超级阻断剂与网络结构对信息级联的影响
Super-blockers and the effect of network structure on information cascades
摘要：
对在线社交网络上的信息级联进行建模在从市场营销到内乱预测等领域都很重要，然而底层网络结构强烈影响这种级联的概率和性质。即使是简单的级联动力学，大级联的概率几乎完全取决于网络特性，著名的网络，如Erdos-Renyi和Barabasi-Albert，从同一个模型中产生了截然不同的级联。事实上，“超级传播者”的概念已经出现，用来描述在社交网络中促进全球级联的具有高度影响力的节点。在这里，我们使用一个简单的全球级联模型来表明，在网络中的局部性的存在增加了全球级联的概率，由于连接节点的脆弱性增加。而不是“超级传播者”，我们发现这些高度连接的“超级阻断者”在重尾网络中的存在实际上降低了全球级联的概率，同时促进了信息传播。
英文摘要：
Modelling information cascades over online social networks is important in fields from marketing to civil unrest prediction, however the underlying network structure strongly affects the probability and nature of such cascades. Even with simple cascade dynamics the probability of large cascades are almost entirely dictated by network properties, with well-known networks such as Erdos-Renyi and Barabasi-Albert producing wildly different cascades from the same model. Indeed, the notion of 'superspreaders' has arisen to describe highly influential nodes promoting global cascades in a social network. Here we use a simple model of global cascades to show that the presence of locality in the network increases the probability of a global cascade due to the increased vulnerability of connecting nodes. Rather than 'super-spreaders', we find that the presence of these highly connected 'super-blockers' in heavy-tailed networks in fact reduces the probability of global cascades, while promoting information spread when targeted as the initial spreader.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
