Authors:
Marco Vernier
;
Manuela Farinosi
and
Gian Luca Foresti
Affiliation:
University of Udine, Italy
Keyword(s):
Twitter, Geo-data, Data-mining, Event Detection, Situation Awareness, Panoramic Image, Smart Visualization.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Image Formation and Preprocessing
;
Image Formation, Acquisition Devices and Sensors
;
Mobile Imaging
Abstract:
In the last years, social media have grown in popularity with millions of users that everyday produce and share
online digital content. This practice reveals to be particularly useful in extra-ordinary context, such as during
a disaster, when the data posted by people can be integrated with traditional emergency management tools
and used for event detection and hyperlocal situational awareness. In this contribution, we present SVISAT,
an innovative visualization system for Twitter data mining, expressly conceived for signaling in real time a
given event through the uploading and sharing of visual information (i.e., photos). Using geodata, it allows
to display on a map the wide area where the event is happening, showing at the same time the most popular
hashtags adopted by people to spread the tweets and the most relevant images/photos which describe the event
itself.