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Author (up) 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 (up) Mohammed Benali, A.R.G.
Title Towards a Crowdsourcing-based Approach to enhance Decision Making in Collaborative Crisis Management 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 554-563
Keywords Crisis management; decision making; crowdsourcing; SBPMN
Abstract Managing crises is considered as one of the most complicated organizational and managerial task. Indeed, dealing with such situations calls for many groups from different institutions and organizations to interact and collaborate their efforts in a timely manner to reduce their effects. However, response organizations are challenged by several problems. The urgent need of a shared and mutual situational awareness, information and knowledge about the situation are distributed across time and space and owned by both organizations and people. Additionally, decisions and actions have to be achieved promptly, under stress and time pressure. The contribution outlined in this paper is suggesting a crowdsourcing-based approach for decision making in collaborative crisis management based on the literature requirements. The objective of the approach is to support situational awareness and enhance the decision making process by involving citizens in providing opinions and evaluations of potential response actions.
Address Laboratoire de Méthodes de Conception des Systèmes, Ecole nationale Supérieure d'Informatique, Alger, Algérie
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 Serial 2043
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Author (up) 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 (up) Muhammad Imran; Firoj Alam; Umair Qazi; Steve Peterson; Ferda Ofli
Title Rapid Damage Assessment Using Social Media Images by Combining Human and Machine Intelligence Type Conference Article
Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020
Volume Issue Pages 761-773
Keywords Social Media, Damage Assessment, Artificial Intelligence, Image Processing.
Abstract Rapid damage assessment is one of the core tasks that response organizations perform at the onset of a disaster to understand the scale of damage to infrastructures such as roads, bridges, and buildings. This work analyzes the usefulness of social media imagery content to perform rapid damage assessment during a real-world disaster. An automatic image processing system, which was activated in collaboration with a volunteer response organization, processed ~280K images to understand the extent of damage caused by the disaster. The system achieved an accuracy of 76% computed based on the feedback received from the domain experts who analyzed ~29K system-processed images during the disaster. An extensive error analysis reveals several insights and challenges faced by the system, which are vital for the research community to advance this line of research.
Address Qatar Computing Research Institute Hamad Bin Khalifa University Doha, Qatar; Qatar Computing Research Institute Hamad Bin Khalifa University Doha, Qatar; Qatar Computing Research Institute Hamad Bin Khalifa University Doha, Qatar; Montgomery County, Maryland Community Emergency Response Team United States; Qatar Computing Research Institute Hamad Bin Khalifa University Doha, Qatar
Corporate Author Thesis
Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 978-1-949373-27-68 ISBN 2411-3454 Medium
Track Social Media for Disaster Response and Resilie Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management
Notes mimran@hbku.edu.qa Approved no
Call Number Serial 2269
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Author (up) Muhammad Imran; Prasenjit Mitra; Jaideep Srivastava
Title Cross-Language Domain Adaptation for Classifying Crisis-Related Short Messages 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; Tweets Classification; Domain Adaptation
Abstract Rapid crisis response requires real-time analysis of messages. After a disaster happens, volunteers attempt to classify tweets to determine needs, e.g., supplies, infrastructure damage, etc. Given labeled data, supervised machine learning can help classify these messages. Scarcity of labeled data causes poor performance in machine training. Can we reuse old tweets to train classifiers? How can we choose labeled tweets for training? Specifically, we study the usefulness of labeled data of past events. Do labeled tweets in different language help? We observe the performance of our classifiers trained using different combinations of training sets obtained from past disasters. We perform extensive experimentation on real crisis datasets and show that the past labels are useful when both source and target events are of the same type (e.g. both earthquakes). For similar languages (e.g., Italian and Spanish), cross-language domain adaptation was useful, however, when for different languages (e.g., Italian and English), the performance decreased.
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 1396
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Author (up) Muhammad Imran; Shady Elbassuoni; Carlos Castillo; Fernando Díaz; Patrick Meier
Title Extracting information nuggets from disaster- Related messages in social media 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 791-801
Keywords Artificial intelligence; Data visualization; Disasters; Information retrieval; Information systems; Learning systems; Social networking (online); Emergency responders; Extracting information; Machine learning methods; Situational awareness; Social media; Supervised classification; Twitter; Visualization system; Emergency services
Abstract Microblogging sites such as Twitter can play a vital role in spreading information during “natural” or man-made disasters. But the volume and velocity of tweets posted during crises today tend to be extremely high, making it hard for disaster-affected communities and professional emergency responders to process the information in a timely manner. Furthermore, posts tend to vary highly in terms of their subjects and usefulness; from messages that are entirely off-topic or personal in nature, to messages containing critical information that augments situational awareness. Finding actionable information can accelerate disaster response and alleviate both property and human losses. In this paper, we describe automatic methods for extracting information from microblog posts. Specifically, we focus on extracting valuable “information nuggets”, brief, self-contained information items relevant to disaster response. Our methods leverage machine learning methods for classifying posts and information extraction. Our results, validated over one large disaster-related dataset, reveal that a careful design can yield an effective system, paving the way for more sophisticated data analysis and visualization systems.
Address University of Trento, Italy; American Univ. of Beirut, Lebanon; QCRI, Qatar; Microsoft Research, Qatar
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 613
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Author (up) Murray E. Jennex
Title Social media – Truly viable for crisis 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 Availability; Hardware; Cell phone; Crisis events; Crisis response; San Diego; Social media; Information systems
Abstract On September 8, 2011 the Great San Diego/Southwest Blackout occurred. Approximately 5 million people were affected by this blackout. This paper explores the availability of social media following such a crisis event. Contrary to expectations, the cell phone system did not have the expected availability and as a result, users had a difficult time using social media to status/contact family and friends. This paper presents a survey exploring the use and availability of social media during the Great San Diego/Southwest Blackout event. © 2012 ISCRAM.
Address San Diego State University, United States
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 23
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Author (up) 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 (up) Neda Mohammadi; John E. Taylor; Ryan Pollyea
Title Spatiotemporal Dynamics of Public Response to Human-Induced Seismic Perturbations 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 666-672
Keywords Crisis informatics; human-induced earthquake; social media networks; spatiotemporal; far-field effect
Abstract There is general consensus that subsurface wastewater injections associated with unconventional oil and gas operations are responsible for the rapid increase of earthquake activity in the mid-U.S. Understanding the public response to these earthquakes is crucial for policy decisions that govern developing situational awareness and addressing perceived risks. However, we lack sufficient information on the reactive and recovery response behavior of the public tending to occur in the spatiotemporal vicinity of these events. Here, we review the spatiotemporal distribution of public response to the September 3, 2016, M5.8 earthquake in Pawnee, Oklahoma, USA, via a social media network (Twitter). Our findings highlight a statistically significant correlation between the spatial and temporal distribution of public response; and suggest the possible presence of a spatial distance decay, as well as a temporal far-field eect. Understanding the underlying structure of these correlations is fundamental to establishing deliberate policy decisions and targeted response actions.
Address Georgia Tech; Virginia Tech
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 Serial 2054
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Author (up) Nilani Algiriyage; Rangana Sampath; Raj Prasanna; Kristin Stock; Emma Hudson-Doyle; David Johnston
Title Identifying Disaster-related Tweets: A Large-Scale Detection Model Comparison 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 731-743
Keywords Tweet Classification, Machine Learning, Deep Learning, Disasters
Abstract Social media applications such as Twitter and Facebook are fast becoming a key instrument in gaining situational awareness (understanding the bigger picture of the situation) during disasters. This has provided multiple opportunities to gather relevant information in a timely manner to improve disaster response. In recent years, identifying crisis-related social media posts is analysed as an automatic task using machine learning (ML) or deep learning (DL) techniques. However, such supervised learning algorithms require labelled training data in the early hours of a crisis. Recently, multiple manually labelled disaster-related open-source twitter datasets have been released. In this work, we create a large dataset with 186,718 tweets by combining a number of such datasets and evaluate the performance of multiple ML and DL algorithms in classifying disaster-related tweets in three settings, namely ``in-disaster'', ``out-disaster'' and ``cross-disaster''. Our results show that the Bidirectional LSTM model with Word2Vec embeddings performs well for the tweet classification task in all three settings. We also make available the preprocessing steps and trained weights for future research.
Address Massey University; Massey University; Massey University; Massey University; Joint Centre for Disaster Research, Massey University; Joint Center of Disaster Research, Massey University Wellington
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 rangika.nilani@gmail.com Approved no
Call Number ISCRAM @ idladmin @ Serial 2368
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Author (up) Nils Bourgon; Benamara Farah; Alda Mari; Véronique Moriceau; Gaetan Chevalier; Laurent Leygue; Yasmine Djadda
Title Are Sudden Crises Making me Collapse? Measuring Transfer Learning Performances on Urgency Detection Type Conference Article
Year 2022 Publication ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2022
Volume Issue Pages 701-709
Keywords Sudden crises; Transfer learning; Few-shot learning; Zero-shot learning; Social media content
Abstract This paper aims at measuring transfer learning performances across different types of crises related to sudden or unexpected events (like earthquakes, terror attacks, explosions, technological incidents) that cannot be foreseen by emergency services and on the occurrence of which they have virtually no control. Although sudden crises are present in most existing crisis datasets, as far as we are aware, no one studied their impact on classifiers performances when evaluated in an out-of-type scenario in which models are tested on a particular type of crisis unseen during training. Our contribution is threefold: (1) A new dataset of about 3,800 French tweets related to four sudden events that occurred in France annotated for both relatedness (i.e., useful vs. not useful for emergency responders) and urgency (i.e., not useful vs. urgent vs. not urgent), (2) A set of monotask and multitask zero-shot learning experiments to transfer knowledge across events and types, and finally, (3) Experiments involving few-shot learning to measure the amount of sudden events instances needed during training to guarantee good performances. When compared to a cross-event setting, our preliminary results are encouraging and show that transfer from predictable ecological crisis to sudden events is feasible and constitutes a first step towards real-time crisis management systems from social media content.
Address IRIT, Université de Toulouse, CNRS, Toulouse INP, UT3; IRIT, Université de Toulouse, CNRS, Toulouse INP, UT3; IJN, CNRS/ENS/EHESS PSL University; IRIT, Université de Toulouse, CNRS, Toulouse INP, UT3; DGSCGC SDAIRS; DGSCGC SDAIRS
Corporate Author Thesis
Publisher Place of Publication Tarbes, France Editor Rob Grace; Hossein Baharmand
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 978-82-8427-099-9 Medium
Track Social Media for Crisis Management Expedition Conference
Notes Approved no
Call Number ISCRAM @ idladmin @ Serial 2449
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Author (up) Ntalla Athanasia; Ponis T. Stavros
Title Twitter as an instrument for crisis response: The Typhoon Haiyan case study 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 Crisis Management; emergency response; Haiyan; social media; Twitter
Abstract The research presented in this paper attempts an initial evaluation of Twitter as an instrument for emergency response in the context of a recent crisis event. The case of the 2013 disaster, when typhoon Haiyan hit Philippines is examined by analyzing nine consecutive days of Twitter messages and comparing them to the actual events. The results indicate that during disasters, Twitter users tend to post messages to enhance situation awareness and to motivate people to act. Furthermore, tweets were found reliable and provided valuable information content, supporting the argument that Twitter presents a very good potential to become a useful tool in situations where rapid emergency response is essential.
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 1238
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Author (up) Nurollahian, S.; Talegaonkar, I.; Bell, A.Z.; Kogan, M.
Title Factors Affecting Public’s Engagement with Tweets by Authoritative Sources During Crisis Type Conference Article
Year 2023 Publication Proceedings of the 20th International ISCRAM Conference Abbreviated Journal Iscram 2023
Volume Issue Pages 459-477
Keywords Crisis Informatics; Social Media; Public Engagement; Authoritative Sources; Topic Modeling
Abstract People increasingly use social media at the time of crisis, which produces a social media data deluge, where the public may find it difficult to locate trustworthy and credible information. Therefore, they often turn to authoritative sources: official individuals and organizations who are trusted to provide reliable information. It is then imperative that their credible messages reach and engage the widest possible audience, especially among those affected. In this study, we explore the role of metadata and linguistic factors in facilitating three types of engagement — retweets, replies, and favorites— with posts by authoritative sources. We find that many factors are similarly important across models (popularity, sociability, activity). However, some features are salient for only a specific type of engagement. We conclude by providing guidance to authoritative sources on how they may optimize specific types of engagement: retweets for information propagation, replies for in-depth sense-making, and favorites for cross-purpose visibility.
Address University of Utah; University of Utah; University of Utah; University of Utah
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/AVHJ5856 Approved no
Call Number ISCRAM @ idladmin @ Serial 2540
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Author (up) Online Media as a Means to Affect Public Trust in Emergency Responders
Title Amanda Lee Hughes; Apoorva Chauhan 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 computer-mediated communication; crisis informatics; emergency response; social media; trust
Abstract This exploratory study examines how fire and police departments used online media during the 2012 Hurricane Sandy and how these media can be used to affect trust with members of the public during such an event. Using trust theory, we describe how online communications provide a means for emergency responders to appear trustworthy through online acts of ability, integrity, and benevolence. We conclude with implications and recommendations for emergency response practice and a trajectory of future work.
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 1226
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Author (up) 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 (up) Patrick C. Shih; Kyungsik Han; John M. Carroll
Title Community incident chatter: Informing local incidents by aggregating local news and social media content 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 772-776
Keywords Hardware; Civic awareness and participation; Large-scale event; Local incidents and emergencies; News agencies; Smart-phone applications; Social media; Two way communications; User study; Information systems
Abstract The emergence of social media provides an additional channel for broadcasting information to the public and support two-way communication between governmental stakeholders and the public during crisis. Research has focused on large-scale events, and few have investigated how social media can contribute to civic awareness and participation of small-scale incidents in a community-oriented context. Moreover, social media have been criticized because it is overabundant with noisy, inaccurate, and unprofessional information that are often misleading. This presents a serious challenge for community members to identify information that are relevant to a local incident. We introduce Community Incident Chatter (CIC), a smartphone application that is designed to aggregate information reported by formal news agencies and social media surrounding local incidents. Participants in a preliminary user study indicate that the community-oriented information presented in CIC is informative, relevant to the community, and has the potential of empowering community residents for responding to and managing local incidents.
Address Pennsylvania State University, United States
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 949
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Author (up) Pereira, J.; Fidalgo, R.; Lotufo, R.; Nogueira, R.
Title Crisis Event Social Media Summarization with GPT-3 and Neural Reranking Type Conference Article
Year 2023 Publication Proceedings of the 20th International ISCRAM Conference Abbreviated Journal Iscram 2023
Volume Issue Pages 371-384
Keywords Crisis Management; Social Media; Multi-Document Summarization; Query-Based Summarization.
Abstract Managing emergency events, such as natural disasters, requires management teams to have an up-to-date view of what is happening throughout the event. In this paper, we demonstrate how a method using a state-of-the-art open-sourced search engine and a large language model can generate accurate and comprehensive summaries by retrieving information from social media and online news sources. We evaluated our method on the TREC CrisisFACTS challenge dataset using automatic summarization metrics (e.g., Rouge-2 and BERTScore) and the manual evaluation performed by the challenge organizers. Our approach is the best in comprehensiveness despite presenting a high redundancy ratio in the generated summaries. In addition, since all pipeline components are few-shot, there is no need to collect training data, allowing us to deploy the system rapidly. Code is available at https://github.com/neuralmind-ai/visconde-crisis-summarization.
Address Centro de Inform´atica, Universidade Federal de Pernambuco; NeuralMind
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/JJYT4136 Approved no
Call Number ISCRAM @ idladmin @ Serial 2532
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Author (up) Peter A. Jongejan; Tim J. Grant
Title Social media in command & control: An extended framework 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 Communication; Information systems; Peer to peer networks; Basic theory; Crisis management; Dynamic environments; Network-enabled capabilities; Social media; Social software; Theoretical development; Work-in-progress; File editors
Abstract Our research is aimed at investigating whether social media has a role to play in military Command & Control. Since social media is peer-to-peer, it could facilitate Network-Enabled Capabilities. A useful theoretical development is Reuter, Marx, and Pipek's (2011) proposal of a two-by-two matrix for social software infrastructure. Their framework assumes one-way communication and monolithic organizations. However, to operate in a real-time, dynamic environment, crisis management organizations must close the decision-making loop. Moreover, they must be structured into an action part that handles the crisis on-site, and a control part that monitors and directs operations in real time. The purpose of this work-in-progress paper is to present our extension of Reuter et al's framework. The paper outlines Reuter et al's framework, summarises the basic theory of Command & Control, describes how we extended Reuter et al's framework, and outlines further research. © 2012 ISCRAM.
Address Netherlands Defence Academy, Netherlands
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 137
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Author (up) Pooneh Mousavi; Cody Buntain
Title “Please Donate for the Affected”: Supporting Emergency Managers in Finding Volunteers and Donations in Twitter Across Disasters Type Conference Article
Year 2022 Publication ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2022
Volume Issue Pages 605-622
Keywords social media; crisis in formatics; volunteers; donations; emergency support functions
Abstract Despite the outpouring of social support posted to social media channels in the aftermath of disaster, finding and managing content that can translate into community relief, donations, volunteering, or other recovery support is difficult due to the lack of sufficient annotated data around volunteerism. This paper outlines three experiments to alleviate these difficulties. First, we estimate to what degree volunteerism content from one crisis is transferable to another by evaluating the consistency of language in volunteer-and donation-related social media content across 78 disasters. Second it introduces methods for providing computational support in this emergency support function and developing semi-automated models for classifying volunteer-and donation-related social media content in new disaster events. Results show volunteer-and donation-related social media content is sufficiently similar across disasters and disaster types to warrant transferring models across disasters, and we evaluate simple resampling techniques for tuning these models. We then introduce and evaluate a weak-supervision approach to integrate domain knowledge from emergency response officers with machine learningmodelstoimproveclassification accuracy andacceleratethisemergencysupportinnewevents. This method helps to overcome the scarcity in data that we observe related to volunteer-and donation-related social media content.
Address University of Maryland, College Park; University of Maryland, College Park
Corporate Author Thesis
Publisher Place of Publication Tarbes, France Editor Rob Grace; Hossein Baharmand
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 978-82-8427-099-9 Medium
Track Social Media for Crisis Management Expedition Conference
Notes Approved no
Call Number ISCRAM @ idladmin @ Serial 2442
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Author (up) Pragna Debnath; Saniul Haque; Somprakash Bandyopadhyay; Siuli Roy
Title Post-disaster Situational Analysis from WhatsApp Group Chats of Emergency Response Providers 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
Abstract Use of social media has established itself as one of the important information carriers in the field of disaster management. However, use of Twitter and Facebook by victims, first responders and others generates information that is varied, unstructured and unreliable. On the other hand, NGOs, operating in the disaster area, are often involved in intra-organizational communication using messaging apps like WhatsApp, and their group interactions can help in gathering meaningful data for situational analysis and need assessment. Our focus is to automate the process of filtering relevant information, query-based clustering of pertinent information from a WhatsApp group conversation of a specific volunteer group, so that situation analysis and need assessment can be done more rapidly. We have evaluated our scheme using WhatsApp chat log of a medical volunteer group in two post-disaster scenarios and concluded that it can provide valuable insights about region-specific resource requirements and allocation for effective decision making.
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 1393
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Author (up) Rachel Samuels; John Eric Taylor; Neda Mohammadi
Title The Sound of Silence: Exploring How Decreases in Tweets Contribute to Local Crisis Identification 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 696-704
Keywords Crisis informatics, emergency response, flooding, hurricanes, social media
Abstract Recent research has identified a correlation between increasing Twitter activity and incurred damage in disasters. This research, however, fails to account for localized emergencies occurring in areas in which people have lost power, otherwise lack internet connectivity, or are uncompelled to Tweet during a disaster. In this paper, we analyze the correlation between daily Tweet counts and FEMA Building Level Damage Assessments during Hurricane Harvey. We find that the absolute deviation of Tweet counts from steady state is a potentially useful tool for the evolving information needs of emergency responders. Our results show this to be a more consistent and persistent metric for flood damage across the full temporal extent of the disaster. This shows that, when considering the varied information needs of emergency responders, social media tools that seek to identify emergencies need to consider both where Tweet counts are increasing and where they are dropping off.
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 2143
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Author (up) Raquel Gimenez; Leire Labaka; Jose Mari Sarriegi; Josune Hernantes
Title Development of a Virtual Community of Practice on Natural Disasters 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 Crisis Management; knowledge sharing; lessons learned; natural disasters; Virtual Communities of Practice (VCoPs)
Abstract This research identifies from literature principles of successful Virtual Communities of Practice (VCoPs) and explains how they have been fulfilled in the development of a VCoP that aims at contributing to knowledge sharing on natural disasters. The developed VCoP involves 70 experts in dealing with natural disasters from different hierarchical levels, organizations and nationalities of Europe. The VCoP has been developed within a European project from the 7th framework program. During the project three workshops were arranged for the members of the VCoP to know each other and to develop a living document. The living document is a web based tool used by the VCoP to share documents and insights, and it helps VCoP members networking. This paper provides direction for developing a VCoP to exchange lessons learned reports among crisis managers and first responders, and it identifies barriers that hinder the use of the living document.
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 1230
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Author (up) Rémy Bossu; Robert Steed; Gilles Mazet-Roux; Caroline Etivant; Fréderic Roussel
Title THE EMSC TOOLS USED TO DETECT AND DIAGNOSE THE IMPACT OF GLOBAL EARTHQUAKES FROM DIRECT AND INDIRECT EYEWITNESSES? CONTRIBUTIONS 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 citizen science; crowdsourcing; flashsourcing; situation awareness; social media
Abstract This paper presents the strategy and operational tools developed and implemented at the Euro-Mediterranean Seismological Centre (EMSC) to detect and diagnose the impact of global earthquakes within minutes by combining « flashsourcing » (real time monitoring of website traffic) with social media monitoring and crowdsourcing.

This approach serves both the seismological community and the public and can contribute to improved earthquake response. It collects seismological observations, improves situation awareness from a few tens of seconds to a couple of hours after earthquake occurrence and is the basis of innovative targeted real time public information services.

We also show that graphical input methods can improve crowdsourcing tools both for the increasing use of mobile devices and to erase language barriers. Finally we show how social network harvesting could provide information on indirect earthquake effects such as triggered landslides and fires, which are difficult to predict and monitor through existing geophysical networks.
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 1235
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Author (up) Reza Mazloom; HongMin Li; Doina Caragea; Muhammad Imran; Cornelia Caragea
Title Classification of Twitter Disaster Data Using a Hybrid Feature-Instance Adaptation Approach 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 727-735
Keywords Tweet classification, Domain adaptation, Matrix factorization, k-Nearest Neighbors, Disaster response
Abstract Huge amounts of data that are generated on social media during emergency situations are regarded as troves of critical information. The use of supervised machine learning techniques in the early stages of a disaster is challenged by the lack of labeled data for that particular disaster. Furthermore, supervised models trained on labeled data from a prior disaster may not produce accurate results, given the inherent variation between the current and the prior disasters. To address the challenges posed by the lack of labeled data for a target disaster, we propose to use a hybrid feature-instance adaptation approach based on matrix factorization and the k nearest neighbors algorithm, respectively. The proposed hybrid adaptation approach is used to select a subset of the source disaster data that is representative for the target disaster. The selected subset is subsequently used to learn accurate Naive Bayes classifiers for the target disaster.
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 2146
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Author (up) Richard McCreadie; Cody Buntain; Ian Soboroff
Title Incident Streams 2019: Actionable Insights and How to Find Them 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 744-760
Keywords Emergency Management, Crisis Informatics, Real-time, Twitter, Categorization.
Abstract The ubiquity of mobile internet-enabled devices combined with wide-spread social media use during emergencies is posing new challenges for response personnel. In particular, service operators are now expected to monitor these online channels to extract actionable insights and answer questions from the public. A lack of adequate tools makes this monitoring impractical at the scale of many emergencies. The TREC Incident Streams (TREC-IS) track drives research into solving this technology gap by bringing together academia and industry to develop techniques for extracting actionable insights from social media streams during emergencies. This paper covers the second year of TREC-IS, hosted in 2019 with two editions, 2019-A and 2019-B, contributing 12 new events and approximately 20,000 new tweets across 25 information categories, with 15 research groups participating across the world. This paper provides an overview of these new editions, actionable insights from data labelling, and the automated techniques employed by participant systems that appear most effective.
Address University of Glasgow; InfEco Lab, New Jersey Institute of Technology (NJIT); National Institute of Standards and Technology (NIST)
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 978-1-949373-27-67 ISBN 2411-3453 Medium
Track Social Media for Disaster Response and Resilie Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management
Notes richard.mccreadie@glasgow.ac.uk Approved no
Call Number Serial 2268
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