“This paper studies how pictures leading online news pieces inuence readers’ processing of the news. I document two relevant facts in the US news market. First, the visual language adopted by news outlets is politically partisan and significantly polarized; such visual polarization is comparable in magnitude to the
documented verbal polarization of Congress in recent years. For this analysis, I construct a visual vocabulary of graphic features and apply a dictionary method to study the visual language polarization in the leading images published in US news between December 2019 and December 2020. Second, I document that such visual partisanship amounts to an expression of political media bias: in a survey experiment, individuals exposed to identical news pieces but leading pictures with opposite partisanship formulate significantly different opinions, which are slanted towards the images’ respective ideological poles. I find that news’ visual bias causes an increase in the issue polarization of the general public. The slanting effect of images interacts with readers’ prior, and audiences on both sides of the political spectrum react more distinctly to pictures aligned with their viewpoint. This pattern implies that the polarizing effect of visual bias is further exacerbated if readers’ source their news exclusively from like-minded outlets.”