Drawing from the paper Social Mobilization and the Networked Public Sphere: Mapping the SOPA-PIPA Debate, this interactive visualization maps the evolution of a public controversy by collecting time slices of thousands of sources, then using link analysis to assess the progress of the debate over time. For this study, we compiled, mapped, and analyzed a set of 9,757 stories relevant to the COICA-SOPA-PIPA debate from September 2010 through the end of January 2012 using Media Cloud, an open source tool created at the Berkman Center to allow quantitative analysis of a large number of online media sources. This study applies a mixed-methods approach by combining text and link analysis with human coding and informal interviews to map the evolution of the controversy over time and to analyze the mobilization, roles, and interactions of various actors.
This visualization includes selected maps from the periods discussed in the paper. In it, we depict media sources ("nodes", which appear as circles on the map with different colors denoting different media types) using a platform developed in part for such work, Media Cloud. By tracking these media sources, we are able to see who is linking to whom at any point in time, which lets us begin to understand the dynamics of the emerging public conversation. What emerged from our novel, data-driven investigation was a set of network maps that support the proposition that the 17-months of the SOPA-PIPA debate reflect quite a different game from the one that has historically played out in the traditional, mass-mediated public sphere.
In exploring the maps depicted here and in the associated paper, it is worth noting that the size of a given node in the map is a reflection of the number of in-links to that media source during the specified time period. This means that the size of a node offers a measure of the relative importance of that site within the ecosystem of entities engaged with the topic. When the number of links are sparse in the network, as in the early weeks of the debate, sites that receive just a handful of links can appear as large nodes in the figures, and we caution against assigning too much importance to large nodes during these weeks without further investigation. For such weeks, the Media Cloud team based the conclusions drawn in the paper as well as in the text that accompanies each map in this visualization on a substantive review of every article published in the noted period. This approach allowed us to ensure that we did not assign more importance to a given node than is deserved. We encourage interested researchers to consult the methods section of the paper for further details.