  With an increasing amount of information on globally important events, there
is a growing demand for efficient analytics of multilingual event-centric
information. Such analytics is particularly challenging due to the large amount
of content, the event dynamics and the language barrier. Although memory
institutions increasingly collect event-centric Web content in different
languages, very little is known about the strategies of researchers who conduct
analytics of such content. In this paper we present researchers' strategies for
the content, method and feature selection in the context of cross-lingual
event-centric analytics observed in two case studies on multilingual Wikipedia.
We discuss the influence factors for these strategies, the findings enabled by
the adopted methods along with the current limitations and provide
recommendations for services supporting researchers in cross-lingual
event-centric analytics.
