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A step towards real-time analysis of major disaster events based on tweets
André Dittrich
author
Christian Lucas
author
2013
Karlsruher Institut fur Technologie
KIT; Baden-Baden
English
The most popular micro blogging platform Twitter has been the topic of a variety of research papers related to disaster and crisis management. As an essential first step and basis for a real-time methodology to exploit Twitter for event detection, localization and ultimately semantic content analysis, a functional model to describe the amount of tweets during a day has been developed. It was derived from a corpus of messages in an exemplary area of investigation. To satisfy the different daily behavior on particular days, two types of days are distinguished in this paper. Moreover, keyword-adjusted data is used to point out the potential of semantic tweet analysis in following steps. The consideration of spatial event descriptions in relevant tweets could significantly improve and accelerate the perception of a disaster. The results from the conducted tests demonstrate the capability of the functional model to detect events with significant social impact in Twitter data.
Information systems
Semantics
Social networking (online)
Crisis management
Event detection
Functional model
Micro-blogging platforms
Real time analysis
Semantic content analysis
Social sensors
Twitter
Disasters
exported from refbase (http://idl.iscram.org/show.php?record=452), last updated on Sun, 09 Aug 2015 05:50:49 +0200
text
http://idl.iscram.org/files/dittrich/2013/452_Dittrich+Lucas2013.pdf
AndreDittrich+ChristianLucas2013
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management
ISCRAM 2013
T. Comes
F
Fiedrich
editor
10th International ISCRAM Conference on Information Systems for Crisis Response and Management
2013
Karlsruher Institut fur Technologie
KIT; Baden-Baden
conference publication
868
874
9783923704804
2411-3387
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