Contrasting Protest from Mundanity in Communication Networks: Cohesion,Centralization, and the Russian Opposition Movement
Department of Sociology
Faculty of Social Sciences and Center for Advanced Studies
National Research University--Higher School of Economics
Though the intersection of social movement theory and network analysis has advanced many subjects on social mobilization--including research on interorganizational relationships, diffusion, and recruitment--this research area offers few systematic descriptions of protest sites. Expanding upon McPhail’s (2006, 2008) ethnographic work on interaction among protest participants, the study at hand seeks to characterize communication networks at protest sites.
By analyzing communication networks, this study tests the extent to which leadership and solidarity exist at protests. Social movement literature has offered competing descriptions on the nature of leadership. On the one hand, social mobilization requires a set of individuals to assume a disproportionate burden of the initial collective action costs (Oliver, Marwell, and Teixeira 1985) and such individuals may increase the prospects for successful social movement mobilization (Lind and Stepan-Norris 2011) as well as its associated outcomes (Ganz 2009). On the other hand, movements may disagree with the concept of leadership (Polletta 2005), undemocratic regimes characteristically repress movement leaders (Marx 1979; Nepstad and Bob 2006), and previous studies have found an association between the rise of centralized leadership and a decline of direct action tactics (Piven and Cloward 1977) as well as movement exclusivity (Taylor 1989:768-9). This study treats the presence of leadership as a conceptual cognate to centralization in communication networks (Freeman 1977, Shaw 1964). In the context of movement communication networks, betweenness centralization addresses the ability for leaders to bridge audiences, closeness centralization captures the speed at which leaders can disseminate a movement’s message, and eigenvector centralization captures the presence of cadres.
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