In a dynamic social network, nodes can be removed from the network for some reasons, and consequently affect the behaviors of the network. In this paper, we tackle the challenge of finding a successor node for each removed seed node to maintain the influence spread in the network. Given a social network and a set of seed nodes for influence maximization, the problem is to effectively choose successors to inherit the jobs of initial influence propagation when some seeds are removed from the network. To tackle this problem, we present and discuss five neighborhoodbased selection heuristics, including degree, degree discount, overlapping, community bridge, and community degree. Experiments on DBLP co-authorship network show the effectiveness of devised heuristics. Copyright is held by the author/owner(s).