Event Detection in Czech Twitter

The main goal of this paper is to create a novel experimental system for the Czech News Agency (ČTK) which is able to monitor the current dataflow on Twitter, analyze it and extract relevant events. The detected events are then presented to users in an acceptable form. A novel event detection approach adapted to the Czech Twitter is thus proposed. It uses user-lists to discover potentially interesting tweets which are further clustered into groups based on the content. The final decision is based on thresholding. The main research contribution is to propose an original approach to harvest potential events from Twitter with high download speed. We experimentally show that the proposed approach is useful because it detects a significant amount of the events. It is worth of noting that this approach is domain independent.