Details
| Original language | English |
|---|---|
| Title of host publication | CIKM 2022 |
| Subtitle of host publication | Proceedings of the 31st ACM International Conference on Information and Knowledge Management |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 4941-4945 |
| Number of pages | 5 |
| ISBN (electronic) | 9781450392365 |
| Publication status | Published - 17 Oct 2022 |
| Event | 31st ACM International Conference on Information and Knowledge Management, CIKM 2022 - Atlanta, United States Duration: 17 Oct 2022 → 21 Oct 2022 |
Publication series
| Name | International Conference on Information and Knowledge Management, Proceedings |
|---|
Abstract
Microblogging platforms such as Twitter, receive massive messages during crisis events. Real-time insights are crucial for emergency response. Hence, there is a need to develop faithful tools for efficiently digesting information. In this paper, we present CrisICSum, a platform for classification and summarization of crisis events. The objective of CrisICSum is to classify user posts during disaster events into different humanitarian classes (i.e., damage, affected people, etc.) and generate summaries of class-level messages. Unlike existing systems, CrisICSum employs an interpretable by design backend classifier. It can generate explanations for output decisions. Besides, the platform allows user feedback on both classification and summarization phases. CrisICSum is designed and run as an easily integrated web application. Backend models are interchangeable. The system can assist users and human organizations in improving response efforts during disaster situations. CrisICSum is available at https://crisicsum.l3s.uni-hannover.de
Keywords
- classification, crisis events, learning with feedback, summarization
ASJC Scopus subject areas
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CIKM 2022 : Proceedings of the 31st ACM International Conference on Information and Knowledge Management. Association for Computing Machinery (ACM), 2022. p. 4941-4945 (International Conference on Information and Knowledge Management, Proceedings).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - CrisICSum
T2 - 31st ACM International Conference on Information and Knowledge Management, CIKM 2022
AU - Nguyen, Thi Huyen
AU - Shaltev, Miroslav
AU - Rudra, Koustav
N1 - Funding Information: This work was partially funded by the DFG Grant NI-1760/1-1, and the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101021866.
PY - 2022/10/17
Y1 - 2022/10/17
N2 - Microblogging platforms such as Twitter, receive massive messages during crisis events. Real-time insights are crucial for emergency response. Hence, there is a need to develop faithful tools for efficiently digesting information. In this paper, we present CrisICSum, a platform for classification and summarization of crisis events. The objective of CrisICSum is to classify user posts during disaster events into different humanitarian classes (i.e., damage, affected people, etc.) and generate summaries of class-level messages. Unlike existing systems, CrisICSum employs an interpretable by design backend classifier. It can generate explanations for output decisions. Besides, the platform allows user feedback on both classification and summarization phases. CrisICSum is designed and run as an easily integrated web application. Backend models are interchangeable. The system can assist users and human organizations in improving response efforts during disaster situations. CrisICSum is available at https://crisicsum.l3s.uni-hannover.de
AB - Microblogging platforms such as Twitter, receive massive messages during crisis events. Real-time insights are crucial for emergency response. Hence, there is a need to develop faithful tools for efficiently digesting information. In this paper, we present CrisICSum, a platform for classification and summarization of crisis events. The objective of CrisICSum is to classify user posts during disaster events into different humanitarian classes (i.e., damage, affected people, etc.) and generate summaries of class-level messages. Unlike existing systems, CrisICSum employs an interpretable by design backend classifier. It can generate explanations for output decisions. Besides, the platform allows user feedback on both classification and summarization phases. CrisICSum is designed and run as an easily integrated web application. Backend models are interchangeable. The system can assist users and human organizations in improving response efforts during disaster situations. CrisICSum is available at https://crisicsum.l3s.uni-hannover.de
KW - classification
KW - crisis events
KW - learning with feedback
KW - summarization
UR - http://www.scopus.com/inward/record.url?scp=85140827678&partnerID=8YFLogxK
U2 - 10.1145/3511808.3557191
DO - 10.1145/3511808.3557191
M3 - Conference contribution
AN - SCOPUS:85140827678
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 4941
EP - 4945
BT - CIKM 2022
PB - Association for Computing Machinery (ACM)
Y2 - 17 October 2022 through 21 October 2022
ER -