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In times marked by an abundance of news sources and the widespread use ofsocial media for staying informed, acquiring accurate data faces increasingchallenges. Today, access to information plays a crucial role in shaping publicopinion and is significantly influenced by interactions on social media.Therefore, studying the dissemination of news on these platforms is vital forunderstanding how individuals stay informed. In this paper, we study emergentproperties of media outlet sharing behavior by users in social media. Wequantify this behavior in terms of coordinates in a latent space proposing ametric called Media Sharing Index (MSI). We observe that the MSI shows abimodal distribution in this latent dimension, reflecting the preference oflarge groups of users for specific groups of media outlets. This methodologyallows the study of the extent to which communities of interacting users arepermeable to different sources of information. Additionally, it facilitates theanalysis of the relationship between users' media outlet preferences, theirpolitical leanings, and the political leanings of the media outlets.

The hidden dimension of information diffusion: A latent space representation of Social Media News Sharing behavior