Detecting News Bias With Sentence Salience and Hierarchical Structures

ABSTRACT News communication is not only a process of information transmission, but also a means of expressing and shaping ideologies. Journalists often embed different political biases in news reports on the same event, depending on their perspectives. Therefore, detecting political bias in news has become a key tool for understanding media bias and uncovering hidden communication strategies. It helps identify politically biased news at its source, thereby reducing the media's influence on public perception. This paper proposes a tree‐structured hierarchical model for detecting political bias in news, where elements such as titles, bodies and sentences serve as nodes. A new method is introduced to extract the central sentence of the news, forming a primary‐secondary relationship between sentences. Experimental results show that our model is highly effective in detecting political bias in news.