利用朋友作为传感器来检测全球范围的传染病爆发
Using Friends as Sensors to Detect Global-Scale Contagious Outbreaks
摘要：
最近的研究侧重于监测全球规模的在线数据，以更好地发现流行病、情绪模式、股票市场的波动、政治革命、票房收入、消费者行为和许多其他重要现象。然而，隐私方面的考虑和在线可用数据的庞大规模正在迅速使全球监测变得不可行，并且现有方法没有充分利用本地网络结构来识别用于监测的关键节点。在这里，我们开发了一个全球规模的，公开表达的社交网络中的信息传染性传播模型，并表明一个简单的方法不仅可以早期检测，而且可以提前预警传染性疫情。在这种方法中，我们随机选择网络中的一小部分节点，然后随机选择每个节点的一个“朋友”，包括在一个组中进行本地监控。使用来自整个Twitter领域的大部分六个月的数据，我们表明这个朋友群体在网络中更重要，它有助于我们比我们使用相同大小的随机选择的群体提前7天检测到使用新标签的病毒爆发。此外，由于网络结构本身，该方法实际上比预期的效果更好，因为高度中心化的参与者更加活跃，并且在他们向其他人传递的信息中表现出更大的多样性。这些结果表明，局部监测不仅效率更高，而且更有效，而且有可能对全球规模网络中的其他传染过程进行类似的监测。
英文摘要：
Recent research has focused on the monitoring of global-scale online data for improved detection of epidemics, mood patterns, movements in the stock market, political revolutions, box-office revenues, consumer behaviour and many other important phenomena. However, privacy considerations and the sheer scale of data available online are quickly making global monitoring infeasible, and existing methods do not take full advantage of local network structure to identify key nodes for monitoring. Here, we develop a model of the contagious spread of information in a global-scale, publicly-articulated social network and show that a simple method can yield not just early detection, but advance warning of contagious outbreaks. In this method, we randomly choose a small fraction of nodes in the network and then we randomly choose a "friend" of each node to include in a group for local monitoring. Using six months of data from most of the full Twittersphere, we show that this friend group is more central in the network and it helps us to detect viral outbreaks of the use of novel hashtags about 7 days earlier than we could with an equal-sized randomly chosen group. Moreover, the method actually works better than expected due to network structure alone because highly central actors are both more active and exhibit increased diversity in the information they transmit to others. These results suggest that local monitoring is not just more efficient, it is more effective, and it is possible that other contagious processes in global-scale networks may be similarly monitored.
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。
