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Author
Stephen Kelly
;
Xiubo Zhang
;
Khurshid Ahmad
Title
Mining Multimodal Information on Social Media for Increased Situational Awareness
Type
Conference Article
Year
2017
Publication
Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management
Abbreviated Journal
Iscram 2017
Volume
Issue
Pages
613-622
Keywords
Spatio-temporal
;
Social media analysis
;
Multimodal analysis
;
Geolocation
Abstract
Social media platforms have become a source of high volume, real-time information describing significant events in a timely fashion. In this paper we describe a system for the real-time extraction of information from text and image content in Twitter messages and combine the spatio-temporal metadata of the messages to filter the data stream for emergency events and visualize the output on an interactive map. Twitter messages for a geographic region are monitored for flooding events by analysing the text content and images posted. Events detected are compared with a ground truth to see if information in social media correlates with actual events. We propose an Intrusion Index as part of this prototype to facilitate ethical harvesting of data. A map layer is created by the prototype system that visualises the analysis and filtered Twitter messages by geolocation.
Address
rinity College Dublin, Ireland
Corporate Author
Thesis
Publisher
Iscram
Place of Publication
Albi, France
Editor
Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds
Language
English
Summary Language
English
Original Title
Series Editor
Series Title
Abbreviated Series Title
Series Volume
Series Issue
Edition
ISSN
2411-3387
ISBN
Medium
Track
Social Media Studies
Expedition
Conference
14th International Conference on Information Systems for Crisis Response And Management
Notes
Approved
no
Call Number
Serial
2049
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