Localizing the Information Source in a Network
Localizing the Information Source in a Network
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DOI：
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发表时间：
2019
影响因子：
3
通讯作者：
G. Nie;Christoper Quinn
中科院分区：
文献类型：
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作者：
G. Nie;Christoper Quinn
信息和内容可以在社交网络中传播，就像疾病在生物体之间传播一样。当感染时间未知时，确定疫情的来源具有挑战性。我们考虑了一个简单的扩散模型，即传染性指数时间模型，在网络中随机传播的谣言的来源检测问题。感染时间不详。只有在特定时间之前传播谣言的节点集是已知的。由于评估传播的可能性在计算上是禁止的，我们提出了一个简单而有效的程序来近似的可能性，并选择一个候选谣言源。我们经验证明我们的方法优于约旦中心程序在各种随机图和现实世界的网络。
Information and content can spread in social networks analogous to how diseases spread between organisms. Identifying the source of an outbreak is challenging when the infection times are unknown. We consider the problem of detecting the source of a rumor that spread randomly in a network according to a simple diffusionmodel, the susceptible-infected (SI) exponential time model. The infection times are unknown. Only the set of nodes that propagated the rumor before a certain time is known. Since evaluating the likelihood of spreads is computationally prohibitive, we propose a simple and efficient procedure to approximate the likelihood and select a candidate rumor source. We empirically demonstrate our method out-performs the Jordan center procedure in various random graphs and a real-world network.