Visual analysis of real-time social media for emergency response

MAZUMDAR, Suvodeep, LANFRANCHI, Vitaveska, IRESON, Neil and CIRAVEGNA, Fabio (2014). Visual analysis of real-time social media for emergency response. In: 2nd Workshop on Social Media and Linked Data for Emergency Response (SMILE 2014), Extended Semantic Web Conference 2014. (ESWC 2014), Anissaras, Crete, Greece, 25 May 2014.

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Official URL: http://linkedscience.org/events/smile2014/
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Abstract

The prevalence of Social Media in sharing day to day in- formation regarding all aspects of our life is ever increasing. More so, with access to cheap Internet-enabled devices and proliferation of Social Media applications. Among the variety of information shared, the most relevant, in the context of this paper is how individuals assess their surroundings and how they or their loved ones are affected by adverse events, disasters and crises. Traditional channels of communication often fall behind in providing timely information for emergency responders to formulate an accurate picture of the situation on the ground. The role of Social Media in complimenting such sources of information is thus invaluable and Social Media has been recognised as a key element of assessing evolving situations. Timely, accurate and efficient means to explore and query Social Media is essential for an effective response during emergencies, and hence this gives rise to a Knowledge Management issue. Our paper presents our approach to analysing Real-Time Social Media data streams using Visual Analytic techniques. We discuss the highly visual and interactive approach we employ to provide emergency responders means to access data of interest, supporting different information seeking paradigms.

Item Type: Conference or Workshop Item (Paper)
Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
Depositing User: Suvodeep Mazumdar
Date Deposited: 23 Jan 2018 12:56
Last Modified: 18 Mar 2021 16:30
URI: https://shura.shu.ac.uk/id/eprint/16894

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