Instituto de Biocomputación y Física de Sistemas Complejos (BIFI), Universidad de Zaragoza, Zaragoza, Spain.
PLoS One. 2011;6(8):e23883. doi: 10.1371/journal.pone.0023883. Epub 2011 Aug 19.
The number of people using online social networks in their everyday life is continuously growing at a pace never saw before. This new kind of communication has an enormous impact on opinions, cultural trends, information spreading and even in the commercial success of new products. More importantly, social online networks have revealed as a fundamental organizing mechanism in recent country-wide social movements. In this paper, we provide a quantitative analysis of the structural and dynamical patterns emerging from the activity of an online social network around the ongoing May 15th (15M) movement in Spain. Our network is made up by users that exchanged tweets in a time period of one month, which includes the birth and stabilization of the 15M movement. We characterize in depth the growth of such dynamical network and find that it is scale-free with communities at the mesoscale. We also find that its dynamics exhibits typical features of critical systems such as robustness and power-law distributions for several quantities. Remarkably, we report that the patterns characterizing the spreading dynamics are asymmetric, giving rise to a clear distinction between information sources and sinks. Our study represents a first step towards the use of data from online social media to comprehend modern societal dynamics.
在日常生活中,使用在线社交网络的人数正在以空前的速度持续增长。这种新的交流方式对意见、文化趋势、信息传播甚至新产品的商业成功都产生了巨大的影响。更重要的是,在线社交网络已经成为最近全国性社会运动的基本组织机制。在本文中,我们对围绕西班牙正在进行的 5 月 15 日(15M)运动的在线社交网络活动中出现的结构和动态模式进行了定量分析。我们的网络由在一个月的时间内交换推文的用户组成,其中包括 15M 运动的诞生和稳定。我们深入刻画了这样一个动态网络的增长,并发现它具有无标度特征,在介观尺度上具有社区结构。我们还发现,它的动力学表现出典型的临界系统特征,例如几个数量的稳健性和幂律分布。值得注意的是,我们报告说,刻画传播动力学的模式是不对称的,导致信息源和汇之间存在明显的区别。我们的研究代表了朝着使用在线社交媒体数据来理解现代社会动态迈出的第一步。