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Social media has quickly risen to prominence as a news source, yet lingering doubts remain about its ability to spread rumor and misinformation. Systematically studying this phenomenon, however, has been difficult due to the need to collect large-scale, unbiased data along with in-situ judgements of its accuracy. In this paper we present CREDBANK, a corpus designed to bridge this gap by systematically combining machine and human computation. Specifically, CREDBANK is a corpus of tweets, topics, events and associated human credibility judgements.

Starting this summer, the Atlanta Streetcar began using a real-time dispatching method developed at Georgia Tech that eliminates the need for schedules and cuts down on passenger wait times. School of Civil and Environmental Engineering Assistant Professor Kari Watkins and Ph.D student Simon Berrebi developed an algorithm that ensures each vehicle is spaced evenly along the 2.7 mile route in downtown Atlanta, maximizing the frequency of service. Unlike the previous method, the Georgia Tech algorithm uses real-time information.

Heart Sense takes biometric data from participants and produces captivating visualizations as their bodies react to visual stimuli.