In order to support the task of detecting the unusual, we compare five widely used temporal aberration detection algorithms to look for spikes in the news event stream. This paper builds on our previously reported study for monolingual news alerting [4] by seeking to explore the hypothesis that cross-lingual events from text mining can provide improved detection rates. Although we focus here on newswire as a source we believe the results should have applicability for other unverified reports such as email lists and the rapidly developing space of user generated content.