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	Author	Andrea Zielinski; Stuart E. Middleton; Laurissa N. Tokarchuk; Xinyue Wang
	Title	Social media text mining and network analysis for decision support in natural crisis management			Type	Conference Article
	Year	2013	Publication	ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	ISCRAM 2013
	Volume		Issue		Pages	840-845
	Keywords	Arts computing; Decision support systems; Information systems; Software prototyping; Decision supports; Link analysis; Social media; Text mining; Vgi; Web Mining; Data mining
	Abstract	A core issue in crisis management is to extract from the mass of incoming information what is important for situational awareness during mass emergencies. Based on a case study we develop a prototypical application, TweetComp1, which is integrated into the decision-support component of a Tsunami early warning system and demonstrates the applicability of our approach. This paper describes four novel approaches using focused twitter crawling, trustworthiness analysis, geo-parsing, and multilingual tweet classification in the context of how they could be used for monitoring crises. The validity of our state-of-the art text mining and network analysis technologies will be verified in different experiments based on a human annotated gold standard corpus.
	Address	Fraunhofer Institute of Optronics, System Technologies and Image Exploitation, Karlsruhe, Germany; IT Innovation Centre, University of Southampton, Southampton, United Kingdom; School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom
	Corporate Author				Thesis
	Publisher	Karlsruher Institut fur Technologie	Place of Publication	KIT; Baden-Baden	Editor	T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	9783923704804	Medium
	Track	Social Media	Expedition		Conference	10th International ISCRAM Conference on Information Systems for Crisis Response and Management
	Notes				Approved	no
	Call Number				Serial	1160
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	Author	Shalini Priya; Manish Bhanu; Sourav Kumar Dandapat; Joydeep Chandra
	Title	Mirroring Hierarchical Attention in Adversary for Crisis Task Identification: COVID-19, Hurricane Irma			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	609-620
	Keywords	Covid-19, Hurricane, Adversarial, Hierarchical attention, Support, Infrastructure Damage
	Abstract	A surge of instant local information on social media serves as the first alarming tone of need, supports, damage information, etc. during crisis. Identifying such signals primarily helps in reducing and suppressing the substantial impacts of the outbreak. Existing approaches rely on pre-trained models with huge historic information as well ason domain correlation. Additionally, existing models are often task specific and need auxiliary feature information.Mitigating these limitations, we introduce Mirrored Hierarchical Contextual Attention in Adversary (MHCoA2) model that is capable to operate under varying tasks of different crisis incidents. MHCoA2 provides attention by capturing contextual correlation among words to enhance task identification without relying on auxiliary information.The use of adversarial components and an additional feature extractor in MHCoA2 enhances its capability to achievehigher performance. MHCoA2 reports an improvement of 5-8% in terms of standard metrics on two real worldcrisis incidents over state-of-the-art.
	Address	Indian Institute of Technology Patna; Indian Institute of Technology Patna; Indian Institute of Technology Patna; Indian Institute of Technology Patna
	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	shalini.pcs16@iitp.ac.in			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2359
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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	Michael Aupetit; Muhammad Imran
	Title	Interactive Monitoring of Critical Situational Information on Social Media			Type	Conference Article
	Year	2017	Publication	Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management	Abbreviated Journal	Iscram 2017
	Volume		Issue		Pages	673-683
	Keywords	Social media; disaster management; information visualization
	Abstract	According to many existing studies, the data available on social media platforms such as Twitter at the onset of a crisis situation could be useful for disaster response and management. However, making sense of this huge data coming at high-rate is still a challenging task for crisis managers. In this work, we present an interactive social media monitoring tool that uses a supervised classification engine and natural language processing techniques to provide a detailed view of an on-going situation. The tool allows users to apply various filtering options using interactive timelines, critical entities, and other logical operators to get quick access to situational information. The evaluation of the tool conducted with crisis managers shows its significance for situational awareness and other crisis management related tasks.
	Address	Qatar Computing Research Institute, HBKU Doha, Qatar
	Corporate Author				Thesis
	Publisher	Iscram	Place of Publication	Albi, France	Editor	Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN		Medium
	Track	Social Media Studies	Expedition		Conference	14th International Conference on Information Systems for Crisis Response And Management
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2055
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	Author	Yang Zhang; William Drake; Yuhong Li; Christopher Zobel; Margaret Cowell
	Title	Fostering Community Resilience through Adaptive Learning in a Social Media Age: Municipal Twitter Use in New Jersey following Hurricane Sandy			Type	Conference Article
	Year	2015	Publication	ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	ISCRAM 2015
	Volume		Issue		Pages
	Keywords	Adaptive learning; disaster resilience; Hurricane Sandy; social media; Twitter
	Abstract	Adaptive learning capacity is a critical component of community resilience that describes the ability of a community to effectively gauge its vulnerability to the external environment and to make appropriate changes to its coping strategies. Traditionally, the relationship between government and community learning was framed within a deterministic paradigm. Learning outcomes were understood to result from the activities of central actors (i.e., government) and flow passively into the community. The emergence of social media is fundamentally changing the ways organizations and individuals collect and share information. Despite its growing acceptance, it remains to be determined how this shift in communication will ultimately affect community adaptive learning, and therefore, community resilience. This paper presents the initial results of a mixed-methods research effort that examined the use of Twitter in local municipalities from Monmouth County, NJ after Hurricane Sandy. Using a conceptual model of organizational learning, we examine the learning outcomes following the Hurricane Sandy experience.
	Address
	Corporate Author				Thesis
	Publisher	University of Agder (UiA)	Place of Publication	Kristiansand, Norway	Editor	L. Palen; M. Buscher; T. Comes; A. Hughes
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	9788271177881	Medium
	Track	Social Media Studies	Expedition		Conference	ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management
	Notes				Approved	yes
	Call Number				Serial	1236
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	Author	Paige Maas; Shankar Iyer; Andreas Gros; Wonhee Park; Laura McGorman; Chaya Nayak; P. Alex Dow
	Title	Facebook Disaster Maps: Aggregate Insights for Crisis Response & Recovery			Type	Conference Article
	Year	2019	Publication	Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management	Abbreviated Journal	Iscram 2019
	Volume		Issue		Pages
	Keywords	crisis mapping, crisis informatics, GIS, social media
	Abstract	After a natural disaster or other crisis, humanitarian organizations need to know where affected people are located and what resources they need. While this information is difficult to capture quickly through conventional methods, aggregate usage patterns of social media apps like Facebook can help fill these information gaps. In this paper, we describe the data and methodology that power Facebook Disaster Maps. These maps utilize information about Facebook usage in areas impacted by natural hazards, producing aggregate pictures of how the population is affected by and responding to the hazard. The maps include insights into evacuations, cell network connectivity, access to electricity, and long-term displacement. In addition to descriptions and examples of each map type, we describe the source data used to generate the maps, and efforts taken to ensure the security and privacy of Facebook users. We also describe limitations of the current methodologies and opportunities for improvement.
	Address	Facebook, United States of America
	Corporate Author				Thesis
	Publisher	Iscram	Place of Publication	Valencia, Spain	Editor	Franco, Z.; González, J.J.; Canós, J.H.
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-84-09-10498-7	Medium
	Track	T8- Social Media in Crises and Conflicts	Expedition		Conference	16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019)
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	1912
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	Author	Muhammad Imran; Carlos Castillo; Jesse Lucas; Patrick Meier; Jakob Rogstadius
	Title	Coordinating human and machine intelligence to classify microblog communications in crises			Type	Conference Article
	Year	2014	Publication	ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	ISCRAM 2014
	Volume		Issue		Pages	712-721
	Keywords	Information systems; Classification accuracy; Disaster response; Human intelligence; Large-scale datum; Machine computations; Machine intelligence; Real-world datasets; Supervised classifiers; Artificial intelligence
	Abstract	An emerging paradigm for the processing of data streams involves human and machine computation working together, allowing human intelligence to process large-scale data. We apply this approach to the classification of crisis-related messages in microblog streams. We begin by describing the platform AIDR (Artificial Intelligence for Disaster Response), which collects human annotations over time to create and maintain automatic supervised classifiers for social media messages. Next, we study two significant challenges in its design: (1) identifying which elements must be labeled by humans, and (2) determining when to ask for such annotations to be done. The first challenge is selecting the items to be labeled by crowd sourcing workers to maximize the productivity of their work. The second challenge is to schedule the work in order to reliably maintain high classification accuracy over time. We provide and validate answers to these challenges by extensive experimentation on real world datasets.
	Address	Qatar Computing Research Institute, Qatar; University of Madeira, Portugal
	Corporate Author				Thesis
	Publisher	The Pennsylvania State University	Place of Publication	University Park, PA	Editor	S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih.
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	9780692211946	Medium
	Track	Social Media in Crisis Response and Management	Expedition		Conference	11th International ISCRAM Conference on Information Systems for Crisis Response and Management
	Notes				Approved	no
	Call Number				Serial	612
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	Author	Gayane Shalunts; Gerhard Backfried; Prinz Prinz
	Title	Sentiment analysis of German social media data for natural disasters			Type	Conference Article
	Year	2014	Publication	ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	ISCRAM 2014
	Volume		Issue		Pages	752-756
	Keywords	Disasters; Information systems; First responders; Integral part; Media analysis; Multiple languages; Natural disasters; Sentiment analysis; Social media; Social media datum; Data mining
	Abstract	Analysis of social media and traditional media provides significant information to first responders in times of natural disasters. Sentiment analysis, particularly of social media originating from the affected population, forms an integral part of multifaceted media analysis. The current paper extends an existing methodology to the domain of natural disasters, broadens the support of multiple languages and introduces a new manner of classification. The performance of the approach is evaluated on a recently collected dataset manually annotated by three human annotators as a reference. The experiments show a high agreement rate between the approach taken and the annotators. Furthermore, the paper presents the initial application of the resulting technology and models to sentiment analysis of social media data in German, covering data collected during the Central European floods of 2013.
	Address	SAIL LABS Technology AG, Vienna, Austria
	Corporate Author				Thesis
	Publisher	The Pennsylvania State University	Place of Publication	University Park, PA	Editor	S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih.
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	9780692211946	Medium
	Track	Social Media in Crisis Response and Management	Expedition		Conference	11th International ISCRAM Conference on Information Systems for Crisis Response and Management
	Notes				Approved	no
	Call Number				Serial	940
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	Author	Xukun Li; Doina Caragea; Cornelia Caragea; Muhammad Imran; Ferda Ofli
	Title	Identifying Disaster Damage Images Using a Domain Adaptation Approach			Type	Conference Article
	Year	2019	Publication	Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management	Abbreviated Journal	Iscram 2019
	Volume		Issue		Pages
	Keywords	image classification, disaster damage, domain adaptation, domain adversarial neural networks.
	Abstract	Approaches for effectively filtering useful situational awareness information posted by eyewitnesses of disasters, in real time, are greatly needed. While many studies have focused on filtering textual information, the research on filtering disaster images is more limited. In particular, there are no studies on the applicability of domain adaptation to filter images from an emergent target disaster, when no labeled data is available for the target disaster. To fill in this gap, we propose to apply a domain adaptation approach, called domain adversarial neural networks (DANN), to the task of identifying images that show damage. The DANN approach has VGG-19 as its backbone, and uses the adversarial training to find a transformation that makes the source and target data indistinguishable. Experimental results on several pairs of disasters suggest that the DANN model generally gives similar or better results as compared to the VGG-19 model fine-tuned on the source labeled data.
	Address	Department of Computer Science, Kansas State University, United States of America;Department of Computer Science, University of Illinois at Chicago, United States of America;Qatar Computing Research Institute, Hamad Bin Khalifa University, Qatar
	Corporate Author				Thesis
	Publisher	Iscram	Place of Publication	Valencia, Spain	Editor	Franco, Z.; González, J.J.; Canós, J.H.
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-84-09-10498-7	Medium
	Track	T8- Social Media in Crises and Conflicts	Expedition		Conference	16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019)
	Notes				Approved	no
	Call Number				Serial	1853
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	Author	Ly Dinh; Sumeet Kulkarni; Pingjing Yang; Jana Diesner
	Title	Reliability of Methods for Extracting Collaboration Networks from Crisis-related Situational Reports and Tweets			Type	Conference Article
	Year	2023	Publication	Proceedings of the ISCRAM Asia Pacific Conference 2022	Abbreviated Journal	Proc. ISCRAM AP 2022
	Volume		Issue		Pages	181-195
	Keywords	Collaboration Networks; Natural Language Processing; Interorganizational Collaboration; Situational Awareness
	Abstract	Assessing the effectiveness of crisis response is key to improving preparedness and adapting policies. One method for response evaluation is reviewing actual response activities and interactions. Response reports are often available in the form of natural language text data. Analyzing a large number of such reports requires automated or semi automated solutions. To improve the trustworthiness of methods for this purpose, we empirically validate the reliability of three relation extraction methods that we used to construct interorganizational collaboration networks by comparing them against human-annotated ground truth (crisis-specific situational reports and tweets). For entity extraction, we find that using a combination of two off-the-shelf methods (FlairNLP and SpaCy) is optimal for situational reports data and one method (SpaCy) for tweets data. For relation extraction, we find that a heuristics-based model that we built by leveraging word co-occurrence and deep and shallow syntax as features and training it on domain-specific text data outperforms two state-of-the-art relation extraction models (Stanford OpenIE and OneIE) that were pre-trained on general domain data. We also find that situational reports, on average, contain less entities and relations than tweets, but the extracted networks are more closely related to collaboration activities mentioned in the ground truth. As it is widely known that general domain tools might need adjustment to perform accurately in specific domains, we did not expect the tested off-the-shelf tools to perform highly accurately. Our point is to rather identify what accuracy one could reasonably expect when leveraging available resources as-is for domain specific work (in this case, crisis informatics), what errors (in terms of false positives and false negatives) to expect, and how to account for that.
	Address	University of South Florida; University of Illinois at Urbana-Champaign; University of Illinois at Urbana-Champaign; University of Illinois at Urbana-Champaign
	Corporate Author				Thesis
	Publisher	Massey Unversity	Place of Publication	Palmerston North, New Zealand	Editor	Thomas J. Huggins, V.L.
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-0-473-66845-7	Medium
	Track	Social Media for Disaster Response	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2492
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	Author	Tracey L. O'Sullivan; Wayne Corneil; Craig E. Kuziemsky; Daniel E. Lane
	Title	Citizen participation in the specification and mapping of potential disaster assets			Type	Conference Article
	Year	2013	Publication	ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	ISCRAM 2013
	Volume		Issue		Pages	890-895
	Keywords	Disaster prevention; Disasters; Information systems; Innovation; Asset-mapping; Collaboration; Empowerment; Engagement; Resilience; Mapping
	Abstract	Asset-mapping is a strategy used in disaster preparedness planning, however participation is typically limited to a small number of organizations with specific expertise related to disaster response. Broader strategies are needed to ensure identification of assets is comprehensive and to stimulate innovative thinking about which attributes of a community are potential assets for response and recovery. As part of The EnRiCH Project intervention, asset-mapping was used as a collaborative activity to promote identification of a broad range of assets which could be used to enhance resilience and promote preparedness among high risk populations. In this paper we present a study (in progress) which explores innovation and empowerment among a collaborative community group in Canada. Qualitative content analysis was used to analyze focus group transcripts from 2 sessions where the participants (n=18) learned how to use google docs and create a database of community assets, while developing collaborative relationships.
	Address	Interdisciplinary School of Health Sciences, University of Ottawa, Canada; Institute of Population Health, University of Ottawa, Canada; Telfer School of Management, University of Ottawa, Canada
	Corporate Author				Thesis
	Publisher	Karlsruher Institut fur Technologie	Place of Publication	KIT; Baden-Baden	Editor	T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	9783923704804	Medium
	Track	Social Media	Expedition		Conference	10th International ISCRAM Conference on Information Systems for Crisis Response and Management
	Notes				Approved	no
	Call Number				Serial	819
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	Author	Cody Buntain; Richard Mccreadie; Ian Soboroff
	Title	Incident Streams 2020: TRECIS in the Time of COVID-19			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	621-639
	Keywords	Emergency Management, Crisis Informatics, Twitter, Categorization, Prioritization, COVID-19
	Abstract	Between 2018 and 2019, the Incident Streams track (TREC-IS) has developed standard approaches for classifying the types and criticality of information shared in online social spaces during crises, but the introduction of SARS-CoV-2 has shifted the landscape of online crises substantially. While prior editions of TREC-IS have lacked data on large-scale public-health emergencies as these events are exceedingly rare, COVID-19 has introduced an over-abundance of potential data, and significant open questions remain about how existing approaches to crisis informatics and datasets built on other emergencies adapt to this new context. This paper describes how the 2020 edition of TREC-IS has addressed these dual issues by introducing a new COVID-19-specific task for evaluating generalization of existing COVID-19 annotation and system performance to this new context, applied to 11 regions across the globe. TREC-IS has also continued expanding its set of target crises, adding 29 new events and expanding the collection of event types to include explosions, fires, and general storms, making for a total of 9 event types in addition to the new COVID-19 events. Across these events, TREC-IS has made available 478,110 COVID-related messages and 282,444 crisis-related messages for participant systems to analyze, of which 14,835 COVID-related and 19,784 crisis-related messages have been manually annotated. Analyses of these new datasets and participant systems demonstrate first that both the distributions of information type and priority of information vary between general crises and COVID-19-related discussion. Secondly, despite these differences, results suggest leveraging general crisis data in the COVID-19 context improves performance over baselines. Using these results, we provide guidance on which information types appear most consistent between general crises and COVID-19.
	Address	New Jersey Institute of Technology; University of Glasgow; National Institute of Standards and Technology
	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	cbuntain@njit.edu			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2360
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	Author	McCreadie, R.; Buntain, C.
	Title	CrisisFACTS: Buidling and Evaluating Crisis Timelines			Type	Conference Article
	Year	2023	Publication	Proceedings of the 20th International ISCRAM Conference	Abbreviated Journal	Iscram 2023
	Volume		Issue		Pages	320-339
	Keywords	Emergency Management; Crisis Informatics News; Twitter; Facebook; Reddit; Wikipedia; Summarization
	Abstract	Between 2018 and 2021, the Incident Streams track (TREC-IS) developed standard approaches for classifying information types and criticality of tweets during crises. While successful in producing substantial collections of labeled data, TREC-IS as a data challenge had several limitations: It only evaluated information at type-level rather than what was reported; it only used Twitter data; and it lacked measures of redundancy in system output. This paper introduces Crisis Facts and Cross-Stream Temporal Summarization (CrisisFACTS), a new data challenge piloted in 2022 and developed to address these limitations. The CrisisFACTS framework recasts TREC-IS into an event-summarization task using multiple disaster-relevant data streams and a new fact-based evaluation scheme, allowing the community to assess state-of-the-art methods for summarizing disaster events Results from CrisisFACTS in 2022 include a new test-collection comprising human-generated disaster summaries along with multi-platform datasets of social media, crisis reports and news coverage for major crisis events.
	Address	University of Glasgow; University of Maryland, College Park (UMD)
	Corporate Author				Thesis
	Publisher	University of Nebraska at Omaha	Place of Publication	Omaha, USA	Editor	Jaziar Radianti; Ioannis Dokas; Nicolas Lalone; Deepak Khazanchi
	Language	English	Summary Language		Original Title
	Series Editor	Hosssein Baharmand	Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition	1
	ISSN		ISBN		Medium
	Track	Social Media for Crisis Management	Expedition		Conference
	Notes	http://dx.doi.org/10.59297/JVQZ9405			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2529
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	Author	Linda Plotnick; Starr Roxanne Hiltz; Sukeshini Grandhi; Julie Dugdale
	Title	Real or Fake? User Behavior and Attitudes Related to Determining the Veracity of Social Media Posts			Type	Conference Article
	Year	2018	Publication	Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific.	Abbreviated Journal	Iscram Ap 2018
	Volume		Issue		Pages	439-449
	Keywords	Social media, trustworthiness, fake news
	Abstract	Citizens and Emergency Managers need to be able to distinguish “fake” (untrue) news posts from real news posts on social media during disasters. This paper is based on an online survey conducted in 2018 that produced 341 responses from invitations distributed via email and through Facebook. It explores to what extent and how citizens generally assess whether postings are “true” or “fake,” and describes indicators of the trustworthiness of content that users would like. The mean response on a semantic differential scale measuring how frequently users attempt to verify the news trustworthiness (a scale from 1-never to 5-always) was 3.37. The most frequent message characteristics citizens' use are grammar and the trustworthiness of the sender. Most respondents would find an indicator of trustworthiness helpful, with the most popular choice being a colored graphic. Limitations and implications for assessments of trustworthiness during disasters are discussed.
	Address	New Jersey Institute of Technology; Eastern Connecticut State University; New Jersey Institute of Technology; University of Grenoble
	Corporate Author				Thesis
	Publisher	Massey Univeristy	Place of Publication	Albany, Auckland, New Zealand	Editor	Kristin Stock; Deborah Bunker
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Track	Social Media and Community Engagement Supporting Resilience Building	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	1665
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	Author	Faisal Luqman; Martin Griss
	Title	Leveraging mobile context for effective collaboration and task management			Type	Conference Article
	Year	2011	Publication	8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011	Abbreviated Journal	ISCRAM 2011
	Volume		Issue		Pages
	Keywords	Carrier mobility; Information systems; Mobile devices; Agent-based systems; Collaboration; Command and control; Context information; Dynamic role-based; Emergent volunteer; Large scale disasters; Multi-agent; Human resource management
	Abstract	Collaboration and task management is challenging in distributed, dynamically-formed teams, typical in large scale disaster response scenarios. Ineffective collaboration may potentially result in poor performance and loss of life. The increased adoption of sensor rich mobile devices allow for mobile context to be leveraged. In this paper, we present Overseer, an agent-based system that exploits context information from mobile devices to facilitate collaboration and task allocation. We describe how mobile context can be used to create dynamic role-based assignments to enhance collaboration and effective task management.
	Address	Carnegie Mellon Silicon Valley, United States
	Corporate Author				Thesis
	Publisher	Information Systems for Crisis Response and Management, ISCRAM	Place of Publication	Lisbon	Editor	M.A. Santos, L. Sousa, E. Portela
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	9789724922478	Medium
	Track	Social Media and Collaborative Systems	Expedition		Conference	8th International ISCRAM Conference on Information Systems for Crisis Response and Management
	Notes				Approved	no
	Call Number				Serial	730
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	Author	Simon Tucker; Vitaveska Lanfranchi; Neil Ireson; Alfonso Sosa; Gregoire Burel; Fabio Ciravegna
	Title	Straight to the information I need: Assessing collational interfaces for emergency response			Type	Conference Article
	Year	2012	Publication	ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	ISCRAM 2012
	Volume		Issue		Pages
	Keywords	Information systems; Emergency response; Information overloads; Paper-based interfaces; Situational awareness; Social media; User study; Emergency services
	Abstract	Collational interfaces gather information from a range of sources and present them to users. Information overload is tackled by processing information in the back-end and providing interactive means to filter and browse data. Such interfaces have applications in emergency response – giving users the right information to act effectively. In this paper we explore a collational interface for emergency response, carrying out a user study that compares it to a paper based interface and one which presents data without collating it. We demonstrate that a collational interface allows users to build a picture of an emergency, but not necessarily in less time. Â© 2012 ISCRAM.
	Address	Department of Computer Science, University of Sheffield, United Kingdom; Knowledge Media Institute, Open University, United Kingdom
	Corporate Author				Thesis
	Publisher	Simon Fraser University	Place of Publication	Vancouver, BC	Editor	L. Rothkrantz, J. Ristvej, Z.Franco
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	9780864913326	Medium
	Track	Social Media and Collaborative Systems	Expedition		Conference	9th International ISCRAM Conference on Information Systems for Crisis Response and Management
	Notes				Approved	no
	Call Number				Serial	221
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	Author	Zeno Franco; Syed Ahmed; Craig E. Kuziemsky; Paul A. Biedrzycki; Anne Kissack
	Title	Using social network analysis to explore issues of latency, connectivity, interoperability & sustainability in community disaster response			Type	Conference Article
	Year	2013	Publication	ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	ISCRAM 2013
	Volume		Issue		Pages	896-900
	Keywords	Data fusion; Disasters; Information systems; Mergers and acquisitions; Social networking (online); Boundary spanning; Community engagement; Community resources; Community vulnerability; Crisis response; Disaster recovery; Disaster response; Social network analysis approaches; Emergency services
	Abstract	Community-based disaster response is gaining attention in the United States because of major problems with domestic disaster recovery over the last decade. A social network analysis approach is used to illustrate how community-academic partnerships offer one way to leverage information about existing, mediated relationships with the community through trusted actors. These partnerships offer a platform that can be used to provide entré into communities that are often closed to outsiders, while also allowing greater access to community embedded physical assets and human resources, thus facilitated more culturally appropriate crisis response. Using existing, publically available information about funded community-academic partnerships in Wisconsin, USA, we show how social network analysis of these meta-organizations may provide critical information about both community vulnerabilities in disaster and assist in rapidly identifying these community resources in the aftermath of a crisis event that may provide utility for boundary spanning crisis information systems.
	Address	Medical College of Wisconsin, United States; U. Ottawa, Canada; City of Milwaukee Public Health Department, United Kingdom
	Corporate Author				Thesis
	Publisher	Karlsruher Institut fur Technologie	Place of Publication	KIT; Baden-Baden	Editor	T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	9783923704804	Medium
	Track	Social Media	Expedition		Conference	10th International ISCRAM Conference on Information Systems for Crisis Response and Management
	Notes				Approved	no
	Call Number				Serial	504
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	Author	Briony Jennifer Gray
	Title	Social Media and Disasters: A New Conceptual Framework			Type	Conference Article
	Year	2016	Publication	ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	ISCRAM 2016
	Volume		Issue		Pages
	Keywords	Social Media; Conceptual Framework; Disaster Management; Web Accessibility; Information Reliability
	Abstract	Conceptual frameworks which seek to integrate social media uses into disaster management strategies are employed in a range of events. With continued variations to social media practices, developments in technology, and changes in online behaviors, it is imperative to provide conceptual frameworks which are relevant, current and insightful. This paper conceptualizes a range of recent literature through an inductive methodology, and presents the themes of Web accessibility and online information reliability as broad and emerging considerations for the identification of social media uses during disasters. It presents a new conceptual framework of current social media uses which may be used to supplement existing frameworks. The framework has been applied to a dataset of Tweets from the 2015 Nepal earthquake to demonstrate its validity. Suggestions for future applications are discussed.
	Address
	Corporate Author				Thesis
	Publisher	Federal University of Rio de Janeiro	Place of Publication	Rio de Janeiro, Brasil	Editor	A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3388	ISBN	978-84-608-7984-9	Medium
	Track	Social Media Studies	Expedition		Conference	13th International Conference on Information Systems for Crisis Response and Management
	Notes				Approved	no
	Call Number				Serial	1400
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	Author	Imen Bizid; Patrice Boursier; Jacques Morcos; Sami Faiz
	Title	A Classification Model for the Identification of Prominent Microblogs Users during a Disaster			Type	Conference Article
	Year	2015	Publication	ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	ISCRAM 2015
	Volume		Issue		Pages
	Keywords	Disaster Management; Information retrieval; Microblogs
	Abstract	Content shared in microblogs during disasters is expressed in various formats and languages. This diversity makes the information retrieval process more complex and computationally infeasible in real time. To address this, we propose a classification model for the identification of prominent users who are sharing relevant and exclusive information during the disaster. Users who have shared at least one tweet about the disaster are modeled using three kinds of time-sensitive features, including topical, social and geographical features. Then, these users are classified into two classes using a linear Support Vector Machine (SVM) to evaluate them over the extracted features and identify the most prominent ones. The first results using the actual dataset, show that our model has a high accuracy by detecting most of the prominent users. Moreover, we demonstrate that all the proposed features used by our model are indispensable to achieve this high accuracy.
	Address
	Corporate Author				Thesis
	Publisher	University of Agder (UiA)	Place of Publication	Kristiansand, Norway	Editor	L. Palen; M. Buscher; T. Comes; A. Hughes
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	9788271177881	Medium
	Track	Social Media Studies	Expedition		Conference	ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management
	Notes				Approved	yes
	Call Number				Serial	1241
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	Author	Christian Reuter
	Title	Power outage communications: Survey of needs, infrastructures and concepts			Type	Conference Article
	Year	2013	Publication	ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	ISCRAM 2013
	Volume		Issue		Pages	884-889
	Keywords	Information systems; Mobile computing; Citizen; Communication infrastructure; Crisis communications; General information; Information and Communication Technologies; Information demand; Power outage; Smart-phone applications; Outages
	Abstract	Crisis communication during power outages poses several challenges. Frist, the causes of power outages are often events such as severe weather, which also lead to complications. Second, power outages themselves lead to limitations in everyday life. Third, communication infrastructures, that are necessary for crisis communication, are often affected. This work focuses on the communication of the organizations responsible for recovery work (emergency services, public administration, energy network operators) to the public affected by the power outage. Therefore this paper investigates the perception and the information demands of citizens and communication infrastructures in different scenarios. Taking the users' needs into consideration, an Information and Communication Technology (ICT) based concept for crisis communication, which combines general information with location-specific and setting-specific information was implemented as a prototype smartphone application and evaluated with 12 potential end users. ICT-based concepts can gain acceptance, however they should be understood as supplemental for some target groups and in some scenarios.
	Address	Institute for Information Systems, University of Siegen, Germany
	Corporate Author				Thesis
	Publisher	Karlsruher Institut fur Technologie	Place of Publication	KIT; Baden-Baden	Editor	T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	9783923704804	Medium
	Track	Social Media	Expedition		Conference	10th International ISCRAM Conference on Information Systems for Crisis Response and Management
	Notes				Approved	no
	Call Number				Serial	873
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	Author	Laura Petersen; Laure Fallou; Grigore Havarneanu; Paul Reilly; Elisa Serafinelli; Rémy Bossu
	Title	November 2015 Paris Terrorist Attacks and Social Media Use: Preliminary Findings from Authorities, Critical Infrastructure Operators and Journalists			Type	Conference Article
	Year	2018	Publication	ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2018
	Volume		Issue		Pages	629-638
	Keywords	Social media, crisis communication, situational awareness, Paris terrorist attacks, terrorism.
	Abstract	Crisis communication is a key component of an effective emergency response. Social media has evolved as a prominent crisis communication tool. This paper reports how social media was used by authorities, critical infrastructure operators and journalists during the terrorist attacks that hit Paris on 13th November 2015. A qualitative study was conducted between January and February 2017 employing semi-structured interviews with seven relevant stakeholders involved in this communication process. The preliminary critical thematic analysis revealed four main themes which are reported in the results section: (1) social media is used in crisis times; (2) authorities gained situational awareness via social media; (3) citizens used social media to help one another; and (4) communication procedures changed after these critical events. In conclusion, authorities, citizens and journalists all turned to social media during the attack, both for crisis communication and for increasing situational awareness.
	Address
	Corporate Author				Thesis
	Publisher	Rochester Institute of Technology	Place of Publication	Rochester, NY (USA)	Editor	Kees Boersma; Brian Tomaszeski
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-0-692-12760-5	Medium
	Track	Social Media Studies	Expedition		Conference	ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management
	Notes				Approved	no
	Call Number				Serial	2137
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	Author	Jess Kropczynski; Rob Grace; Julien Coche; Shane Halse; Eric Obeysekare; Aurélie Montarnal; Frederick Bénaben; Andrea Tapia
	Title	Identifying Actionable Information on Social Media for Emergency Dispatch			Type	Conference Article
	Year	2018	Publication	Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific.	Abbreviated Journal	Iscram Ap 2018
	Volume		Issue		Pages	428-438
	Keywords	Public Safety Answering Point (PSAP), Social Media, Qualitative Coding
	Abstract	Crisis informatics researchers have taken great interest in methods to identify information relevant to crisis events posted by digital bystanders on social media. This work codifies the information needs of emergency dispatchers and first responders as a method to identify actionable information on social media. Through a design workshop with public safety professionals at a Public-Safety Answering Point (PSAP) in the United States, we develop a set of information requirements that must be satisfied to dispatch first responders and meet their immediate situational awareness needs. We then present a manual coding scheme to identify information satisfying these requirements in social media posts and apply this scheme to fictitious tweets professionals propose as actionable information to better assess ways that this information may be communicated. Finally, we propose automated methods from previous literature in the field that can be used to implement these methods in the future.
	Address	University of Cincinnati; The Pennsylvania State University; coles des Mines d'Albi Carmaux; The Pennsylvania State University; The Pennsylvania State University; coles des Mines d'Albi Carmaux; The Pennsylvania State University; coles des Mines d'Albi Carmaux
	Corporate Author				Thesis
	Publisher	Massey Univeristy	Place of Publication	Albany, Auckland, New Zealand	Editor	Kristin Stock; Deborah Bunker
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Track	Social Media and Community Engagement Supporting Resilience Building	Expedition		Conference
	Notes				Approved	no
	Call Number				Serial	1672
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	Author	Geneviève Dubé; Chelsea Kramer; François Vachon; Sébastien Tremblay
	Title	Measuring the impact of a collaborative planning support system on crisis management			Type	Conference Article
	Year	2011	Publication	8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011	Abbreviated Journal	ISCRAM 2011
	Volume		Issue		Pages
	Keywords	Information systems; Maps; Planning; Collaborative planning; Crisis management; Cwss; Functional simulations; Microworld; Objective assessment; Preliminary analysis; Team cognition; Human resource management
	Abstract	Crisis management (CM) is an aspect of command and control characterized by complexity, uncertainty, and severe time pressure. To address these challenges, CM teams can use collaborative work support systems (CWSS) to help plan their intervention and coordination activities. However, the use of CWSS is not necessarily beneficial and in some cases, can impede more than augment performance. Hence, it is essential to understand the impact of a CWSS on team performance and CM teamwork. We have developed a methodology to assess the effectiveness of CWSS by comparing the use of an interactive Smartboard with that of a traditional topographic map during team planning activities. To do so, a dynamic CM situation is simulated using a forest firefighting functional simulation – the C3Fire microworld. We compared two groups of participants on the basis of performance, communication, coordination efficiency, and planning quality. Based on a preliminary analysis, in comparison to maps, the use of a CWSS seems to be beneficial to planning activities and CM coordination. At this point the main contribution of the current on-going project is to provide a method and metrics for the objective assessment of new technology in the context of CM.
	Address	École de Psychologie, Université Laval, QC, Canada; CAE Professional Services, Ottawa, Canada
	Corporate Author				Thesis
	Publisher	Information Systems for Crisis Response and Management, ISCRAM	Place of Publication	Lisbon	Editor	M.A. Santos, L. Sousa, E. Portela
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	9789724922478	Medium
	Track	Social Media and Collaborative Systems	Expedition		Conference	8th International ISCRAM Conference on Information Systems for Crisis Response and Management
	Notes				Approved	no
	Call Number				Serial	459
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	Author	Apoorva Chauhan; Amanda Hughes
	Title	COVID-19 Named Resources on Facebook, Twitter, and Reddit			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	679-690
	Keywords	Crisis Named Resources, Facebook, Twitter, Reddit, COVID-19
	Abstract	Crisis Named Resources (CNRs) are social media accounts and pages named after a crisis event. They are created soon after an event occurs. CNRs share a lot of information around an event and are followed by many. In this study, we identify CNRs created around COVID-19 on Facebook, Twitter, and Reddit. We analyze when these resources were created, why they were created, how they were received by members of the public, and who created them. We conclude by comparing CNRs created around COVID-19 with past crisis events and discuss how CNR owners attempt to manage content and combat misinformation.
	Address	University of Waterloo; Brigham Young 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	apoorva.chauhan@aggiemail.usu.edu			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2364
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	Author	Apoorva Chauhan; Amanda Lee Hughes
	Title	Social Media Resources Named after a Crisis Event			Type	Conference Article
	Year	2018	Publication	ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2018
	Volume		Issue		Pages	573-583
	Keywords	Crisis Informatics, Crisis Named Resources, Social Media
	Abstract	Crisis Named Resources (CNRs) are the social media accounts and pages named after a crisis event. CNRs typically appear spontaneously after an event as places for information exchange. They are easy to find when searching for information about the event. Yet in most cases, it is unclear who manages these resources. Thus, it is important to understand what kinds of information they provide and what role they play in a response. This paper describes a study of Facebook and Twitter CNRs around the 2016 Fort McMurray wildfire. We report on CNR lifecycles, and their relevance to the event. Based on the information provided by these resources, we categorize them into 8 categories: donations, fundraisers, prayers, reactions, reports, needs and offers, stories, and unrelated. We also report on the most popular CNR on both Facebook and Twitter. We conclude by discussing the role of CNRs and the need for future investigation.
	Address
	Corporate Author				Thesis
	Publisher	Rochester Institute of Technology	Place of Publication	Rochester, NY (USA)	Editor	Kees Boersma; Brian Tomaszeski
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-0-692-12760-5	Medium
	Track	Social Media Studies	Expedition		Conference	ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management
	Notes				Approved	no
	Call Number				Serial	2132
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