
The recent wave of mobilizations in the Arab world and across Western countries has generated much discussion on how digital media is connected to the diffusion of protests. We examine that connection using data from the surge of mobilizations that took place in Spain in May 2011. We study recruitment patterns in the Twitter network and find evidence of social influence and complex contagion. We identify the network position of early participants (i.e. the leaders of the recruitment process) and of the users who acted as seeds of message cascades (i.e. the spreaders of information). We find that early participants cannot be characterized by a typical topological position but spreaders tend to me more central to the network. These findings shed light on the connection between online networks, social contagion, and collective dynamics, and offer an empirical test to the recruitment mechanisms theorized in formal models of collective action.
Main text: 20 pages, 4 figures; Supplementary Information: 17 pages, 5 figures, 3 tables
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Physics - Physics and Society, Internet, Time Factors, Information Dissemination, Politics, FOS: Physical sciences, Computer Science - Social and Information Networks, Physics and Society (physics.soc-ph), Models, Theoretical, Article, Social Networking, Humans
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Physics - Physics and Society, Internet, Time Factors, Information Dissemination, Politics, FOS: Physical sciences, Computer Science - Social and Information Networks, Physics and Society (physics.soc-ph), Models, Theoretical, Article, Social Networking, Humans
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 426 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
