Twitter Geolocation

Abstract

Geotagging Twitter messages is an important tool for event detection and enrichment. Despite the availability of both social media content and user network information, these two features are generally utilized separately in the methodology. In this article, we create a hybrid method that uses Twitter content and network information jointly as model features. We use Gaussian mixture models to map the raw spatial distribution of the model features to a predicted field. This approach is scalable to large datasets and provides a natural representation of model confidence. Our method is tested against other approaches and we achieve greater prediction accuracy. The model also improves both precision and coverage.