to liberal ones. Sentiment analysis shows that conservative publishers express a more negative sentiment compared to liberal publishers. A two-way ANOVA examining the effect of election years shows a significant interaction between language dimensions and election cycle. Mixed linear model analyses reveal a decrease in intergroup language usage and a slight decrease in positive sentiment during election years. The findings contribute to our understanding of how political bias and electoral context influence the linguistic choices in news media. The results suggest that partisan outlets strategically employ language to engage and potentially polarize their audience, while adapting to the heightened political climate of election years. These insights shed light on the complex interplay between language, media bias, and political polarization, underlining the importance of media literacy in navigating the contemporary media landscape.