In nature and human society, information can be spread in many different ways. How this process actually occurs is of the utmost importance both for our everyday life and for manmade systems. At BIFI (Institute for Biocomputation and Physics of Complex Systems), and in collaboration with the start-up company Cierzo Development, we have investigated the mechanism driving the emergence of the "15M movement", and whether this social phenomenon shares dynamical and structural features with other natural, social and technological processes. The ultimate aim is to advance in our understanding of this kind of dynamics in order to be able to make predictions.
The analysis comprises the period between April 25 and May 26, 2011. From the 70 keywords related to the movement 15M, all the messages exchanged between users that contained at least one of these words have been traced. In total, 581.749 messages coming from 87.569 users were identified and used for the study. The data analyzed here represent about one third of all the messages and posts created in the world.
The study carried out constitutes a unique opportunity to get enough of real time statistical data. Other mass-tracking events such as large sport events, tend to be too concentrated in a few hours and some processes for which large statistics can be obtained, are usually of slow variation. A social phenomenon like the 15M movement is an excellent opportunity to understand network formation processes and its spreading dynamics.
The figure represents the evolution of the network of Twitter users that exchange messages during the 10 days following the beginning (May 15, 2011) of camp in Puerta del Sol in Madrid, Spain. Each node in the network represents an individual, and the node size is proportional to the total number of messages he/she sent or received in the period analyzed. Two nodes are connected if they have exchanged at least one message. The colors encode the "age" of the node: the first active users are represented in yellow, while black color is used for the latecomers.
As we can appreciate, the evolution of the number of users following the protest is not a slow, linear or progressive process, on the contrary, it is quite fast and nonlinear. During the previous days to the emergence of the movement, the system was asleep and in less than 6 days, it was capable of agglutinating the entire group. The growth pattern of the movement recalls other well-known examples of self-organization (critical phenomena in Physics, Economics, Biology, Avalanches and Earthquakes phenomena, etc...)