Empirical evidence confirms the warnings forecasted by political theory: the legitimacy of the institutions of representative democracy is under fire. At the same time, non conventional forms of political participation emerge to express social discontent, and to organize unrepresented preferences. Understanding the motivations, dynamics and proposals of those new actors is a sine qua non to identify the inefficiencies of the challenged political systems, and also to inform the normatively substantiated enactment and adaptation of the political institutions. However, the scientific inquiry of those novel forms of participation introduces methodological challenges which need to be solved in order to deal with the increasing reliance of collective action on information and communication technologies. This paper undertakes that task showing how the methods of Social Network Analysis and Natural Language Processing can be applied on Big Data to successfully unveil the content and the structure of the emerging political actors.
