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Because of computational concerns, social network analysis generally uses only directly connected nodes to perform classification tasks. However, recent research indicates that this method of classification may not consider that nodes in the graph could have different influence over other nodes near them in the graph. It is possible that well-selected nodes may have a stronger importance in a social graph. Here, we analyze methods by which these important nodes may be identified and used todoi:10.1109/isi.2011.5984054 dblp:conf/isi/HeatherlyK11 fatcat:w4xplz7lwzdtbojd7tcvewni3q