Abstract

We propose an algorithm and system that detects earthquakes worldwide in real time based on reports of social media users, or "citizen-sensors." Earthquake detections are based on user postings in any language and from any region. This approach is unsupervised, adapting automatically to changes in the input data stream, and only requires a general list of keywords for each language. Our method is noise tolerant and simple, providing good results both in terms of precision and recall. This complements prior work that mostly consists of supervised approaches that focus on performing detections in a specific geographical area and are difficult to generalize to a global scope. We demonstrate the effectiveness of this approach by using it within a real-time on-line system, which is publicly available and currently in use at National Seismology Center in Chile and Oceanographic and Hydrological Office of the Chilean Army. The quantitative evaluation of our system, performed during a 9-month period, shows that our solution is competitive to the best state-of-the-art methods. Overall, our findings indicate that our approach is an effective low-cost alternative for earthquake monitoring at a global scale.