We demonstrate that framing, a subjective aspect of news, is a causal precursor to both significant public perception changes, and to federal legislation. We posit, counter-intuitively, that topic news volume and article similarity vary in direct proportion. We observe that public attention changes are driven primarily by periods of high news volume and similarity. We show that specific features of news, such as publishing volume are predictive of both sustained public attention, measured by annual Google trend data, and federal legislation. Finally, we demonstrate that framing during causal periods may be characterized by high-utility news keywords.
LAS aims to bring together a multi-disciplinary group of academic, industry, and government researchers, analysts and managers together to re-engineer the intelligence analysis process to promote predictive analysis. LAS will do this by conducting both classified and unclassified research in a variety of areas of research. The research done in this area will serve as the foundation for mission effects and integrated back into the enterprise.
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