Computer ScienceHumanities & Social Sciences Communications
Uncovering the essence of diverse media biases from the semantic embedding space
H. Huang, H. Zhu, et al.
This study, conducted by Hong Huang, Hua Zhu, Wenshi Liu, Hua Gao, Hai Jin, and Bang Liu, reveals a groundbreaking media bias analysis framework that utilizes embedding techniques to quantify bias across diverse topics. With an analysis of over 8 million event records and 1.2 million news articles, findings indicate that media bias varies regionally and is influenced by current events, shedding light on important stereotypes like gender bias.
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