  It is widely believed that information spread on social media is a
percolation process, with parallels to phase transitions in theoretical
physics. However, evidence for this hypothesis is limited, as phase transitions
have not been directly observed in any social media. Here, through analysis of
100 million Weibo and 40 million Twitter users, we identify percolation-like
spread, and find that it happens more readily than current theoretical models
would predict. The lower percolation threshold can be explained by the
existence of positive feedback in the coevolution between network structure and
user activity level, such that more active users gain more followers. Moreover,
this coevolution induces an extreme imbalance in users' influence. Our findings
indicate that the ability of information to spread across social networks is
higher than expected, with implications for many information spread problems.
