While scholars have made great strides in formulating theories and measuring public attention, "most important problem" and media-based indicators are less than ideal measures. In order to address this shortcoming, this article borrows from health-care epidemiology to measure public attention based on Internet search trends. In doing so, it reviews the innovative ways in which scientists have used search activity to track the spread of infectious disease, discusses the ease and flexibility with which search data can be gathered, and then subjects a Google-based search measure to a series of validity tests. In particular, the analysis subjects the proposed measure to a battery of visual and statistical tests for convergent validity by comparing it with the most commonly used media-based measure of public attention-issue coverage in the New York Times. Across a range of policy issues (health care, global warming, and terrorism), the proposed measure demonstrates convergent validity. The article concludes by posing a series of important questions that the new measure will allow researchers to address.

This paper evaluates the prospects for application of the "grid/group" cultural theory (CT), as advanced by Mary Douglas and Aaron Wildavsky, to the Advocacy Coalition Theory (ACF). CT would seem to be relevant to several key aspects of the ACF: the content of the core beliefs that provide the "glue" that binds coalitions; the resilience of core beliefs and associated implications for belief change and learning; and the structure of coalitions and the mechanisms for coordination and control within them. The paper considers the compatibility of the ACF's account of deep core beliefs and coalition structure with that of CT; surveys an array of empirical studies based on variations of CT; and extends accounts of change in cultural identities from CT to the ACF. In addition, we highlight some of the ways in which the ACF may offer important theoretical insights for scholars of CT, potentially clarifying hypotheses concerning the relationships among basic worldviews, more specific beliefs, and behaviors.

Deep core beliefs represent an important yet theoretically underspecified concept within the Advocacy Coalition Framework (ACF). This underspecification can (in part) be attributed to the ad hoc way in which ACF scholars have defined and measured the concept over time. To overcome this, we advocate the development and future use of a standardized metric for measuring deep core beliefs in ACF studies. Such a measure, we contend, should be multidimensional, generalizable, measurable using multiple techniques, and broad enough in scope to operate across virtually all policy domains. Using these criteria as our benchmark, we evaluate the viability of cultural theory (CT) as one such metric. In short, we find that CT meets all of these criteria, and therefore provides ACF scholars with a way to measure deep core beliefs across enduring public policy disputes that are demarcated by conflicting belief systems. Accordingly, we advocate its use in future studies.

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Increasingly, policy scholars are using the Narrative Policy Framework (NPF) to systematically study the narrative elements and strategies that policy actors and groups use to advance their agendas. The majority of these studies analyze reports, documents, and websites published by the actors and groups that are most active in the policy subsystem. Though useful, these “public consumption documents” can be difficult to find and relatively static. In this article, we suggest that the constant flow of messages and content that competing actors and groups publish on social media may provide a solution to this problem. To test this proposition, we use the NPF to analyze messages published on Twitter by competing advocacy groups in the U.S. nuclear energy policy subsystem from January 2014 to May 2014 (n = 703). We find that both groups use Twitter to disseminate messages that contain the basic elements of policy narratives. Moreover, the narratives they use include strategies that are consistent with their position in the subsystem. These findings demonstrate the utility of the NPF for research on social media and, more importantly, validate the use of Twitter data in future work on the NPF.