Abstract
A methodological approach is developed for exploring the relationship between the use of social networking sites and participation in protest activities. Although a recent meta-analysis study demonstrated that there is a positive association between the two, little work examining this association further appears to have been published. The methodology proposed here studies the patterns of the relationship between nine social media and five types of protest activity using the techniques of multiple correspondence analysis, hierarchical cluster analysis and induction of decision rules. The results give insights into the relationship in different segments of individuals’ profiles defined as non-activist, offline activist, social media user (two types) and online activist. Significantly, this last segment proves to be a small and heterogeneous group. The results also show that the proposed approach is useful for exploring the patterns of the relationship in a low-dimensional space. Limitations of the methodology and possible extensions are discussed.
Highlights
The use of social networking sites has emerged in recent years as a factor in the dynamic of civil protest [1, 2]
This section sets out the results of the proposed methodological approach separately for the three techniques, that is, multiple correspondence analysis (MCA), agglomerative hierarchical clustering and decision rule induction
We explore in detail the active and supplementary variables to obtain a better appreciation of the MCA results
Summary
The use of social networking sites has emerged in recent years as a factor in the dynamic of civil protest [1, 2]. Examples include Chilean students marching in support of education reform [3], demonstrations in Brazil culminating in the impeachment of Dilma Rousseff [4] and street clashes in Venezuela between supporters and opponents of Nicolás Maduro [5]. In each of these situations, the role played by online social networks in the protests has been documented (see [6, 7]). Measuring individual online activities in many social networking sites (i.e., cross-channel social media analysis) is still in the experimental
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