Stern School of Business, New York University, New York, NY 10012, USA.
Science. 2012 Jul 20;337(6092):337-41. doi: 10.1126/science.1215842. Epub 2012 Jun 21.
Identifying social influence in networks is critical to understanding how behaviors spread. We present a method that uses in vivo randomized experimentation to identify influence and susceptibility in networks while avoiding the biases inherent in traditional estimates of social contagion. Estimation in a representative sample of 1.3 million Facebook users showed that younger users are more susceptible to influence than older users, men are more influential than women, women influence men more than they influence other women, and married individuals are the least susceptible to influence in the decision to adopt the product offered. Analysis of influence and susceptibility together with network structure revealed that influential individuals are less susceptible to influence than noninfluential individuals and that they cluster in the network while susceptible individuals do not, which suggests that influential people with influential friends may be instrumental in the spread of this product in the network.
识别网络中的社会影响对于理解行为传播至关重要。我们提出了一种方法，该方法使用体内随机实验来识别网络中的影响和易感性，同时避免了传统社会传染估计中固有的偏差。在对 130 万 Facebook 用户的代表性样本进行估计时，结果表明，年轻用户比老年用户更容易受到影响，男性比女性更有影响力，女性对男性的影响大于对其他女性的影响，而已婚人士在决定是否采用所提供的产品时最不容易受到影响。对影响和易感性以及网络结构的综合分析表明，有影响力的个体比无影响力的个体更不容易受到影响，而且他们在网络中聚集，而易感个体则不会，这表明具有有影响力的朋友的有影响力的人可能是该产品在网络中传播的重要因素。
