Before revision:  We present the first systematic analysis of  U.S. political train networks, which involve many thousands of hyper-partisan accounts. These accounts engage in various suspicious behaviors , including some that violate platform policies: we find evidence of  inauthentic automated accounts , artificial inflation of friends and followers, and abnormal content deletion .
After revision:  We present the first systematic analysis of U.S. hyper-partisan train network. We observe an artificial inflation of influence: accounts heavily promoted by follow trains profit from a median six-fold increase in daily follower growth. This catalyzes the formation of highly clustered echo chambers, URLanized around a dense core of active accounts. Train accounts also engage in other behaviors that violate platform policies: we find evidence of inauthentic automated accounts , artificial inflation of friends and followers, and abnormal content deletion .