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	Author	Hannah Van Wyk; Kate Starbird
	Title	Analyzing Social Media Data to Understand How Disaster-Affected Individuals Adapt to Disaster-Related Telecommunications Disruptions			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	704-717
	Keywords	Telecommunications, Adaptations, Social Media, Cellular Phone Service, Wi-Fi Access.
	Abstract	Information is a critical need during disasters such as hurricanes. Increasingly, people are relying upon cellular and internet-based technology to communicate that information--modalities that are acutely vulnerable to the disruptions to telecommunication infrastructure that are common during disasters. Focusing on Hurricane Maria (2017) and its long-term impacts on Puerto Rico, this research examines how people affected by severe and sustained disruptions to telecommunications services adapt to those disruptions. Leveraging social media trace data as a window into the real-time activities of people who were actively adapting, we use a primarily qualitative approach to identify and characterize how people changed their telecommunications practices and routines--and especially how they changed their locations--to access Wi-Fi and cellular service in the weeks and months after the hurricane. These findings have implications for researchers seeking to better understand human responses to disasters and responders seeking to identify strategies to support affected populations.
	Address	University of Washington; University of Washington
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-64	ISBN	2411-3450	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	hcvw@uw.edu			Approved	no
	Call Number				Serial	2265
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	Author	James A. Reep; Andrea Tapia
	Title	Toward an Organizational Technology Adoption Process (OTAP) for Social Media Integration in a PSAP			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	718-729
	Keywords	Crisis informatics, Organizational Change, Technology Adoption, Social Media, OTAP
	Abstract	Integration of social media in emergency response environments presents specific organizational challenges, such as lack of resources or information credibility. Additionally, there exists individual resistance to change in these environments that could potentially discourage adoption. To identify and understand these challenges, we conducted semi-structured group interviews with emergency call takers and dispatchers. We find that these PSAP operators desire participation and explanation of changes throughout the organizational change process. Participants also articulated they desired training regarding change even when not directly affected. Though change management procedures often call for these strategies, they are commonly overlooked, leaving individuals to imagine worse case scenarios that manifest as additional stress in an already stressful work environment. It is suggested that a formalized change management process which directly addresses the identified challenges within the organizational technology adoption process (OTAP) is needed in order to mitigate undue stress.
	Address	The Pennsylvania State University; The Pennsylvania State University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-65	ISBN	2411-3451	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	jar5757@psu.edu			Approved	no
	Call Number				Serial	2266
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	Author	Lise Ann St. Denis; Amanda Lee Hughes; Jeremy Diaz; Kylen Solvik; Maxwell B. Joseph; Jennifer K. Balch
	Title	'What I Need to Know is What I Don't Know!': Filtering Disaster Twitter Data for Information from Local Individuals			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	730-743
	Keywords	Crisis Informatics, Social Media, Emergency Management, Situational Awareness.
	Abstract	We report on the design, development, and evaluation of a user labeling framework for social media monitoring by emergency responders. By labeling Twitter user accounts based on behavior and content, this novel approach identifies tweets from accounts belonging to Individuals generating Personalized content and captures information that might otherwise be missed. We evaluate the framework using training data from the 2018 Camp, Woolsey, and Hill fires. Approximately 30% of the Individual-Personalized tweets contain first-hand information, providing a rich stream of content for social media monitoring. Because it can quickly eliminate most redundant tweets, this framework could be a critical first step in an end-to-end information extraction pipeline. It may also generalize more easily for new disaster events since it relies on general user account attributes rather than tweet content. We conclude with next steps for refining and evaluating our framework in near real-time during a disaster response.
	Address	CIRES, Earth Lab, University of Colorado, Boulder; Crisis Informatics Lab Brigham Young University; Institute for Computational and Data Sciences, Department of Geography, Penn State University; CIRES, Earth Lab, Department of Geography, University of Colorado, Boulder; CIRES, Earth Lab, University of Colorado, Boulder; CIRES, Earth Lab, Department of Geography, University of Colorado, Boulder
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-66	ISBN	2411-3452	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	Lise.St.Denis@Colorado.edu			Approved	no
	Call Number				Serial	2267
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	Author	Muhammad Imran; Firoj Alam; Umair Qazi; Steve Peterson; Ferda Ofli
	Title	Rapid Damage Assessment Using Social Media Images by Combining Human and Machine Intelligence			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	761-773
	Keywords	Social Media, Damage Assessment, Artificial Intelligence, Image Processing.
	Abstract	Rapid damage assessment is one of the core tasks that response organizations perform at the onset of a disaster to understand the scale of damage to infrastructures such as roads, bridges, and buildings. This work analyzes the usefulness of social media imagery content to perform rapid damage assessment during a real-world disaster. An automatic image processing system, which was activated in collaboration with a volunteer response organization, processed ~280K images to understand the extent of damage caused by the disaster. The system achieved an accuracy of 76% computed based on the feedback received from the domain experts who analyzed ~29K system-processed images during the disaster. An extensive error analysis reveals several insights and challenges faced by the system, which are vital for the research community to advance this line of research.
	Address	Qatar Computing Research Institute Hamad Bin Khalifa University Doha, Qatar; Qatar Computing Research Institute Hamad Bin Khalifa University Doha, Qatar; Qatar Computing Research Institute Hamad Bin Khalifa University Doha, Qatar; Montgomery County, Maryland Community Emergency Response Team United States; Qatar Computing Research Institute Hamad Bin Khalifa University Doha, Qatar
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-68	ISBN	2411-3454	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	mimran@hbku.edu.qa			Approved	no
	Call Number				Serial	2269
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	Author	Sandrine Bubendorff; Caroline Rizza
	Title	The Wikipedia Contribution to Social Resilience During Terrorist Attacks			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	790-801
	Keywords	Wikipedia, Resilience Process, Terrorist Attacks, Social Media.
	Abstract	This paper aims at studying the role of Wikipedia in social resilience processes during terrorist attacks. It discusses how Wikipedia users' specific skills are mobilized in order to make sense of the event as it unfolds. We have conducted an ethnographic analysis of several Wikipedia's terrorist attacks pages as well as interviews with regular Wikipedia's contributors. We document how Wikipedia is used during crisis by readers and contributors. Doing so, we identify a specific pace of contributions which provides reliable information to readers. By discussing the conditions of their trustworthiness, we highlight how historical sources (i.e. traditional media and authorities) support this pace. Our analyses demonstrate that citizens are engaging very quickly in processes of resilience and should be, therefore, considered as relevant partners by authorities when engaging a response to the crisis.
	Address	i3-SES, Telecom Paris, IP Paris, CNRS; i3-SES, Telecom Paris, IP Paris, CNRS
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-70	ISBN	2411-3456	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	sandrine.bubendorff@telecom-paristech.fr			Approved	no
	Call Number				Serial	2271
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	Author	Ferda Ofli; Firoj Alam; Muhammad Imran
	Title	Analysis of Social Media Data using Multimodal Deep Learning for Disaster Response			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	802-811
	Keywords	Multimodal Deep Learning, Multimedia Content, Natural Disasters, Crisis Computing, Social Media.
	Abstract	Multimedia content in social media platforms provides significant information during disaster events. The types of information shared include reports of injured or deceased people, infrastructure damage, and missing or found people, among others. Although many studies have shown the usefulness of both text and image content for disaster response purposes, the research has been mostly focused on analyzing only the text modality in the past. In this paper, we propose to use both text and image modalities of social media data to learn a joint representation using state-of-the-art deep learning techniques. Specifically, we utilize convolutional neural networks to define a multimodal deep learning architecture with a modality-agnostic shared representation. Extensive experiments on real-world disaster datasets show that the proposed multimodal architecture yields better performance than models trained using a single modality (e.g., either text or image).
	Address	Qatar Computing Research Institute Hamad Bin Khalifa University Doha, Qatar; Qatar Computing Research Institute Hamad Bin Khalifa University Doha, Qatar; Qatar Computing Research Institute Hamad Bin Khalifa University Doha, Qatar
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-71	ISBN	2411-3457	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	fofli@hbku.edu.qa			Approved	no
	Call Number				Serial	2272
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	Author	Kamol Roy; MD Ashraf Ahmed; Samiul Hasan; Arif Mohaimin Sadri, P.D.
	Title	Dynamics of Crisis Communications in Social Media: Spatio-temporal and Text-based Comparative Analyses of Twitter Data from Hurricanes Irma and Michael			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	812-824
	Keywords	Social Media, Dynamic Topic Modeling, Irma, Michael, Disaster Management.
	Abstract	Social media platforms play critical roles in information dissemination, communication and co-ordination during different phases of natural disasters as it is crucial to know the type of crisis information being disseminated and user concerns. Large-scale Twitter data from hurricanes Irma (Sept. 2017) and Michael (Oct. 2018) are used here to understand the topic dynamics over time by applying the Dynamic Topic Model, followed by a comparative analyses of the differences in such dynamics for these two hurricane scenarios. We performed a spatio-temporal analyses of user activities with reference to the hurricane center location and wind speed. The findings of spatio-temporal analyses show that differences in hurricane path and the affected regions influence user participation and social media activity. Besides, topic dynamics reveals that situational awareness, disruptions, relief action are among the patterns common for both hurricanes; unlike topics such as hurricane evacuation and political situation that are scenario dependent.
	Address	Department of CECE University of Central Florida; Department of CECE University of Central Florida; Department of CECE University of Central Florida; Department of MDCM Florida International University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-72	ISBN	2411-3458	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	roy.kamol@knights.ucf.edu			Approved	no
	Call Number				Serial	2273
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	Author	Anna Kruspe
	Title	Detecting Novelty in Social Media Messages During Emerging Crisis Events			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	860-871
	Keywords	Social media; Clustering; Novelty; Embeddings
	Abstract	Social media can be a highly valuable source of information during disasters. A crisis' development over time is of particular interest here, as social media messages can convey unfolding events in near-real time. Previous approaches for the automatic detection of information in such messages have focused on a static analysis, not taking temporal changes and already-known information into account. In this paper, we present a novel method for detecting new topics in incoming Twitter messages (tweets) conditional upon previously found related tweets. We do this by first extracting latent representations of each tweet using pre-trained sentence embedding models. Then, Infinite Mixture modeling is used to dynamically cluster these embeddings anew with each incoming tweet. Once a cluster reaches a minimum number of members, it is considered to be a new topic. We validate our approach on the TREC Incident Streams 2019A data set.
	Address	German Aerospace Center (DLR), Jena, Germany
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-76	ISBN	2411-3462	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	anna.kruspe@dlr.de			Approved	no
	Call Number				Serial	2277
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	Author	Marion Lara Tan; Sara Harrison; Julia S. Becker; Emma E.H. Doyle; Raj Prasanna
	Title	Research Themes on Warnings in Information Systems Crisis Management Literature			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1085-1099
	Keywords	Early Warnings Systems, Literature Review, Ethics, Social Media.
	Abstract	Early Warning Systems (EWS) are crucial to mitigating and reducing disaster impacts. Furthermore, technology and information systems (IS) are key to the success of EWSs. This systematic literature review investigates the research topics and themes from the past six years of Information Systems for Crisis Response and Management (ISCRAM) conference proceedings and seeks to identify the research developments and directions for EWSs to steer a discourse to advance the research in this field. Findings from a sample size of 60 papers show that there are technical, social, and topical considerations to using and advancing technology for EWSs. While technology has advanced EWSs to new levels, it is important to consider the influence of technology in the successful operation of EWSs. The results are based on the ISCRAM proceedings literature and may be broader or have different prioritization if a wider disciplinary body of literature was explored. This will be considered in the future.
	Address	Massey University; Massey University; Massey University; Massey University; Massey University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-98	ISBN	2411-3484	Medium
	Track	Visions for Future Crisis Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	M.L.Tan@massey.ac.nz			Approved	no
	Call Number				Serial	2299
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	Author	Nada Matta; Thomas Godard; Guillaume Delatour; Ludovic Blay; Franck Pouzet; Audrey Senator
	Title	Analyzing Social Media in Crisis Management Using Expertise Feedback Modelling			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	17-27
	Keywords	Social Media analysis, TextMining, sentiment analysis, crisis management, decision making
	Abstract	Currently social media are largely used in interactions, especially in crisis situations. We note a big volume of interactions around events. Observing these interactions give information even to alert the existence of an incident, event, or to understand the expansion of a problem. Crisis management actors observe social media to be aware about this type of information in order to consider them in their decisions. Specific organizations are founded in order to observe social media interactions and send their analysis to rescue and crisis management actors. In our work, an experience feedback of this type of organizations (VISOV, a crisis social media analysis association) is capitalized in order to emphasize from one side, main dimensions of this analysis and from another side, to simulate some aspects using TextMining that help to explore big volume of data.
	Address	University of Technology of Troyes; University of Technology of Troyes; University of Technology of Troyes; VISOV; CS Group; ENSOSP
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	AI and Intelligent Systems for Crises and Risks	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	nada.matta@utt.fr			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2309
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	Author	Shangde Gao; Yan Wang; Lisa Platt
	Title	Modeling U.S. Health Agencies' Message Dissemination on Twitter and Users' Exposure to Vaccine-related Misinformation Using System Dynamics			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	333-344
	Keywords	COVID-19, misinformation, social media, System Dynamics, vaccine hesitancy
	Abstract	This research intends to answer: how do (i) generation frequency and (ii) retweeting count of health agencies' messages impact the exposure of the general users to vaccine-related misinformation on Twitter? We creatively employed a Susceptible-Infected-Recovered (SIR) System Dynamics paradigm to model interactions between message dissemination of 168 U.S. health agencies and proportions of users who are at different exposure statuses to misinformation, namely “Susceptible”, “Infected”, or “Recovered” status. The SIR model was built based on the vaccine-relevant tweets posted over November and December in 2020. Our preliminary outcomes suggest that augmenting the generation frequency of agencies' messages and increasing retweeting count can effectively moderate the exposure risk to vaccine-related misinformation. This model illustrates how health agencies may combat vaccine hesitancy through credible information dissemination on social media. It offers a novel approach for crisis informatics studies to model different information categories and the impacted population in the complex digital world.
	Address	University of Florida; University of Florida; University of Florida
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Disaster Public Health & Healthcare Informatics in the Pandemic	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	gao.shangde@ufl.edu			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2337
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	Author	Nathan Elrod; Pranav Mahajan; Monica Katragadda; Shane Halse; Jess Kropczynski
	Title	An Exploration of Methods Using Social Media to Examine Local Attitudes Towards Mask-Wearing During a Pandemic			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	345-358
	Keywords	Social media analytics, situational awareness, sentiment analysis, n-grams, social network analysis
	Abstract	During the COVID-19 health crisis, local public offcials expend considerable energy encouraging citizens to comply with prevention measures in order to reduce the spread of infection. During the pandemic, mask-wearing has been accepted among health offcials as a simple preventative measure; however, some local areas have been more likely to comply than others. This paper explores methods to better understand local attitudes towards mask-wearing as a tool for public health offcials' situational awareness when preparing public messaging campaigns. This exploration compares three methods to explore local attitudes: sentiment analysis, n-grams, and hashtags. We also explore hashtag co-occurrence networks as a starting point to begin the filtering process. The results show that while sentiment analysis is quick and easy to employ, the results oer little insight into specific local attitudes towards mask-wearing, while examining hashtags and hashtag co-occurrence networks may be used a tool for a more robust understanding of local areas when attempting to gain situational awareness.
	Address	University of Cincinnati; University of Cincinnati; University of Cincinnati; University of Cincinnati; University of Cincinnati
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Disaster Public Health & Healthcare Informatics in the Pandemic	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	elrodnj@ucmail.uc.edu			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2338
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	Author	Zainab Akhtar; Ferda Ofli; Muhammad Imran
	Title	Towards Using Remote Sensing and Social Media Data for Flood Mapping			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	536-551
	Keywords	Flood mapping, social media, Satellite imagery, Remote sensing
	Abstract	Ghana's capital, the Greater Accra Metropolitan Area (GAMA) is most vulnerable to flooding due to its high population density. This paper proposes the fusion of satellite imagery, social media, and geospatial data to derive near real-time (NRT) flood maps to understand human activity during a disaster and the extent of infrastructure damage. To that end, the paper presents an automatic thresholding technique for NRT flood mapping using Sentinel-1 images where four different speckle filters are compared using the VV, VH and VV/VH polarization to determine the best polarization(s) for delineating flood extents. The VV and VH bands together on Perona-Malik filtered images achieved the highest accuracy with an F1-score of 81.6%. Moreover, all tweet text and images were found to be located in flooded regions or in very close proximity to a flooded region, thus allowing crisis responders to better understand vulnerable communities and what humanitarian action is required.
	Address	Qatar Computing Research Institute; Qatar Computing Research Institute; Qatar Computing Research Institute
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Geospatial Technologies and Geographic Information Science for Crisis Management (GIS)	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	zakhtar@hbku.edu.qa			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2354
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	Author	Yudi Chen; Angel Umana; Chaowei Yang; Wenying Ji
	Title	Condition Sensing for Electricity Infrastructures in Disasters by Mining Public Topics from Social Media			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	598-608
	Keywords	social media, infrastructure resilience, human behaviors, disaster response
	Abstract	Timely and reliable sensing of infrastructure conditions is critical in disaster management for planning effective infrastructure restorations. Social media, a near real-time information source, has been widely used in the disaster domain for building timely, general situational awareness, such as urgent public needs and donations. However, the employment of social media for sensing electricity infrastructure conditions has yet been explored. This study aims to address the research gap to sense electricity infrastructure conditions through mining public topics from social media. To achieve this purpose, we proposed a systematic and customized approach wherein (1) electricity-related social media data is extracted by the classifier developed based on Bidirectional Encoder Representations from Transformers (BERT); and (2) public topics are modeled with unigrams, bigrams, and trigrams to incorporate the formulaic expressions of infrastructure conditions in social media. Electricity infrastructures in Florida impacted by Hurricane Irma are studied for illustration and demonstration. Results show that the proposed approach is capable of sensing the temporal evolutions and geographic differences of electricity infrastructure conditions.
	Address	George Mason University; George Mason University; George Mason University; George Mason University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Social Media for Disaster Response and Resilience	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	wji2@gmu.edu			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2358
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	Author	Lucia Castro Herrera
	Title	Configuring Social Media Listening Practices in Crisis Management			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	640-654
	Keywords	Social media listening, Practice, Improvisation, Crisis management strategy, Configuration
	Abstract	Social media listening practices are increasingly adopted in crisis management and have become an object of interest for researchers and practitioners alike. This article analyzes how these enactments have been studied in the academic literature. Through a systematic review of the available body of knowledge, features from studies involving depictions of practice were extracted, analyzed, and turned into a narrative using an inductive approach. Strategies of improvisation, overreliance on personal and professional networks, manual work, spontaneous coordination, and re-assigning tasks represent the main findings in the multidisciplinary literature. This article is a consolidated overview of experiences from social media listening in practice beyond listing the benefits of social media as a source of information. Moreover, the paper sets the basis for future studies on the range of possible configurations and institutionalization of disruptive crisis management practices.
	Address	Universitetet i Agder
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Social Media for Disaster Response and Resilience	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	lucia.c.herrera@uia.no			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2361
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	Author	Congcong Wang; Paul Nulty; David Lillis
	Title	Crisis Domain Adaptation Using Sequence-to-Sequence Transformers			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	655-666
	Keywords	Domain Adaptation, Emergency Response, Social media, Transformers
	Abstract	User-generated content (UGC) on social media can act as a key source of information for emergency responders incrisis situations. However, due to the volume concerned, computational techniques are needed to effectively filter and prioritise this content as it arises during emerging events. In the literature, these techniques are trained using annotated content from previous crises. In this paper, we investigate how this prior knowledge can be best leveraged for new crises by examining the extent to which crisis events of a similar type are more suitable for adaptation tonew events (cross-domain adaptation). Given the recent successes of transformers in various language processing tasks, we propose CAST: an approach for Crisis domain Adaptation leveraging Sequence-to-sequence Transformers. We evaluate CAST using two major crisis-related message classification datasets. Our experiments show that ourCAST-based best run without using any target data achieves the state of the art performance in both in-domain and cross-domain contexts. Moreover, CAST is particularly effective in one-to-one cross-domain adaptation when trained with a larger language model. In many-to-one adaptation where multiple crises are jointly used as the source domain, CAST further improves its performance. In addition, we find that more similar events are more likely to bring better adaptation performance whereas fine-tuning using dissimilar events does not help for adaptation. To aid reproducibility, we open source our code to the community.
	Address	University College Dublin; University College Dublin; University College Dublin
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Social Media for Disaster Response and Resilience	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	wangcongcongcc@gmail.com			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2362
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	Author	Valerio Lorini; Carlos Castillo; Steve Peterson; Paola Rufolo; Hemant Purohit; Diego Pajarito; João Porto de Albuquerque; Cody Buntain
	Title	Social Media for Emergency Management: Opportunities and Challenges at the Intersection of Research and Practice			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	772-777
	Keywords	Crisis Informatics, Social Media, Workshop Report, Disaster Management
	Abstract	This paper summarizes key opportunities and challenges identified during the workshop “Social Media for Disaster Risk Management: Researchers Meet Practitioners” which took place online in November 2020. It constitutes a work-in-progress towards identifying new directions for research and development of systems that can better serve the information needs of emergency managers. Practitioners widely recognize the potential of accessing timely information from social media. Nevertheless, the discussion outlined some critical challenges for improving its adoption during crises. In particular, validating such information and integrating it with authoritative information and into more traditional information systems for emergency managers requires further work, and the negative impacts of misinformation and disinformation need to be prevented.
	Address	European Commission, Joint Research Centre (JRC), Ispra, Italy; Universitat Pompeu Fabra, Barcelona, Spain; Community Emergency Response Team, Montgomery County, Maryland, USA; European Commission, Joint Research Centre, Ispra, Italy; George Mason Univers
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Social Media for Disaster Response and Resilience	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	valerio.lorini@ec.europa.eu			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2372
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	Author	Therese Habig; Richard Lüke; Simon Gehlhar; Torben Sauerland; Daniel Tappe
	Title	A Consolidated Understanding of Disaster Community Technologies			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	778-791
	Keywords	Disaster Community Technologies, social media and crowdsourcing, categorization and classification schema, knowledge base
	Abstract	Since the beginning of this millennium, there has been an increasing use of social media and crowdsourcing (SMCS) technologies in disaster situations (Reuter & Kaufhold, 2018). Disaster management organizations and corresponding research are increasingly working on ways of integrating SMCS into the processes of crisis management. In a changing technological landscape to address disasters, and with increasing diversity of stakeholders in disasters, the purpose of this research is to provide an overview of technologies for SMCS within disasters to improve community resilience. The identified and analyzed technologies are summarized under the term “Disaster Community Technologies” (DCT). The paper presents a classification schema (the “DCT-schema”) for those technologies. The goal is to generate an overview of DCT in a rapidly evolving environment and to provide the practical benefit for different stakeholders to identify the right one from the overview.
	Address	safety innovation center; safety innovation center; safety innovation center; safety innovation center; safety innovation center
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Social Media for Disaster Response and Resilience	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	habig@safetyinnovation.center			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2373
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	Author	Julien Coche; Jess Kropczynski; Aurélie Montarnal; Andrea Tapia; Frédérick Bénaben
	Title	Actionability in a Situation Awareness world: Implications for social media processing system design			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	994-1001
	Keywords	Actionable Information, Situation Awareness, Social Media, Crisis Management
	Abstract	The field of crisis informatics now has a decade-long history of designing tools that leverage social media to support decision-makers situation awareness. Despite this history, there remains few examples of these tools adopted by practitioners. Recent fieldwork with public safety answering points and first responders has led to an awareness of the need for tools that gather actionable information, rather than situational awareness alone. This paper contributes to an ongoing discussion about these concepts by proposing a model that embeds the concept of actionable information into Endsley's model of situation awareness. We also extend the insights of this model to the design implications of future information processing systems.
	Address	IMT Mines Albi; University of Cincinnati; Ecole des Mines d'Albi Carmaux; The Pennsylvania State University; Ecole des Mines d'Albi-Carmaux
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Visions for Future Crisis Management	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	coche.emac@gmail.com			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2391
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	Author	Anouck Adrot; Samuel Auclair; Julien Coche; Audrey Fertier; Cécile Gracianne; Aurélie Montarnal
	Title	Using Social Media Data in Emergency Management: A Proposal for a Socio-technical Framework and a Systematic Literature Review			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	470-479
	Keywords	data eco-system; data processing; social media; information management; information technology; emergency organization
	Abstract	Data represents an essential resource to the management of emergencies: organizations have been growingly investing in technologies and resources to lever data as an asset before, during, and after disasters and emergencies. However, research on data usage in emergency management remains fragmented, preventing practitioners and scholars from approaching data comprehensively. To address this gap, this research in progress consists of a systematic review of the literature in a two-steps approach: we first propose a socio-technical framework and use it in an exploratory mapping of the main topics covered by the literature. Our preliminary findings suggest that research on data usage primarily focuses on technological opportunities and affordances and, hence, lacks practical implementation aspects in organizations. The expected contribution is double. First, we contribute to a more comprehensive understanding of data usage in emergency management. Second, we propose future avenues for research on data and resilience.
	Address	Dauphine Recherches en Management; French Geological Survey BRGM; IMT Mines Albi; IMT Mines Albi; French Geological Survey BRGM; IMT Mines Albi
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Data and Resilience: Opportunities and Challenges	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2433
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	Author	Dario Salza; Edoardo Arnaudo; Giacomo Blanco; Claudio Rossi
	Title	A 'Glocal' Approach for Real-time Emergency Event Detection in Twitter			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	570-583
	Keywords	Emergency; Event Detection; Social Media; Twitter; Incremental Clustering
	Abstract	Social media like Twitter offer not only an unprecedented amount of user-generated content covering developing emergencies but also act as a collector of news produced by heterogeneous sources, including big and small media companies as well as public authorities. However, this volume, velocity, and variety of data constitute the main value and, at the same time, the key challenge to implement and automatic detection and tracking of independent emergency events from the real-time stream of tweets. Leveraging online clustering and considering both textual and geographical features, we propose, implement, and evaluate an algorithm to automatically detect emergency events applying a ‘glocal’ approach, i.e., offering a global coverage while detecting events at local (municipality level) scale.
	Address	LINKS Foundation; LINKS Foundation; LINKS Foundation; LINKS Foundation
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Social Media for Crisis Management	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2440
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	Author	Pooneh Mousavi; Cody Buntain
	Title	“Please Donate for the Affected”: Supporting Emergency Managers in Finding Volunteers and Donations in Twitter Across Disasters			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	605-622
	Keywords	social media; crisis in formatics; volunteers; donations; emergency support functions
	Abstract	Despite the outpouring of social support posted to social media channels in the aftermath of disaster, finding and managing content that can translate into community relief, donations, volunteering, or other recovery support is difficult due to the lack of sufficient annotated data around volunteerism. This paper outlines three experiments to alleviate these difficulties. First, we estimate to what degree volunteerism content from one crisis is transferable to another by evaluating the consistency of language in volunteer-and donation-related social media content across 78 disasters. Second it introduces methods for providing computational support in this emergency support function and developing semi-automated models for classifying volunteer-and donation-related social media content in new disaster events. Results show volunteer-and donation-related social media content is sufficiently similar across disasters and disaster types to warrant transferring models across disasters, and we evaluate simple resampling techniques for tuning these models. We then introduce and evaluate a weak-supervision approach to integrate domain knowledge from emergency response officers with machine learningmodelstoimproveclassification accuracy andacceleratethisemergencysupportinnewevents. This method helps to overcome the scarcity in data that we observe related to volunteer-and donation-related social media content.
	Address	University of Maryland, College Park; University of Maryland, College Park
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Social Media for Crisis Management	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2442
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	Author	Thomas Papadimos; Nick Pantelidis; Stelios Andreadis; Aristeidis Bozas; Ilias Gialampoukidis; Stefanos Vrochidis; Ioannis Kompatsiaris
	Title	Real-time Alert Framework for Fire Incidents Using Multimodal Event Detection on Social Media Streams			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	623-635
	Keywords	Alert framework; social media; event detection; kernel density estimation; community detection
	Abstract	The frequency of wildfires is growing day by day due to vastly climate changes. Forest fires can have a severe impact on human lives and the environment, which can be minimised if the population has early and accurate warning mechanisms. To date, social media are able to contribute to early warning with the additional, crowd-sourced information they can provide to the emergency response workers during a crisis event. Nevertheless, the detection of real-world fire incidents using social media data, while filtering out the unavoidable noise, remains a challenging task. In this paper, we present an alert framework for the real-time detection of fire events and we propose a novel multimodal event detection model, which fuses both probabilistic and graph methodologies and is evaluated on the largest fires in Spain during 2019.
	Address	Centre for Research & Technology Hellas Information Technologies Institute Thessaloniki, Greece;Centre for Research & Technology Hellas Information Technologies Institute Thessaloniki, Greece;Centre for Research & Technology Hellas Information Technologie
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Social Media for Crisis Management	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2443
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	Author	Kiran Zahra; Rahul Deb Das; Frank O. Ostermann; Ross S. Purves
	Title	Towards an Automated Information Extraction Model from Twitter Threads during Disasters			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	637-653
	Keywords	Social media threads; Text summarization; Disasters; Lexicons; Information extraction models; Word embeddings
	Abstract	Social media plays a vital role as a communication source during large-scale disasters. The unstructured and informal nature of such short individual posts makes it difficult to extract useful information, often due to a lack of additional context. The potential of social media threads– sequences of posts– has not been explored as a source of adding context and more information to the initiating post. In this research, we explored Twitter threads as an information source and developed an information extraction model capable of extracting relevant information from threads posted during disasters. We used a crowdsourcing platform to determine whether a thread adds more information to the initial tweet and defined disaster-related information present in these threads into six themes– event reporting, location, time, intensity, casualty and damage reports, and help calls. For these themes, we created the respective thematic lexicons from WordNet. Moreover, we developed and compared four information extraction models trained on GloVe, word2vec, bag-of-words, and thematic bag-of-words to extract and summarize the most critical information from the threads. Our results reveal that 70 percent of all threads add information to the initiating post for various disaster-related themes. Furthermore, the thematic bag-of-words information extraction model outperforms the other algorithms and models for preserving the highest number of disaster-related themes.
	Address	University of Zurich; University of Zurich, IBM; University of Twente; University of Zurich
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Social Media for Crisis Management	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2444
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	Author	Carlo Alberto Bono; Barbara Pernici; Jose Luis Fernandez-Marquez; Amudha Ravi Shankar; Mehmet Oguz Mülâyim; Edoardo Nemni
	Title	TriggerCit: Early Flood Alerting using Twitter and Geolocation – A Comparison with Alternative Sources			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	674-686
	Keywords	Social Media; Disaster management; Early Alerting
	Abstract	Rapid impact assessment in the immediate aftermath of a natural disaster is essential to provide adequate information to international organisations, local authorities, and first responders. Social media can support emergency response with evidence-based content posted by citizens and organisations during ongoing events. In the paper, we propose TriggerCit: an early flood alerting tool with a multilanguage approach focused on timeliness and geolocation. The paper focuses on assessing the reliability of the approach as a triggering system, comparing it with alternative sources for alerts, and evaluating the quality and amount of complementary information gathered. Geolocated visual evidence extracted from Twitter by TriggerCit was analysed in two case studies on floods in Thailand and Nepal in 2021. The system respectively returned a large scale and a local scale alert, both in a timely manner and accompanied by a valid geographical description, while providing information complementary to existing disaster alert mechanisms.
	Address	Politecnico di Milano- DEIB;Politecnico di Milano- DEIB;University of Geneva;University of Geneva;Artificial Intelligence Research Institute (IIIA-CSIC); United Nations Satellite Centre (UNOSAT), United Nations Institute for Training and Research (UNITAR)
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Social Media for Crisis Management	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2447
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