How Social Media Facilitates Political Protest: Information, Motivation, and Social Networks : Social Media and Political Protest

An integrative social identity model of collective action (SIMCA) is developed that incorporates 3 socio-psychological perspectives on collective action. Three meta-analyses synthesized a total of 182 effects of perceived injustice, efficacy, and identity on collective action (corresponding to these socio-psychological perspectives). Results showed that, in isolation, all 3 predictors had medium-sized (and causal) effects. Moreover, results showed the importance of social identity in predicting collective action by supporting SIMCA's key predictions that (a) affective injustice and politicized identity produced stronger effects than those of non-affective injustice and non-politicized identity; (b) identity predicted collective action against both incidental and structural disadvantages, whereas injustice and efficacy predicted collective action against incidental disadvantages better than against structural disadvantages; (c) all 3 predictors had unique medium-sized effects on collective action when controlling for between-predictor covariance; and (d) identity bridged the injustice and efficacy explanations of collective action. Results also showed more support for SIMCA than for alternative models reflecting previous attempts at theoretical integration. The authors discuss key implications for theory, practice, future research, and further integration of social and psychological perspectives on collective action. PsycINFO Database Record (c) 2008 APA

Human behaviour is thought to spread through face-to-face social networks, but it is difficult to identify social influence effects in observational studies, and it is unknown whether online social networks operate in the same way. Here we report results from a randomized controlled trial of political mobilization messages delivered to 61 million Facebook users during the 2010 US congressional elections. The results show that the messages directly influenced political self-expression, information seeking and real-world voting behaviour of millions of people. Furthermore, the messages not only influenced the users who received them but also the users' friends, and friends of friends. The effect of social transmission on real-world voting was greater than the direct effect of the messages themselves, and nearly all the transmission occurred between 'close friends' who were more likely to have a face-to-face relationship. These results suggest that strong ties are instrumental for spreading both online and real-world behaviour in human social networks.

The origin of large but rare cascades that are triggered by small initial shocks is a phenomenon that manifests itself as diversely as cultural fads, collective action, the diffusion of norms and innovations, and cascading failures in infrastructure and organizational networks. This paper presents a possible explanation of this phenomenon in terms of a sparse, random network of interacting agents whose decisions are determined by the actions of their neighbors according to a simple threshold rule. Two regimes are identified in which the network is susceptible to very large cascades-herein called global cascades-that occur very rarely. When cascade propagation is limited by the connectivity of the network, a power law distribution of cascade sizes is observed, analogous to the cluster size distribution in standard percolation theory and avalanches in self-organized criticality. But when the network is highly connected, cascade propagation is limited instead by the local stability of the nodes themselves, and the size distribution of cascades is bimodal, implying a more extreme kind of instability that is correspondingly harder to anticipate. In the first regime, where the distribution of network neighbors is highly skewed, it is found that the most connected nodes are far more likely than average nodes to trigger cascades, but not in the second regime. Finally, it is shown that heterogeneity plays an ambiguous role in determining a system's stability: increasingly heterogeneous thresholds make the system more vulnerable to global cascades; but an increasingly heterogeneous degree distribution makes it less vulnerable.