Event detection in social media usually exploits information from social-networking platforms, such as Twitter or Facebook. However, previous research has suggested that Wikipedia constitutes a valuable source of information for the task of detecting breaking news. In this work we adapt a graph-based algorithm to the Wikipedia context, and compare it to the state-of-the-art Wikipedia real-time monitoring method. The main idea behind the proposed method is to extract breaking news by looking at unusual activity in the Wikipedia edit stream. We assess the performance of the two competing algorithms by measuring the percentage of true events correctly identified. Results show that the proposed graph-based method achieves better accuracy and coverage.