A spread algorithm of the most influential node on single-source

Based on node influence, establishes a maximum spread model of single-source influence, defines concepts related to maximum spread of single-source influence, proposes the polynomial time algorithm of maximum influence on single-source, quantifies the largest node set influenced by single-source, computes the most influential node in a social network. Our algorithms significantly out-perform node selection heuristics based on the well-studied notions of degree centrality and distance centrality from the field of social networks. Our framework suggests a special approach for reasoning about the performance guarantees of algorithms for this type of influence problems in social networks. Typical applications show that the optimization problem of selecting the most influential node on single-source has an important practical value.