The Complexity of Finding Effectors

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• 作者：Laurent Bulteau ; Stefan Fafianie ; Vincent Froese…
• 关键词：Probabilistic information propagation ; Influence maximization ; Network activation ; Social networks ; Exact algorithms ; Parameterized complexity
• 刊名：Theory of Computing Systems
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：60
• 期：2
• 页码：253-279
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Theory of Computation; Computational Mathematics and Numerical Analysis;
• 出版者：Springer US
• ISSN：1433-0490
• 卷排序：60

文摘

The NP-hard Effectors problem on directed graphs is motivated by applications in network mining, particularly concerning the analysis of probabilistic information-propagation processes in social networks. In the corresponding model the arcs carry probabilities and there is a probabilistic diffusion process activating nodes by neighboring activated nodes with probabilities as specified by the arcs. The point is to explain a given network activation state as well as possible by using a minimum number of “effector nodes”; these are selected before the activation process starts. We correct, complement, and extend previous work from the data mining community by a more thorough computational complexity analysis of Effectors, identifying both tractable and intractable cases. To this end, we also exploit a parameterization measuring the “degree of randomness” (the number of ‘really’ probabilistic arcs) which might prove useful for analyzing other probabilistic network diffusion problems as well.