A large part of media shared on online platforms such as Flickr and YouTube is captured at various social events (e.g. music festivals, exhibitions, and sport events). While it is quite easy to share personal impressions online, it is much more challenging to identify content that is related to the same social event across different platforms. In this paper we focus on the detection of social events in a data collection from Flickr and YouTube. We propose an unsupervised, multi-staged approach that explores commonly available, real-world metadata for the detection and linking of social events across sharing platforms. The proposed methodology and the performed experiments allow for a thorough evaluation of the usefulness of available metadata in the context of social event detection in both single-platform and cross-platform scenario.

Top