Mazimum Spread of Single-source Influence in Social Networks
Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains. The optimization problem of selecting the most influential nodes (multiple-sources) is NP-hard up to now. We consider the optimization problem of selecting the most influential single-source node based on trustworthiness, establish a maximum spread model of single-source influence, define concepts related to maximum spread of single-source influence, propose the polynomial time algorithm of maximum influence on single-source, quantify the largest node set influenced by single-source, and compute the most influential node in a social network. Our algorithm significantly out-performs node selection heuristics based on the well-studied notions of degree centrality and distance centrality from the field of social networks. Typical applications show that the optimization problem of selecting the most influential node on single-source has an important practical value. Our framework suggests a special approach for reasoning about the performance guarantees of algorithms for this type of influence problems in social networks.
The most influential algorithm mazimum spread single-source influence trust evaluation
Wang Fengying li Xiumei Zhou Lili Zhang Longbo
School of Computer Science and Technology, Shandong University of Technology, Zibo, China
国际会议
The Ninth Wuhan International Conference on E-Business(第九届武汉电子商务国际会议)
武汉
英文
416-421
2010-05-29（万方平台首次上网日期，不代表论文的发表时间）