Sara Barozzi, Jose Luis Fernandez Marquez, Amudha Ravi Shankar, & Barbara Pernici. (2019). Filtering images extracted from social media in the response phase of emergency events. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: The use of social media to support emergency operators in the first hours of the response phases can improve the
quality of the information available and awareness on ongoing emergency events. Social media contain both textual
and visual information, in the form of pictures and videos. The problem related to the use of social media posts
as a source of information during emergencies lies in the difficulty of selecting the relevant information among
a very large amount of irrelevant information. In particular, we focus on the extraction of images relevant to an
event for rapid mapping purpose. In this paper, a set of possible filters is proposed and analyzed with the goal of
selecting useful images from posts and of evaluating how precision and recall are impacted. Filtering techniques,
which include both automated and crowdsourced steps, have the goal of providing better quality posts and easy
manageable data volumes both to emergency responders and rapid mapping operators. The impact of the filters on
precision and recall in extracting relevant images is discussed in the paper in two different case studies.