James McCorriston

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Geolocated social media data provides a powerful source of information about place and regional human behavior. Because little social media data is geolocation-annotated, inference techniques serve an essential role for increasing the volume of annotated data. One major class of inference approaches has relied on the social network of Twitter, where the(More)
Much work on the demographics of social media platforms such as Twitter has focused on the properties of individuals, such as gender or age. However, because credible detectors for organization accounts do not exist, these and future large-scale studies of human behavior on social media can be contaminated by the presence of accounts belonging to(More)
Exercise plays a central role in many peoples' fitness goals. While prior work has examined how individuals pursue these health and fitness goals on general purpose platforms such as Twitter, the lack of precise activity recording has limited detailed analyses of individual and group behaviors. In this study, we explore a recent social media platform(More)
Discriminating amongst stimuli in the environment is a fundamental aspect of brain function. Research has shown that chaotic neural networks are exquisitely sensitive to small perturbations making them unreliable and unpredictable. Here, we examine how neuronal oscillations (i.e., temporal waves of activity) may be tuned to enhance the discrimination(More)
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