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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	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Title	17th ISCRAM Conference Proceedings			Type	Conference Volume
	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	1-1193
	Keywords
	Abstract	The 17th annual conference on Information Systems for Crisis Response and Management (ISCRAM 2020) was scheduled to be held in Blacksburg, Virginia from May 24th-27th, 2020. Unfortunately, due to the widespread impacts of the COVID-19 pandemic, the conference organizers and the ISCRAM Board decided to postpone the conference until May 2021. Even though we could not hold the conference as originally planned, all papers accepted for presentation at ISCRAM 2020 are published in the conference proceedings presented here, and the authors of these papers will have the opportunity to present their papers at the 2021 conference. The 2021 conference will once again be hosted at Virginia Tech in Blacksburg, Virginia, and it will take place during the week of May 23rd, 2021. The theme of ISCRAM 2020 is �Bringing Disaster Resilience into Focus.� These proceedings seek to highlight resilience in Crisis and Emergency Management and to stimulate discussions that enable the design of crisis and emergency management systems that contribute to more resilient organizations and communities. We are pleased to present the accepted papers for ISCRAM 2020, which consist of excellent contributions on a wide range of topics.
	Address
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-92	ISBN	2411-3478	Medium
	Track	Proceedings	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes				Approved	yes
	Call Number				Serial	2307
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	Author	Benjamin Barth; Govinda Chaithanya Kabbinahithilu; Alexandros Bartzas; Spyros Pantazis; Tomaso deCola
	Title	A Content Oriented Information Sharing System for Disaster Management			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	922-927
	Keywords	Information Sharing, Preparation, Response, Content Oriented.
	Abstract	In response to natural and man-made hazards multiple organisations usually are involved in a very complex situation. On the other hand, extreme weather situations due to the climate change create hazards in areas which were considered safe before. In order to improve the capabilities of involved organisations in responding and preparing for disaster events, the availability of an efficient information sharing approach is a key enabler. To this end, we propose a communication system based on a content oriented architecture tailored to disaster management. It includes a catalogue that is offering web services for publishing and subscribing of disaster information and for further collaboration amongst agencies and first responders. Moreover, the considered approach also allows for full content access control and enables a flexible system. The paper shows the current status of the system design. Next steps will include the implementation and evaluation of the approach.
	Address	German Aerospace Center (DLR); German Aerospace Center (DLR); Space Hellas S.A.; Space Hellas S.A.; German Aerospace Center (DLR)
	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	978-1-949373-27-82	ISBN	2411-3468	Medium
	Track	Technologies for First Responders	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	Benjamin.Barth@dlr.de			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2283
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	Author	Michael Holzhüter; Ulrich Meissen
	Title	A Decentralized Reference Architecture for Interconnected Systems in Emergency Management			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	961-972
	Keywords	Civil Protection; Emergency Management; Interoperability; Interconnected Collaboration; Resilient Architecture
	Abstract	Optimal communication and information exchange are key elements for handling complex crises or disaster situations. With the increasing number of heterogeneous ICT systems, also raises the importance of adequate support for interconnectivity and information logistics between stakeholders to thoroughly gather information and to make quick but precise decisions. The main purpose of the information exchange is then to manage the crisis as quickly as possible, to provide full information to protect first responders' health and safety, to optimally dispatch resources, and to ensure coordination between different relief forces. Based on an end user survey with a particular focus on first responders, this paper introduces an evolutionary architecture to enable information exchange in crises situation or disasters. The aim is to provide a decentralized approach among heterogeneous ICT-systems which abstracts from the underlying communication technologies and heterogeneity of connected systems and fulfills the functional and non-functional requirements from end users.
	Address	Hochschule für Technik und Wirtschaft Berlin; Fraunhofer-Institut für Offene Kommunikationssysteme; Hochschule für Technik und Wirtschaft Berlin; Fraunhofer-Institut für Offene Kommunikationssysteme
	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	978-1-949373-27-86	ISBN	2411-3472	Medium
	Track	Technologies for First Responders	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	michael.holzhueter@fokus.fraunhofer.de			Approved	no
	Call Number				Serial	2287
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	Author	Miguel Ramirez de la Huerga; Victor A. Bañuls; Pilar Ortiz Calderon; Rocio Ortiz Calderon
	Title	A Delphi-Based Approach for Analysing the Resilience Level of Local Goverments in a Regional Context			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	602-611
	Keywords	Delphi Analysis; Resilience; Regional Context
	Abstract	This article shows the research process carried out by Regional Government of southern Europe, with more than 8 million citizens, to create an Information System to serve as a diagnostic and certification model for the resilience level of the municipalities of that region. This Information System will allow the local authorities of the regional governments to know in what situation they are and what they should do to improve their resilience level. The research framework is based on the best practices in urban resilience. One of the relevant characteristics of the work is the integration of the knowledge of a very heterogeneous group of experts for the identification of the special needs of the target region that has been articulated through a Delphi process.
	Address	MSIG Smart Management; Universidad Pablo de Olavide; Universidad Pablo de Olavide; Universidad Pablo de Olavide
	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	978-1-949373-27-56	ISBN	2411-3442	Medium
	Track	Planning, Foresight and Risk Analysis	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	miguelramirezdelahuerga@gmail.com			Approved	no
	Call Number				Serial	2257
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	Author	Alexander Staves; Harry Balderstone; Benjamin Green; Antonios Gouglidis; David Hutchison
	Title	A Framework to Support ICS Cyber Incident Response and Recovery			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	638-651
	Keywords	ICS; CNI; Cyber Incident; Guidance; Response and Recovery
	Abstract	During the past decade there has been a steady increase in cyber attacks targeting Critical National Infrastructure. In order to better protect against an ever-expanding threat landscape, governments, standards bodies, and a plethora of industry experts have produced relevant guidance for operators in response to incidents. However, in a context where safety, reliability, and availability are key, combined with the industrial nature of operational systems, advice on the right practice remains a challenge. This is further compounded by the volume of available guidance, raising questions on where operators should start, which guidance set should be followed, and how confidence in the adopted approach can be established. In this paper, an analysis of existing guidance with a focus on cyber incident response and recovery is provided. From this, a work in progress framework is posited, to better support operators in the development of response and recovery operations.
	Address	Lancaster University, UK; Lancaster University, UK; Lancaster University, UK; Lancaster University, UK; Lancaster University, UK
	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	978-1-949373-27-59	ISBN	2411-3445	Medium
	Track	Resilience in Critical Infrastructures	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	a.staves@lancaster.ac.uk			Approved	no
	Call Number				Serial	2260
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	Author	Manon Grest; Matthieu Lauras; Benoit Montreuil
	Title	A Humanitarian Supply Chain Maturity Model			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	613-621
	Keywords	Maturity Assessment, Performance, Humanitarian Organization, Supply Chain.
	Abstract	Over the past decades, humanitarian organizations have largely been criticized for their lack of effectiveness regarding their mission of assisting vulnerable population. However, few researches have investigated what ideal should humanitarian organizations tend toward and the path to undertake in such transformation. In this perspective, this paper intends to overcome this situation by proposing a supply chain maturity model specifically addressed to the humanitarian sector. In the form of a two-dimension matrix, the table aims at: 1) Objectify one organization's position regarding its transformation journey 2) Depending on the organization, identify the specific improvement areas and suggest their sequence. An instantiation of the maturity model is also proposed through the case of the Indonesian red cross.
	Address	IMT Mines Albi; IMT Mines Albi; Georgia Institute of Technology
	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	978-1-949373-27-57	ISBN	2411-3443	Medium
	Track	Practitioner-centered Logistics and Supply Chain Management in Crisis Response	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	manon.grest@mines-albi.fr			Approved	no
	Call Number				Serial	2258
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	Author	Laura Szczyrba; Yang Zhang; Duygu Pamukcu; Derya Ipek Eroglu
	Title	A Machine Learning Method to Quantify the Role of Vulnerability in Hurricane Damage			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	179-187
	Keywords	Vulnerability, Impact, Damage, Machine Learning, Hurricane María.
	Abstract	Accurate pre-disaster damage predictions and post-disaster damage assessments are challenging because of the complicated interrelationships between multiple damage drivers, including various natural hazards, as well as antecedent infrastructure quality and demographic characteristics. Ensemble decision trees, a family of machine learning algorithms, are well suited to quantify the role of social vulnerability in disaster impacts because they provide interpretable measures of variable importance for predictions. Our research explores the utility of an ensemble decision tree algorithm, Random Forest Regression, for quantifying the role of vulnerability with a case study of Hurricane Mar\'ia. The contributing predictive power of eight drivers of structural damage was calculated as the decrease in model mean squared error. A measure of social vulnerability was found to be the model's leading predictor of damage patterns. An additional algorithm, other methods of quantifying variable importance, and future work are discussed.
	Address	Virginia Tech; Virginia Tech; Virginia Tech; Virginia Tech
	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	978-1-949373-27-17	ISBN	2411-3403	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	lszczyrba@vt.edu			Approved	no
	Call Number				Serial	2218
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	Author	Gerasimos Antzoulatos; Panagiotis Giannakeris; Ilias Koulalis; Anastasios Karakostas; Stefanos Vrochidis; Ioannis Kompatsiaris
	Title	A Multi-Layer Fusion Approach For Real-Time Fire Severity Assessment Based on Multimedia Incidents			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	75-89
	Keywords	Crisis Management, Real-Time Fire Severity Assessment, Image Recognition, Object Detection, Semantic Segmentation.
	Abstract	Shock forest fires have short and long-terms devastating impact on the sustainable management and viability of natural, cultural and residential environments, the local and regional economies and societies. Thus, the utilisation of risk-based decision support systems which encapsulate the technological achievements in Geographical Information Systems (GIS) and fire growth simulation models have rapidly increased in the last decades. On the other hand, the rise of image and video capturing technology, the usage mobile and wearable devices, and the availability of large amounts of multimedia in social media or other online repositories has increased the interest in the image understanding domain. Recent computer vision techniques endeavour to solve several societal problems with security and safety domains to be one of the most serious amongst others. Out of the millions of images that exist online in social media or news articles a great deal of them might include the existence of a crisis or emergency event. In this work, we propose a Multi-Layer Fusion framework, for Real-Time Fire Severity Assessment, based on knowledge extracted from the analysis of Fire Multimedia Incidents. Our approach consists of two levels: (a) an Early Fusion level, in which state-of-the-art image understanding techniques are deployed so as to discover fire incidents and objects from images, and (b) the Decision Fusion level which combines multiple fire incident reports aiming to assess the severity of the ongoing fire event. We evaluate our image understanding techniques in a collection of public fire image databases, and generate simulated incidents and feed them to our Decision Fusion level so as to showcase our method's applicability.
	Address	Information Technologies Institute (ITI) – Centre for Research and Technology Hellas (CERTH); Information Technologies Institute (ITI) – Centre for Research and Technology Hellas (CERTH); Information Technologies Institute (ITI) – Centre for Research and Technology Hellas (CERTH);Information Technologies Institute (ITI) – Centre for Research and Technology Hellas (CERTH);Information Technologies Institute (ITI) – Centre for Research and Technology Hellas (CERTH);Information Technologies Institute (ITI) – Centre for Research and Technology Hellas (CERTH)
	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	978-1-949373-27-8	ISBN	2411-3394	Medium
	Track	AI Systems for Crisis and Risks	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	gantzoulatos@iti.gr			Approved	no
	Call Number				Serial	2209
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	Author	Flavio Dusse; Renato Novais; Manoel Mendonça
	Title	A Visual Analytics Based Model for Crisis Management Decision-Making			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	157-166
	Keywords	Crisis Management, Decision-Making, Visual Analytics, Model.
	Abstract	Crisis Management (CM) refers to the ability to deal with crisis tasks in different phases and iterations. People working in a crisis are generally under pressure to make the right decision at the right time. They must process large amounts of data and assimilate the received information in an intuitive way. Visual Analytics (VA) is potentially useful to analyze and understand the huge amount of data in several areas including in a crisis. We propose a model based on VA to support decision-making in CM. The aim of the model is to help visualization designers to create effective VA interfaces, to help crisis managers to make quick and assertive decisions with them. In previous studies, we carried out a survey protocol with a multi-method approach to collect data on crisis related decision-making and analyze all these data qualitatively with formal techniques during the large events held in Brazil in recent years. In this work, we used our previous findings to develop the proposed model. We validated it using the focus group technique. With the new findings, we identified relevant insights on the use of VA for crisis management. We hope that, with these continuous cycles of validation and improvement, the agencies that manage crises might use our model as a reference for building more effective IT decision-making infrastructures based on VA.
	Address	Federal University of Bahia; Federal Institute of Bahia; Federal University of Bahia
	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	978-1-949373-27-15	ISBN	2411-3401	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	dussebr@dcc.ufba.br			Approved	no
	Call Number				Serial	2216
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	Author	Nasik Muhammad Nafi; Avishek Bose; Sarthak Khanal; Doina Caragea; William H. Hsu
	Title	Abstractive Text Summarization of Disaster-Related Documents			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	881-892
	Keywords	Disaster Reporting; Text Summarization; Information Extraction; Reinforcement Learning; Evaluation Metrics
	Abstract	Abstractive summarization is intended to capture key information from the full text of documents. In the application domain of disaster and crisis event reporting, key information includes disaster effects, cause, and severity. While some researches regarding information extraction in the disaster domain have focused on keyphrase extraction from short disaster-related texts like tweets, there is hardly any work that attempts abstractive summarization of long disaster-related documents. Following the recent success of Reinforcement Learning (RL) in other domains, we leverage an RL-based state-of-the-art approach in abstractive summarization to summarize disaster-related documents. RL enables an agent to find an optimal policy by maximizing some reward. We design a novel hybrid reward metric for the disaster domain by combining \underline{Vec}tor Similarity and \underline{Lex}icon Matching (\textit{VecLex}) to maximize the relevance of the abstract to the source document while focusing on disaster-related keywords. We evaluate the model on a disaster-related subset of a CNN/Daily Mail dataset consisting of 104,913 documents. The results show that our approach produces more informative summaries and achieves higher \textit{VecLex} scores compared to the baseline.
	Address	Kansas State University; Kansas State University; Kansas State University; Kansas State University; Kansas 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	978-1-949373-27-78	ISBN	2411-3464	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	nnafi@ksu.edu			Approved	no
	Call Number				Serial	2279
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	Author	Toshihiro Osaragi
	Title	Accessibility Evaluation of Specific Emergency Transportation Roads and Benefits of Seismic Retrofits on Buildings Adjoining Roads			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	143-156
	Keywords	Accessibility of Emergency Vehicle, Specific Emergency Transportation Road, Quake-Resistant-Conversion of Building, Large Earthquake.
	Abstract	Securing the accessibility of emergency vehicles using specific emergency transportation road (SETR) is crucial for the rapid activities of emergency vehicles after a large earthquake. In this paper, we construct a simulation model that describes collapse of roadside buildings and following street blockages, and evaluate the accessibility of emergency vehicles. Performing the simulations, we demonstrate the effects of quake-resistant-conversion of roadside buildings as follows: (1) the accessibility of emergency vehicles using SETR is not good enough under the current situation, but (2) can be significantly improved by performing seismic retrofit of buildings according to seismic index of building structure.
	Address	Tokyo Institute of Technology
	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	978-1-949373-27-14	ISBN	2411-3400	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	osaragi.t.aa@m.titech.ac.jp			Approved	no
	Call Number				Serial	2215
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	Author	Harrison Cole
	Title	Accessible Mitigation Planning: Tactile Hazard Map Design and Evaluation			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	1031-1037
	Keywords	Cartography; Accessibility; Disability; Tactile; Mitigation Planning
	Abstract	While creating a community hazard mitigation plan (HMP) has become recognized as a key component of successful disaster management, significant portions of the process are often inaccessible to people with vision disabilities. Maps in particular are often large, visually dense documents that are printed on two-dimensional paper, or distributed via PDF with no alternate text. For people with profound low vision or who are blind, alternative media is required. The research discussed here proposes that tactile maps may present an accessible and cost-effective medium for representing geospatial data relevant to the hazard mitigation planning process. Using flood insurance rate maps (FIRMs) distributed by the Federal Emergency Management Agency (FEMA) as a starting point, this paper proposes an evaluatory framework for transcribing conventional maps into tactile documents, as well as characterizing users' experiences using them for mitigation planning, directions for future research and generalizing the process for applications in other domains.
	Address	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	978-1-949373-27-93	ISBN	2411-3479	Medium
	Track	Usability and Universal Design of ICT for Emergency Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	harrisoncole@psu.edu			Approved	no
	Call Number				Serial	2294
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	Author	Matti Wiegmann; Jens Kersten; Friederike Klan; Martin Potthast; Benno Stein
	Title	Analysis of Detection Models for Disaster-Related Tweets			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	872-880
	Keywords	Tweet Filtering; Crisis Management; Evaluation Framework
	Abstract	Social media is perceived as a rich resource for disaster management and relief efforts, but the high class imbalance between disaster-related and non-disaster-related messages challenges a reliable detection. We analyze and compare the effectiveness of three state-of-the-art machine learning models for detecting disaster-related tweets. In this regard we introduce the Disaster Tweet Corpus~2020, an extended compilation of existing resources, which comprises a total of 123,166 tweets from 46~disasters covering 9~disaster types. Our findings from a large experiments series include: detection models work equally well over a broad range of disaster types when being trained for the respective type, a domain transfer across disaster types leads to unacceptable performance drops, or, similarly, type-agnostic classification models behave more robust at a lower effectiveness level. Altogether, the average misclassification rate of~3,8\% on performance-optimized detection models indicates effective classification knowledge but comes at the price of insufficient generalizability.
	Address	Bauhaus-Universit\“at Weimar German Aerospace Center (DLR); German Aerospace Center (DLR); German Aerospace Center (DLR); Leipzig University; Bauhaus-Universit\”at Weimar
	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	978-1-949373-27-77	ISBN	2411-3463	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	matti.wiegmann@uni-weimar.de			Approved	no
	Call Number				Serial	2278
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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	Derya Ipek Eroglu; Duygu Pamukcu; Laura Szczyrba; Yang Zhang
	Title	Analyzing and Contextualizing Social Vulnerability to Natural Disasters in Puerto Rico			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	389-395
	Keywords	Data Analytics, Hurricane María, Principal Component Analysis, Social Vulnerability Index.
	Abstract	As the third hurricane the U.S. experienced in 2017, Hurricane María generated impacts that resulted in both short term and long term suffering in Puerto Rico. In this study, we aim to quantify the vulnerability of Puerto Ricans by taking region and society specific characteristics of the island into account. To do this, we follow Cutter et al.'s social vulnerability calculation, which is an inductive approach that aims to represent a society based on its characteristics. We adapted the Social Vulnerability Index (SoVI) for Puerto Rico by using data obtained from the U.S. Census Bureau. We analyzed the newly calculated SoVI for Puerto Rico and compared it with the existing deductive approach developed by the Center for Disease Control (CDC). Our findings show that the new index is able to capture some characteristics that the existing vulnerability index is unable to do.
	Address	Virginia Tech; Virginia Tech; Virginia Tech; Virginia Tech
	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	978-1-949373-27-37	ISBN	2411-3423	Medium
	Track	Data and resilience: opportunities and challenges	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	deryaipek@vt.edu			Approved	no
	Call Number				Serial	2238
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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	Xinyuan Zhang; Nan Li
	Title	Assessment of the Correlation between Extreme Weather Event-Induced Human Mobility Perturbation in Urban Areas and their Spatial Characteristics based on Taxi Trajectories			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	366-380
	Keywords	Extreme Weather Event, Human Mobility, Perturbation, Resilience, Spatial Distribution.
	Abstract	Extreme weather events (EWEs) are significant threats to urban regions. One major reflection of such impact is the EWE-induced perturbation to urban human mobility, which has been documented in a number of recent studies. This study aims to examine the spatial distribution of such perturbation within a city among different areas that are characterized by the type of function and the distance to city center. A case study was conducted on a major rainstorm in the City of Nanjing, China in 2017, based on trajectories of all taxis in the city before and during the rainstorm. It was found that the rainstorm caused decrease in people's travel demand throughout the city, although the magnitude of perturbation and level of resilience notably differed among areas of different functional types. In addition, the urban mobility in areas distant from the city center were relatively less influenced by the rainstorm.
	Address	Tsinghua University; Tsinghua 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	978-1-949373-27-35	ISBN	2411-3421	Medium
	Track	Data and Resilience: Opportunities and Challenges	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	xinyuan-16@mails.tsinghua.edu.cn			Approved	no
	Call Number				Serial	2236
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	Author	Julien Coche; Aurelie Montarnal; Andrea Tapia; Frederick Benaben
	Title	Automatic Information Retrieval from Tweets: A Semantic Clustering Approach			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	134-141
	Keywords	Information Retrieval; Word Embedding; BERT
	Abstract	Much has been said about the value of social media messages for emergency services. The new uses related to these platforms bring users to share information, otherwise unknown in crisis events. Thus, many studies have been performed in order to identify tweets relating to a crisis event or to classify these tweets according to certain categories. However, determining the relevant information contained in the messages collected remains the responsibility of the emergency services. In this article, we introduce the issue of classifying the information contained in the messages. To do so, we use classes such as those used by the operators in the call centers. Particularly we show that this problem is related to named entities recognition on tweets. We then explain that a semi-supervised approach might be beneficial, as the volume of data to perform this task is low. In a second part, we present some of the challenges raised by this problematic and different ways to answer it. Finally, we explore one of them and its possible outcomes.
	Address	IMT Mines Albi; IMT Mines Albi; Penn State University; IMT Mines Albi
	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	978-1-949373-27-13	ISBN	2411-3399	Medium
	Track	AI Systems for Crisis and Risks	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	julien.coche@mines-albi.fr			Approved	no
	Call Number				Serial	2214
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	Author	Eric Rigaud; Anouck Adrot; Frank Fiedrich; Nour Kanaan; Miriam Klein; Farnaz Mahdavian; Yannic Schulte; Marcus Wiens; Frank Schultmann
	Title	Borderland Resilience Studies			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	338-355
	Keywords	Borderland, Resilience, Risk Assessment, Command Control and Coordination.
	Abstract	This article describes the definition and characteristics of borderland resilience studies as an academic field, and precisely its core phenomenon, major themes or components and challenges. The phenomenon of borderland resilience is firstly defined. The results of empirical studies complete the conceptual description. Finally, the article proposes a set of research and development challenges.
	Address	MINES ParisTech, PSL – Research University, CRC, Sophia Antipolis, France; Universite Paris Dauphine, PSL – Research University, Paris, France; Bergische Universitat Wuppertal, Wuppertal, Germany; Universite Paris Dauphine, PSL – Research University, Paris, France; Karlsruhe Institute of Technology (KIT), Karlsruh, Germany; Karlsruhe Institute of Technology (KIT), Karlsruh, Germany; Bergische Universitat Wuppertal, Wuppertal, Germany; Karlsruhe Institute of Technology (KIT), Karlsuh, Germany; Karlsruhe Institute of Technology (KIT), Karlsruh, 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	978-1-949373-27-33	ISBN	2411-3419	Medium
	Track	Data and Resilience: Opportunities and Challenges	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	Eric.rigaud@mines-paristech.fr			Approved	no
	Call Number				Serial	2234
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	Author	Björn J E Johansson
	Title	Boundary Stories – A Systems Perspective on Inter-organizational Learning from Crisis Response Exercises			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	427-434
	Keywords	Inter-organizational Learning, Boundary-crossing Competence, Boundary Discourse, Systems Science, Complex Adaptive Systems.
	Abstract	Inter-organizational exercises are commonly conducted with the aim to improve overall crisis response system performance. However, there are challenges associated with establishing learning goals for, designing and evaluating inter-organizational exercises. This work-in-progress paper applies a systems science perspective on the Swedish crisis response system with the aim to understand (1) what kind of a system it is (2) what properties or mechanisms enable good system performance?, and, (3) what are desirable training goals for improving the crisis response capability of the Swedish crisis response system? The author suggests that (1) the Swedish crisis response system can be seen as a Complex Adaptive System, and (2) that the focus must shift from exercising organizations' intra-organizational capabilities to adaptive capabilities. The latter can be achieved by designing exercises comprising boundary-crossing activities with the purpose to support the buildup of boundary-crossing competence. Cross-organizational learning can be achieved by identifying, documenting and disseminating boundary stories.
	Address	Swedish Defence Research Agency
	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	978-1-949373-27-41	ISBN	2411-3427	Medium
	Track	Enhancing resilient response in inter-organizational contexts: Learning from experience	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	bjorn.j.e.johansson@foi.se			Approved	no
	Call Number				Serial	2242
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	Author	Duygu Pamukcu; Christopher W. Zobel; Andrew Arnette
	Title	Characterizing Social Community Structures in Emergency Shelter Planning			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	228-236
	Keywords	Evacuation Planning; Sheltering; Simulation; Social Network; Group Behavior
	Abstract	During emergencies, it is often necessary to evacuate vulnerable people to safer places to reduce loss of lives and cope with human suffering. Shelters are publically available places to evacuate, especially for people who do not have any other choices. This paper overviews emergency shelter planning in disaster mitigation and preparation and discusses the need for better responding to people who need to evacuate during emergencies. Recent evacuation studies pay attention to integrating social factors into evacuation modeling for better prediction of evacuation decisions. Our goal is to address the impact of social behavior on the sheltering choices of evacuees and to explore the potential contributions of including social network characteristics in the decision-making process of authorities. We present the shelter utilization problem in South Carolina during Hurricane Florence and discuss an agent-based modeling approach that considers social community structures in modeling the shelter choice behavior of socially connected individuals.
	Address	Virginia Tech; Virginia Tech; University of Wyoming
	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	978-1-949373-27-22	ISBN	2411-3408	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	duygu@vt.edu			Approved	no
	Call Number				Serial	2223
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	Author	Rahul Pandey; Brenda Bannan; Hemant Purohit
	Title	CitizenHelper-training: AI-infused System for Multimodal Analytics to assist Training Exercise Debriefs at Emergency Services			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	42-53
	Keywords	Training Exercise, Emergency Preparedness, AI system, Learning Analytics, Responder Training.
	Abstract	The adoption of Artificial Intelligence (AI) technologies across various real-world applications for human performance augmentation demonstrates an unprecedented opportunity for emergency management. However, the current exploration of AI technologies such as computer vision and natural language processing is highly focused on emergency response and less investigated for the preparedness and mitigation phases. The training exercises for emergency services are critical to preparing responders to perform effectively in the real-world, providing a venue to leverage AI technologies. In this paper, we demonstrate an application of AI to address the challenges in augmenting the performance of instructors or trainers in such training exercises in real-time, with the explicit aim of reducing cognitive overload in extracting relevant knowledge from the voluminous multimodal data including video recordings and IoT sensor streams. We present an AI-infused system design for multimodal stream analytics and lessons from its use during a regional training exercise for active violence events.
	Address	George Mason University; George Mason University; George Mason 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	978-1-949373-27-5	ISBN	2411-3391	Medium
	Track	AI Systems for Crisis and Risks	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	rpandey4@gmu.edu			Approved	no
	Call Number				Serial	2206
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	Author	Jean-Paul Monet; Pierre Schaller; Sergio Pirone; Marc Castellnou Ribau; Stéphane Poyau; Marc Dumas
	Title	Civil Protection in Europe: Towards a Unified Command System? Lessons Learned, Studies and Ideas About Change Management			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	315-325
	Keywords	Crisis Management, Incident, Command and Control System, Interoperability, European Union.
	Abstract	After the summer 2017 deadly wildfires in Portugal, President Juncker of the European Commission asked for “a stronger European Union (EU)”, clearly targeting civil protection management. This wish found achievement in the March 2019 guidance to establish a reserve of EU response capacities called “rescEU”, integrated into the jurisdictional basis of EU civil protection. However, the authors regret the ambition of this plan has not been fulfilled. Due to some very “European constraints” this “new deal” has introduced only small changes in terms of resources and knowledge management. In each of the past several years, climate change has brought new examples of fatal natural disasters: wildfires in Sweden, and Greece, and flash floods in Spain and France. Because of this continuous rise in disasters, and based on some lessons learned, the authors stress that it's now time to shape a project to improve European Civil Protection. The idea is to move from the already good modular system of the EU Civil Protection Mechanism to an integrated, robust, and unique European Command System, which clearly must be fully interoperable with other existing mechanisms (US ICS, UNOCHA...).
	Address	Bouches-du-Rhône Fire department; National French Fire Academy (Ensosp); Corpo forestal Piemonte, Italy; Pau Costa foundation, Spain; Landes Fire department; Bouches-du-Rhône Fire department
	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	978-1-949373-27-31	ISBN	2411-3417	Medium
	Track	Command & Control Studies	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	jpmonet@sdis13.fr			Approved	no
	Call Number				Serial	2232
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	Author	Jeremy Diaz; Lise St. Denis; Maxwell B. Joseph; Kylen Solvik; Jennifer K. Balch
	Title	Classifying Twitter Users for Disaster Response: A Highly Multimodal or Simple Approach?			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	774-789
	Keywords	User Classification, Disaster Response, Twitter, Model Comparison, Multimodal Deep Learning.
	Abstract	We report on the development of a classifier to identify Twitter users contributing first-hand information during a disaster. Identifying such users helps social media monitoring teams identify critical information that might otherwise slip through the cracks. A parallel study (St. Denis et al., 2020) demonstrates that Twitter user filtering creates an information-rich stream of content, but the best way to approach this task is unexplored. A user's profile contains many different “modalities” of data, including numbers, text, and images. To integrate these different data types, we constructed a multimodal neural network that combines the loss function of all modalities, and we compared the results to many individual unimodal models and a decision-level fusion approach. Analysis of the results suggests that unimodal models acting on Twitter users' recent tweets are sufficient for accurate classification. We demonstrate promising classification of Twitter users for crisis response with methods that are (1) easy to implement and (2) quick to both optimize and infer.
	Address	Institute for Computational and Data Sciences, The Penn State University Department of Geography, The Penn State University; CIRES, Earth Lab, University of Colorado, Boulder; CIRES, Earth Lab, University of Colorado, Boulder; CIRES, Earth Lab, Department of Geography, 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	978-1-949373-27-69	ISBN	2411-3455	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	jad6655@psu.edu			Approved	no
	Call Number				Serial	2270
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