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Towards an Interpretable Approach to Classify and Summarize Crisis Events from Microblogs
2022
Proceedings of the ACM Web Conference 2022
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This paper proposes an interpretable classification-summarization framework that first classifies tweets into different disaster-related categories and then summarizes those tweets. ...
Unlike existing work, our classification model can provide explanations or rationales for its decisions. ...
CONCLUSION This paper presents an interpretable classification and summarization framework for disaster events on Twitter. ...
doi:10.1145/3485447.3512259
fatcat:oevt252yhfd7fbqh6sw32zac7m
Geographic Situational Awareness: Mining Tweets for Disaster Preparedness, Emergency Response, Impact, and Recovery
2015
ISPRS International Journal of Geo-Information
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Social media data have emerged as a new source for detecting and monitoring disaster events. ...
during a natural disaster and referencing the findings from the relevant literature and official government procedures involving different disaster stages. ...
Acknowledgement We would like to thank Caitlin McKown for the help and support during this research. Work performed under this project has been funded by the UW-Madison WARF grant # PRJ93XF. ...
doi:10.3390/ijgi4031549
fatcat:jthenqdbfrh4ril2ocynx5kxzm
Natural Disasters Detection in Social Media and Satellite imagery: a survey
[article]
2019
arXiv
pre-print
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Furthermore, we also review benchmarking datasets available for the evaluation of disaster detection frameworks. ...
Satellite imagery has also been widely explored for disasters analysis. ...
For the training stage the authors adopt a modified VGGNet [112] model. ...
arXiv:1901.04277v1
fatcat:5zidbp3owbe6ld33pt4j3aijtq
A novel framework for assessing the criticality of retrieved information
2022
International Journal of Computing and Digital Systems
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Taking advantage of Deep Learning (DL) and Natural Language Processing (NLP) techniques, this paper proposes a novel framework for retrieving critical information from Twitter to manage emergencies effectively ...
The proposed framework classifies the tweets into relevant and irrelevant classes using Bidirectional Encoder Representations from Transformers (BERT). ...
Acknowledgment We thank the anonymous annotators for annotating the dataset utilized in the study. Moreover, we thank the anonymous reviewers for their valuable suggestions. ...
doi:10.12785/ijcds/1101100
fatcat:wz4uc236vret3c5i7otmmmmtcu
DCBRTS: A Classification-Summarization Approach for Evolving Tweet Streams in Multiobjective Optimization Framework
2021
IEEE Access
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In the first stage, tweet category is identified as either situational or non-situational using a classification framework. ...
CONCLUSION The current article presents a novel framework for classification followed by summarization to handle the continuous tweet streams posted during disaster events. ...
doi:10.1109/access.2021.3120112
fatcat:nofzfl4gwjckbfllgm6szdwfyu
Neural Networks and Support Vector Machine based Approach for Classifying Tweets by Information Types at TREC 2018 Incident Streams Task
2018
Text Retrieval Conference
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We consider a rich set of hand-crafted features to train our multi-class SVM classifier, whereas a pre-trained word2vec model is used for the DNN based classifiers. ...
Moreover, we introduce a set of rules based on the language of tweets, exploiting indicator terms, and WH-orientation of tweets for our rule-based classifier. ...
Acknowledgments This research was supported by MEXT KAKENHI, Grant-in-Aid for Scientific Research (B), Grant Number 17H01746. ...
dblp:conf/trec/ChySA18
fatcat:s3pa4f6ncvgrvlnv52nm2qmn7u
Time-Critical Geolocation for Social Good
[chapter]
2020
Lecture Notes in Computer Science
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I specifically aim to study the Location Mention Prediction problem in which the system has to extract location mentions in tweets and pin them on the map. ...
Nevertheless, due to several challenges, the current fully-automated processing methods are not yet mature enough for deployment in real scenarios. ...
This work was made possible by GSRA grant# GSRA5-1-0527-18082 from the Qatar National Research Fund (a member of Qatar Foundation). ...
doi:10.1007/978-3-030-45442-5_82
fatcat:lrmzieeiwbgadlnidy6y3kyl4u
Automated machine learning approaches for emergency response and coordination via social media in the aftermath of a disaster: A review
2021
IEEE Access
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This review would help researchers in choosing further research topics pertaining to automated approaches for actionable information classification and disaster coordination and would help the emergency ...
Regardless of the kind of disaster event, whether it is a hurricane, a flood, an earthquake or a man-made disaster event like a riot or a terrorist attack, social media platforms like Facebook, Twitter ...
The authors published a large dataset of 524 million multi-lingual tweets from various countries pertaining to a COVID-19 disaster event. ...
doi:10.1109/access.2021.3074819
fatcat:2ebym34ewjcgzn7im7gaac7udy
Sympathy Detection in Disaster Twitter Data
2019
International Conference on Information Systems for Crisis Response and Management
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Specifically, we propose a refined word embedding technique in terms of various pre-trained word vector models and show great performance of CNNs that use these refined embeddings in the sympathy tweet ...
classification task. ...
We also wish to thank our anonymous reviewers for their constructive comments. ...
dblp:conf/iscram/LiPCCT19
fatcat:esx6sgbnsrhl3gpmnb6bz6xlg4
Tackling the Challenges of Situational Awareness Extraction in Twitter with an Adaptive Approach
2015
Procedia Engineering
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Furthermore, we introduce a novel data model based on a three-label classification scheme to describe the composition of the data-stream. ...
Despite interest in the development of extraction systems for such information, little effort has been put towards systemic methods for obtaining all posts pertaining to a disaster from the live Twitter ...
This is true for disaster and non-disaster tweets alike [8] . ...
doi:10.1016/j.proeng.2015.06.085
fatcat:skzll667hzcahipljpztaqh6xu
Exploit Social Relations in Sentiment Analysis of Social Media Content for Disaster Management
2018
Americas Conference on Information Systems
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The proposed study extends previous work substantially by looking at a larger set of social relations and focusing on different communication goals at each stage of disaster management. ...
The study can help formulate a better understanding of how opinions are formed and propagated during disasters, thus allow stakeholders to strategize for better communication. ...
different stage of a disaster. ...
dblp:conf/amcis/ShivarkarW18
fatcat:ahb5a5e6izfmloygd4c5jtmwkm
Deep Learning Approaches for Multi-Label Incidents Classification from Twitter Textual Information
2022
Journal of Information Systems Engineering and Business Intelligence
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Results: CNN paired with NeuroNER yield the best results for multi-label classification compared to CLSTM and RCNN. ...
Conclusion: CNN was proven to be more effective with an average precision value of 88.54% for multi-label incidents classification. ...
Funding: research received no specific grant from any funding agency.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.20473/jisebi.8.1.31-41
fatcat:3ln4cp3lrfcc5o227iebj6g2nm
Use of Social Media Data in Disaster Management: A Survey
2021
Future Internet
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To the best of our knowledge, there is no published literature on social media data management and analysis that identifies the research problems and provides a research taxonomy for the classification ...
In this paper, we provide a survey of how social media data contribute to disaster management and the methodologies for social media data management and analysis in disaster management. ...
Used a support vector machine (SVM) for the tweet classification and a probabilistic model for location estimation. ...
doi:10.3390/fi13020046
fatcat:2p5xerp3cngkhb2myi7vmwe4pm
Analytics and Evolving Landscape of Machine Learning for Emergency Response
[chapter]
2019
Zenodo
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Based on the literature review, we observe a trend to move from narrow in scope, problem-specific applications of data mining and machine learning to solutions that address a wider spectrum of problems ...
The purpose of this chapter is to discuss a hybrid crowdsourcing and real-time ma- chine learning approaches to rapidly process large volumes of data for emergency response in a time-sensitive manner.We ...
Acknowledgements The work is funded from the Research Council of Norway (RCN) and the Norwegian Centre for International Cooperation in Education (SiU) grant through INT-PART programme. ...
doi:10.5281/zenodo.5106014
fatcat:ui7kmryflbaljkim4u2ync2dqi
Designing Multimodal Interactive Dashboard of Disaster Management Systems
2022
Sensors
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In the aftermath of a disaster, a society's overall growth, resources, and economy are greatly affected as they cause damages from minor to huge proportions. ...
The proposed interactive multimodal dashboards complement the existing techniques of collecting textual, image, audio, and video emergency information and their classifications for usable presentation. ...
Acknowledgments: The authors extend their appreciation to the Deputyship for Research and Innovation, Ministry of Education in Saudi Arabia. ...
doi:10.3390/s22114292
pmid:35684913
pmcid:PMC9185355
fatcat:laavygep6jbyhcnobqu3caikqa
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