  The spreading of unsubstantiated rumors on online social networks (OSN)
either unintentionally or intentionally (e.g., for political reasons or even
trolling) can have serious consequences such as in the recent case of rumors
about Ebola causing disruption to health-care workers. Here we show that
indicators aimed at quantifying information consumption patterns might provide
important insights about the virality of false claims. In particular, we
address the driving forces behind the popularity of contents by analyzing a
sample of 1.2M Facebook Italian users consuming different (and opposite) types
of information (science and conspiracy news). We show that users' engagement
across different contents correlates with the number of friends having similar
consumption patterns (homophily), indicating the area in the social network
where certain types of contents are more likely to spread. Then, we test
diffusion patterns on an external sample of $4,709$ intentional satirical false
claims showing that neither the presence of hubs (structural properties) nor
the most active users (influencers) are prevalent in viral phenomena. Instead,
we found out that in an environment where misinformation is pervasive, users'
aggregation around shared beliefs may make the usual exposure to conspiracy
stories (polarization) a determinant for the virality of false information.
