Twitter is a popular, publicly-accessible, social media service that has proven useful in mapping large-scale events in real-time. In this study, for the first time, the use of Twitter as a measure of auroral activity is investigated. Peaks in the number of aurora-related tweets are found to frequently coincide with geomagnetic disturbances (detection rate of 91%). Additionally, the number of daily aurora-related tweets is found to strongly correlate with several auroral strength proxies (ravg ≈ 0.7). An examination is made of the bias for location and time of day within Twitter data, and a first order correction of these effects is presented. Overall, the results suggest that Twitter can provide both specific details about anindividual aurora and accurate real-time indication of when, and even from where, an aurora is visible.