The diffusion of information, norms, and practices across a social network can be initiated by compelling a small number of seed individuals to adopt first. Strategies proposed in previous work either assume full network information or large degree of control over what information is collected. However, privacy settings on the Internet and high non-response in surveys often severely limit available connectivity information. Here we propose a seeding strategy for scenarios with limited network information: Only the degrees and connections of some random nodes are known. This new strategy is a modification of "random neighbor sampling" and seeds the highest-degree neighbors of randomly selected nodes. In simulations of a linear threshold model on a range of synthetic and real-world networks, we find that this new strategy outperforms other seeding strategies, including high-degree seeding and clustered seeding.
翻译:社会网络的信息、规范和做法的传播可以通过迫使少数种子人首先采用的方式开始。以前工作中提出的战略要么对收集的信息拥有充分的网络信息,要么对收集的信息拥有很大程度的控制。然而,互联网上的隐私设置和调查中的高度无反应往往严重限制可获取的连通信息。我们在这里为网络信息有限的情景提出了一个播种战略:只知道一些随机节点的程度和连接。这一新战略是修改“随机邻居抽样”和种子随机选择的节点的最高水平邻居。在模拟一系列合成和现实世界网络的线性阈值模型时,我们发现这一新战略比其他种子战略(包括高度播种和集群播种)要好得多。