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Patterns of event propagation in online social networks provide novelinsights on the modeling and analysis of information dissemination overnetworks and physical systems. This paper studies the importance of followerlinks for event propagation on Twitter. Three recent event propagation tracesare collected with the Twitter user language field being used to identify theNetwork of Networks (NoN) structure embedded in the Twitter follower networks.We first formulate event propagation on Twitter as an iterative state equation,and then propose an effective score function on follower links accounting forthe containment of event propagation via link removals. Furthermore, we findthat utilizing the NoN model can successfully identify influential followerlinks such that their removals lead to a remarkable reduction in eventpropagation on Twitter follower networks. Experimental results find that thebetween-network follower links, though only account for a small portion of thetotal follower links, are crucial to event propagation on Twitter.

Identifying Influential Links for Event Propagation on Twitter: A Network of Networks Approach