Records |
Author |
Axel Schulz; Tung Dang Thanh; Heiko Paulheim; Immanuel Schweizer |
Title |
A fine-grained sentiment analysis approach for detecting crisis related microposts |
Type |
Conference Article |
Year |
2013 |
Publication |
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2013 |
Volume |
|
Issue |
|
Pages |
846-851 |
Keywords |
Artificial intelligence; Information systems; Learning systems; Risk management; Social networking (online); Amount of information; Emergency management; Microposts; Real-time information; Sentiment analysis; Situational awareness; Systematic evaluation; Twitter; Data mining |
Abstract |
Real-time information from microposts like Twitter is useful for applications in the crisis management domain. Currently, that potentially valuable information remains mostly unused by the command staff, mainly because the sheer amount of information cannot be handled efficiently. Sentiment analysis has been shown as an effective tool to detect microposts (such as tweets) that contribute to situational awareness. However, current approaches only focus on two or three emotion classes. But using only tweets with negative emotions for crisis management is not always sufficient. The amount of remaining information is still not manageable or most of the tweets are irrelevant. Thus, a more fine-grained differentiation is needed to identify relevant microposts. In this paper, we show the systematic evaluation of an approach for sentiment analysis on microposts that allows detecting seven emotion classes. A preliminary evaluation of our approach in a crisis related scenario demonstrates the applicability and usefulness. |
Address |
Technische Universität Darmstadt, Germany; Universität Mannheim, Germany |
Corporate Author |
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Thesis |
|
Publisher |
Karlsruher Institut fur Technologie |
Place of Publication |
KIT; Baden-Baden |
Editor |
T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
|
ISSN |
2411-3387 |
ISBN |
9783923704804 |
Medium |
|
Track |
Social Media |
Expedition |
|
Conference |
10th International ISCRAM Conference on Information Systems for Crisis Response and Management |
Notes |
|
Approved |
no |
Call Number |
|
Serial |
927 |
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Author |
Axel Schulz; Heiko Paulheim; Florian Probst |
Title |
Crisis information management in the Web 3.0 age |
Type |
Conference Article |
Year |
2012 |
Publication |
ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2012 |
Volume |
|
Issue |
|
Pages |
|
Keywords |
Information management; Information systems; Risk management; World Wide Web; Crowdsourcing; Emergency management; Linked open datum; Participatory Sensing; Social media; Data handling |
Abstract |
The effectiveness of emergency response largely depends on having a precise, up-to-date situational picture. With the World Wide Web having evolved from a small read-only text collection to a large-scale collection of socially created data accessible both to machines and humans alike, with the advent of social media and ubiquitous mobile applications, new sources of information are available. Currently, that potentially valuable information remains mostly unused by the command staff, mainly because the sheer amount of information cannot be handled efficiently. In this paper, we show an approach for turning massive amounts of unstructured citizen-generated content into relevant information supporting the command staff in making better informed decisions. We leverage Linked Open Data and crowdsourcing for processing data from social media, and we show how the combination of human intelligence in the crowd and automatic approaches for enhancing the situational picture with Linked Open Data will lead to a Web 3.0 approach for more efficient information handling in crisis management. © 2012 ISCRAM. |
Address |
Technische Universität, Darmstadt, Germany; SAP Research, Germany |
Corporate Author |
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Thesis |
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Publisher |
Simon Fraser University |
Place of Publication |
Vancouver, BC |
Editor |
L. Rothkrantz, J. Ristvej, Z.Franco |
Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9780864913326 |
Medium |
|
Track |
Intelligent Systems |
Expedition |
|
Conference |
9th International ISCRAM Conference on Information Systems for Crisis Response and Management |
Notes |
|
Approved |
no |
Call Number |
|
Serial |
203 |
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