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Although many recent studies have examined presidential campaigns, most have concentrated on television advertising or news media coverage as the key variables of interest.Few empirical analyses have focused on the pattern of candidate appearances and almost none have considered changes in these patterns over time. This gap is intriguing because some places should tend to receive more attention than others, and yet we know very little about the electoral strategies that determine where and why candidates make appearances. We expect that presidential campaigns have increasingly emphasized visits to particular locales because these visits are critical for driving the agenda and shaping voter perceptions through local news media coverage. Our analysis of presidential campaign appearances at the county, media market, and state levels in general elections from 1972-2000 indicates that presidential candidate appearances are increasing both in number and in geographic scope over time. While candidate appearances are concentrated in areas with especially dense and large populations, most eligible voters live in media markets that receive at least one visit by a presidential candidate, and the percentage of eligible voters exposed to especially intense personal campaigning has been on the rise. In contrast to our expectations, our findings suggest that presidential campaign appearances have not become more narrowly focused on smaller segments of the American population.

“Big data” in the form of unstructured text pose challenges and opportunities to social scientists committed to advancing research frontiers. Because machine-based and human-centric approaches to content analysis have different strengths for extracting information from unstructured text, the authors argue for a collaborative, hybrid approach that combines their comparative advantages. The notion of a progressive supervised-learning approach that combines data science techniques and human coders is developed and illustrated using the Social, Political and Economic Event Database (SPEED) project’s Societal Stability Protocol. SPEED’s rich event data on civil strife reveal that conventional machine-based approaches for generating event data miss a great deal of within-category variance, while conventional human-based efforts to categorize periods of civil war or political instability routinely misspecify periods of calm and unrest. To demonstrate the potential of hybrid data collection methods, SPEED data on event intensities and origins are used to trace the changing role of political, socioeconomic, and sociocultural factors in generating global civil strife in the post–World War II era.

I T. ARNOLD, THE SYMBOLS OF GOVERNMENT 123 (1956). herence to strict procedural safeguards is our main assurance that there will be equal justice under law. 4 Consequently, this Article makes a limited inquiry into the nature of the process used to handle defendants accused of felony offenses. We used an extensive body of data on almost 7,500 defendants in nine diverse, medium-sized counties (populations ranged from 200,000 to 1,000,000) in three states (Illinois, Michigan and Pennsylvania). 5 This Article examines empirically-if only 2 Id. 3 341 U.S. 123 (1951). 4 Id. at 179 (Douglas, J., concurring). 5 The Illinois counties were DuPage, Peoria and St. Clair; the Michigan counties were Oakland, Kalamazoo and Saginaw; the Pennsylvania counties were Montgomery, Dauphin and Erie. We selected the countries in an effort to maximize within-state variance along two dimensions: one was a socioeconomic well-being dimension, the other concerned the nature of the political linkages between the court system and its environment. In selecting counties, however, we were restricted by the number of large counties that fit our criteria. Size was crucial because we needed to sample a large number of

University of Illinois 1970. data will be used to conduct a rough examination of some of the ideas presented.