Annotating real time Twitter's images/videos basing on tweets

Nowadays, online social network “Twitter” represents a huge source of unrefined information in various formats (text, video, photo), especially during events and abnormal cases/incidents. New features for Twitter mobile application are now available, allowing user to publish direct photos online. This paper is focusing on photos/videos taken by user and published in real time using only mobile devices. The aim is to find candidates for annotation from Tweet stream, then to annotate them by taking into accounts several features based only on tweets. A preprocessing step is necessary to exclude all useless tweets, we then process textual content of the rest. As a final step, we consider an additional characterization (spatio-temporal and saliency) to get outcome of the annotation as RDF triples.