| Records |
| Author |
Carlo Alberto Bono; Barbara Pernici; Jose Luis Fernandez-Marquez; Amudha Ravi Shankar; Mehmet Oguz Mülâyim; Edoardo Nemni |
| Title |
TriggerCit: Early Flood Alerting using Twitter and Geolocation – A Comparison with Alternative Sources |
Type |
Conference Article |
| Year |
2022 |
Publication |
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2022 |
| Volume |
|
Issue |
|
Pages |
674-686 |
| Keywords |
Social Media; Disaster management; Early Alerting |
| Abstract |
Rapid impact assessment in the immediate aftermath of a natural disaster is essential to provide adequate information to international organisations, local authorities, and first responders. Social media can support emergency response with evidence-based content posted by citizens and organisations during ongoing events. In the paper, we propose TriggerCit: an early flood alerting tool with a multilanguage approach focused on timeliness and geolocation. The paper focuses on assessing the reliability of the approach as a triggering system, comparing it with alternative sources for alerts, and evaluating the quality and amount of complementary information gathered. Geolocated visual evidence extracted from Twitter by TriggerCit was analysed in two case studies on floods in Thailand and Nepal in 2021. The system respectively returned a large scale and a local scale alert, both in a timely manner and accompanied by a valid geographical description, while providing information complementary to existing disaster alert mechanisms. |
| Address |
Politecnico di Milano- DEIB;Politecnico di Milano- DEIB;University of Geneva;University of Geneva;Artificial Intelligence Research Institute (IIIA-CSIC); United Nations Satellite Centre (UNOSAT), United Nations Institute for Training and Research (UNITAR) |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
Tarbes, France |
Editor |
Rob Grace; Hossein Baharmand |
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
978-82-8427-099-9 |
Medium |
|
| Track |
Social Media for Crisis Management |
Expedition |
|
Conference |
|
| Notes |
|
Approved |
no |
| Call Number |
ISCRAM @ idladmin @ |
Serial |
2447 |
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| Author |
Chauhan, A. |
| Title |
Humor-Based COVID-19 Twitter Accounts |
Type |
Conference Article |
| Year |
2023 |
Publication |
Proceedings of the 20th International ISCRAM Conference |
Abbreviated Journal |
Iscram 2023 |
| Volume |
|
Issue |
|
Pages |
417-427 |
| Keywords |
COVID-19; Twitter; Humor; Crisis Named Resources |
| Abstract |
Crisis Named Resources (or CNRs) are social media pages and accounts named after a crisis event. Using the COVID-19 Pandemic as a case study, we identified and examined the role of CNRs that shared humor on Twitter. Our analyses showed that humor-based CNRs shared virus-related rumors, stigma, safety measures, opinions, sarcasm, and news updates. These resources also shared the overall anger and frustration over the year 2020. We conclude by discussing the critical role of humor based CNRs in crisis response. |
| Address |
Concordia University of Edmonton |
| 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/YHDI4576 |
Approved |
no |
| Call Number |
ISCRAM @ idladmin @ |
Serial |
2536 |
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| Author |
Soudip Roy Chowdhury; Muhammad Imran; Muhammad Rizwan Asghar; Amer-Yahia, S.; Carlos Castillo |
| Title |
Tweet4act: Using incident-specific profiles for classifying crisis-related messages |
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 |
834-839 |
| Keywords |
Artificial intelligence; Disaster prevention; Classification methods; Crisis informatics; Disaster management; Micro-blogging platforms; Microblogging; Precision and recall; Standard machines; Twitter data-analytics; Information systems |
| Abstract |
We present Tweet4act, a system to detect and classify crisis-related messages communicated over a microblogging platform. Our system relies on extracting content features from each message. These features and the use of an incident-specific dictionary allow us to determine the period type of an incident that each message belongs to. The period types are: Pre-incident (messages talking about prevention, mitigation, and preparedness), during-incident (messages sent while the incident is taking place), and post-incident (messages related to the response, recovery, and reconstruction). We show that our detection method can effectively identify incident-related messages with high precision and recall, and that our incident-period classification method outperforms standard machine learning classification methods. |
| Address |
University of Trento, Italy; Fehler Textmarke Nicht Definiert, University of Trento, Italy; CNRS, LIG, France; QCRI, Doha, 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 |
396 |
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| Author |
Christian Reuter; Gerhard Backfried; Marc-André Kaufhold; Fabian Spahr |
| Title |
ISCRAM turns 15: A Trend Analysis of all ISCRAM-Papers 2004-2017 |
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 |
445-458 |
| Keywords |
ISCRAM, Social Media, Trend Analysis, Systematic Literature Review, Vocabulary Analysis |
| Abstract |
In 2004, Information Systems for Crisis Response and Management (ISCRAM) was a new area of research. Pioneering researchers from different continents and disciplines found fellowship at the first ISCRAM work-shop. Around the same time, the use of social media in crises was first recognized in academia. In 2018, the 15th ISCRAM conference will take place, which gives us the possibility to look back on what has already been achieved with regard to IT support in crises using social media. With this article, we examine trends and devel-opments with a specific focus on social media. We analyzed all papers published at previous ISCRAMs (n=1339). Our analysis shows that various platforms, the use of language and coverage of different types of disasters follow certain trends – most noticeably a dominance of Twitter, English and crises with large impacts such as hurricanes or earthquakes can be seen. |
| Address |
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| Corporate Author |
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Thesis |
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| 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 |
2122 |
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| Author |
Christian Reuter; Marc-André Kaufhold; René Steinfort |
| Title |
Rumors, Fake News and Social Bots in Conflicts and Emergencies: Towards a Model for Believability in 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 |
583-591 |
| Keywords |
Social media; believability; measurement |
| Abstract |
The use of social media is gaining more and more in importance in ordinary life, but also in conflicts and emer-gencies. The social big data, generated by users, is partially also used as a source for situation assessment, e.g. to receive pictures or to assess the general mood. However, the information's believability is hard to control and can deceive. Rumors, fake news and social bots are phenomenons that challenge the easy consumption of social media. To address this, our paper explores the believability of content in social media. Based on foundations of infor-mation quality we conducted a literature study to derive a three-level model for assessing believability. It summa-rizes existing assessment approaches, assessment criteria and related measures. On this basis, we describe several steps towards the development of an assessment approach that works across different types of social media. |
| Address |
University of Siegen, Institute for Information Systems |
| 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 |
2046 |
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| Author |
Claire Laudy |
| Title |
Rumors detection on Social Media during 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 |
623-632 |
| Keywords |
Semantic information fusion; Uncertainty management; Ontology; Graph matching; conflict detection; rumors detection |
| Abstract |
Social Media monitoring has become a major issue in crisis and emergencies management. Indeed, social media may ease the sharing of information between citizens and Public Safety Organizations, but it also enables the rapid spreading of inaccurate information. As information is now provided and shared by anyone to anyone, information credibility is a major issue. We propose an approach to detect rumor in social media. This paper describes our work on semantic graph based information fusion, enhanced with uncertainty management capabilities. The uncertainty management capability enables managing the dierent level of credibility of actors of an emergency (dierent PSO oÿcers and citizens). Functions for information synthesis, conflicting information detection and information evaluation were developed and test during experimentation campaigns. The synthesis and conflicting information detection functionalities are very welcome by end-users. However, the uncertainty management is a combinatorial approach which remains a limitation for use with large amount of information. |
| Address |
Thales Research & Techology |
| 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 |
2050 |
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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 |
Cody Buntain; Richard Mccreadie; Ian Soboroff |
| Title |
Incident Streams 2021 Off the Deep End: Deeper Annotations and Evaluations in Twitter |
Type |
Conference Article |
| Year |
2022 |
Publication |
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2022 |
| Volume |
|
Issue |
|
Pages |
584-604 |
| Keywords |
Emergency Management; Crisis Informatics; Twitter; Categorization; Priorization; Multi-Modal; Public Safety; PSCR; TREC |
| Abstract |
This paper summarizes the final year of the four-year Text REtrieval Conference Incident Streams track (TREC-IS), which has produced a large dataset comprising 136,263 annotated tweets, spanning 98 crisis events. Goals of this final year were twofold: 1) to add new categories for assessing messages, with a focus on characterizing the audience, author, and images associated with these messages, and 2) to enlarge the TREC-IS dataset with new events, with an emphasis of deeper pools for sampling. Beyond these two goals, TREC-IS has nearly doubled the number of annotated messages per event for the 26 crises introduced in 2021 and has released a new parallel dataset of 312,546 images associated with crisis content – with 7,297 tweets having annotations about their embedded images. Our analyses of this new crisis data yields new insights about the context of a tweet; e.g., messages intended for a local audience and those that contain images of weather forecasts and infographics have higher than average assessments of priority but are relatively rare. Tweets containing images, however, have higher perceived priorities than tweets without images. Moving to deeper pools, while tending to lower classification performance, also does not generally impact performance rankings or alter distributions of information-types. We end this paper with a discussion of these datasets, analyses, their implications, and how they contribute both new data and insights to the broader crisis informatics community. |
| Address |
University of Maryland, College Park (UMD); University of Glasgow; National Institute of Standards and Technology (NIST) |
| 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 |
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| 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 |
2441 |
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| Author |
Sherri L. Condon; Jason R. Robinson |
| Title |
Communication media use in emergency response management |
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 |
687-696 |
| Keywords |
Information systems; Managers; Catastrophic event; Communication media; Emergency response; Emergency response management; Information and Communication Technologies; Instant messaging; Social media; University campus; Emergency services |
| Abstract |
The communications of emergency response managers were tracked during simulated catastrophic events at a university campus in the Washington, D.C. region. Local, state, and federal response managers interacted with each other and with students using a variety of communication media in order to investigate the utility of new communication channels for emergency response management. Students and emergency managers interacted using a Twitter-like platform and a portal built with Ushahidi crowd-sourcing software. The emergency managers also used a chat interface that included private instant messaging, telephone, and the county's existing emergency web portal. Their media use was analyzed along with the functions of their communications, and the patterns that emerged are described and quantified. |
| Address |
MITRE Corporation, United States |
| Corporate Author |
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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 |
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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 |
412 |
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| Author |
Congcong Wang; Paul Nulty; David Lillis |
| Title |
Crisis Domain Adaptation Using Sequence-to-Sequence Transformers |
Type |
Conference Article |
| Year |
2021 |
Publication |
ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2021 |
| Volume |
|
Issue |
|
Pages |
655-666 |
| Keywords |
Domain Adaptation, Emergency Response, Social media, Transformers |
| Abstract |
User-generated content (UGC) on social media can act as a key source of information for emergency responders incrisis situations. However, due to the volume concerned, computational techniques are needed to effectively filter and prioritise this content as it arises during emerging events. In the literature, these techniques are trained using annotated content from previous crises. In this paper, we investigate how this prior knowledge can be best leveraged for new crises by examining the extent to which crisis events of a similar type are more suitable for adaptation tonew events (cross-domain adaptation). Given the recent successes of transformers in various language processing tasks, we propose CAST: an approach for Crisis domain Adaptation leveraging Sequence-to-sequence Transformers. We evaluate CAST using two major crisis-related message classification datasets. Our experiments show that ourCAST-based best run without using any target data achieves the state of the art performance in both in-domain and cross-domain contexts. Moreover, CAST is particularly effective in one-to-one cross-domain adaptation when trained with a larger language model. In many-to-one adaptation where multiple crises are jointly used as the source domain, CAST further improves its performance. In addition, we find that more similar events are more likely to bring better adaptation performance whereas fine-tuning using dissimilar events does not help for adaptation. To aid reproducibility, we open source our code to the community. |
| Address |
University College Dublin; University College Dublin; University College Dublin |
| Corporate Author |
|
Thesis |
|
| Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
978-1-949373-61-5 |
ISBN |
|
Medium |
|
| Track |
Social Media for Disaster Response and Resilience |
Expedition |
|
Conference |
18th International Conference on Information Systems for Crisis Response and Management |
| Notes |
wangcongcongcc@gmail.com |
Approved |
no |
| Call Number |
ISCRAM @ idladmin @ |
Serial |
2362 |
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| Author |
Congcong Wang; Paul Nulty; David Lillis |
| Title |
Transformer-based Multi-task Learning for Disaster Tweet Categorisation |
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 |
705-718 |
| Keywords |
Disaster Response, Tweet Analysis, Transformers, Natural Language Processing |
| Abstract |
Social media has enabled people to circulate information in a timely fashion, thus motivating people to post messages seeking help during crisis situations. These messages can contribute to the situational awareness of emergency responders, who have a need for them to be categorised according to information types (i.e. the type of aid services the messages are requesting). We introduce a transformer-based multi-task learning (MTL) technique for classifying information types and estimating the priority of these messages. We evaluate the effectiveness of our approach with a variety of metrics by submitting runs to the TREC Incident Streams (IS) track: a research initiative specifically designed for disaster tweet classification and prioritisation. The results demonstrate that our approach achieves competitive performance in most metrics as compared to other participating runs. Subsequently, we find that an ensemble approach combining disparate transformer encoders within our approach helps to improve the overall effectiveness to a significant extent, achieving state-of-the-art performance in almost every metric. We make the code publicly available so that our work can be reproduced and used as a baseline for the community for future work in this domain. |
| Address |
University College Dublin; University College Dublin; University College Dublin |
| Corporate Author |
|
Thesis |
|
| Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
978-1-949373-61-5 |
ISBN |
|
Medium |
|
| Track |
Social Media for Disaster Response and Resilience |
Expedition |
|
Conference |
18th International Conference on Information Systems for Crisis Response and Management |
| Notes |
wangcongcongcc@gmail.com |
Approved |
no |
| Call Number |
ISCRAM @ idladmin @ |
Serial |
2366 |
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| Author |
Cornelia Caragea; Adrian Silvescu; Andrea Tapia |
| Title |
Identifying Informative Messages in Disasters using Convolutional Neural Networks |
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 |
Informative Tweets Classification; Disaster Events; Convolutional Neural Networks |
| Abstract |
Social media is a vital source of information during any major event, especially natural disasters. Data produced through social networking sites is seen as ubiquitous, rapid and accessible, and it is believed to empower average citizens to become more situationally aware during disasters and coordinate to help themselves. However, with the exponential increase in the volume of social media data, so comes the increase in data that are irrelevant to a disaster, thus, diminishing peoples? ability to find the information that they need in order to organize relief efforts, find help, and potentially save lives. In this paper, we present an approach to identifying informative messages in social media streams during disaster events. Our approach is based on Convolutional Neural Networks and shows significant improvement in performance over models that use the ?bag of words? and n-grams as features on several datasets of messages from flooding events. |
| 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 |
1397 |
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|
| |
| Author |
Cruz, J.A. dela; Hendrickx, I.; Larson, M. |
| Title |
Towards XAI for Information Extraction on Online Media Data for Disaster Risk Management |
Type |
Conference Article |
| Year |
2023 |
Publication |
Proceedings of the 20th International ISCRAM Conference |
Abbreviated Journal |
Iscram 2023 |
| Volume |
|
Issue |
|
Pages |
478-486 |
| Keywords |
Disaster Risk Management; Information Extraction; Explainable AI (XAI); Explainabilit |
| Abstract |
Disaster risk management practitioners have the responsibility to make decisions at every phase of the disaster risk management cycle: mitigation, preparedness, response and recovery. The decisions they make affect human life. In this paper, we consider the current state of the use of AI in information extraction (IE) for disaster risk management (DRM), which makes it possible to leverage disaster information in social media. We consolidate the challenges and concerns of using AI for DRM into three main areas: limitations of DRM data, limitations of AI modeling and DRM domain-specific concerns, i.e., bias, privacy and security, transparency and accountability, and hype and inflated expectations. Then, we present a systematic discussion of how explainable AI (XAI) can address the challenges and concerns of using AI for IE in DRM. |
| Address |
Centre for Language Studies, Centre for Language and Speech Technology, Radboud University; Centre for Language Studies, Centre for Language and Speech Technology, Radboud University; Centre for Language Studies,Inst. for Computing and Information Sciences,Radboud University |
| 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/BHAE3912 |
Approved |
no |
| Call Number |
ISCRAM @ idladmin @ |
Serial |
2541 |
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| |
|
| |
| Author |
Dharma Dailey; Kate Starbird |
| Title |
Visible skepticism: Community vetting after Hurricane Irene |
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 |
777-781 |
| Keywords |
Hardware; Crisis informatics; Crowdsourcing; Information diffusion; Journalism; Misinformation; Rumors; Social media; Information systems |
| Abstract |
Social media enable rapid, peer-to-peer information flow during crisis events, affordances that have both positive and negative consequences. The potential for spreading misinformation is a significant concern. Drawing on an empirical study of information-sharing practices in a crisis-affected community in the Catskill Mountains after Hurricane Irene, this paper describes how an ad hoc group of community members, led by a handful of journalists, employed specific work practices to mitigate misinformation. We illustrate how the group appropriated specific tools and performed visible skepticism, among other techniques, to help control the spread of false rumors. These findings suggest implications for the design of tools and the development of best practices for supporting community-led, crowd-powered response efforts during disasters. |
| Address |
Human Centered Design and Engineering, University of Washington, 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 |
421 |
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| |
| Author |
Daniel Link; Bernd Hellingrath; Jie Ling |
| Title |
A Human-is-the-Loop Approach for Semi-Automated Content Moderation |
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 |
Disaster Management; Social Media Analysis; Human-Is-The-Loop; Content Moderation; Supervised Machine Learning |
| Abstract |
Online social media has been recognized as a valuable information source for disaster management whose volume, velocity and variety exceed manual processing capacity. Current machine learning systems that support the processing of such data generally follow a human-in-the-loop approach, which has several inherent limitations. This work applies the human-is-the-loop concept from visual analytics to semi-automate a manual content moderation workflow, wherein human moderators take the dominant role. The workflow is instantiated with a supervised machine learning system that supports moderators with suggestions regarding the relevance and categorization of content. The instantiated workflow has been evaluated using in-depth interviews with practitioners and serious games. which suggest that it offers good compatibility with work practices in humanitarian assessment as well as improved moderation quality and higher flexibility than common approaches. |
| 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 |
1401 |
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| |
| Author |
Dario Salza; Edoardo Arnaudo; Giacomo Blanco; Claudio Rossi |
| Title |
A 'Glocal' Approach for Real-time Emergency Event Detection in Twitter |
Type |
Conference Article |
| Year |
2022 |
Publication |
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2022 |
| Volume |
|
Issue |
|
Pages |
570-583 |
| Keywords |
Emergency; Event Detection; Social Media; Twitter; Incremental Clustering |
| Abstract |
Social media like Twitter offer not only an unprecedented amount of user-generated content covering developing emergencies but also act as a collector of news produced by heterogeneous sources, including big and small media companies as well as public authorities. However, this volume, velocity, and variety of data constitute the main value and, at the same time, the key challenge to implement and automatic detection and tracking of independent emergency events from the real-time stream of tweets. Leveraging online clustering and considering both textual and geographical features, we propose, implement, and evaluate an algorithm to automatically detect emergency events applying a ‘glocal’ approach, i.e., offering a global coverage while detecting events at local (municipality level) scale. |
| Address |
LINKS Foundation; LINKS Foundation; LINKS Foundation; LINKS Foundation |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
Tarbes, France |
Editor |
Rob Grace; Hossein Baharmand |
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
978-82-8427-099-9 |
Medium |
|
| Track |
Social Media for Crisis Management |
Expedition |
|
Conference |
|
| Notes |
|
Approved |
no |
| Call Number |
ISCRAM @ idladmin @ |
Serial |
2440 |
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| |
| Author |
Shideh Dashti; Leysia Palen; Mehdi P. Heris; Kenneth M. Anderson; T. Jennings Anderson; Scott Anderson |
| Title |
Supporting disaster reconnaissance with social media data: A design-oriented case study of the 2013 Colorado floods |
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 |
632-641 |
| Keywords |
Disasters; Information systems; Crisis informatics; Engineering reconnaissance; Extreme events; Infrastructure performance; Situational awareness; Social media; Floods |
| Abstract |
Engineering reconnaissance following an extreme event is critical in identifying the causes of infrastructure failure and minimizing such consequences in similar future events. Typically, however, much of the data about infrastructure performance and the progression of geological phenomena are lost during the event or soon after as efforts move to the recovery phase. A better methodology for reliable and rapid collection of perishable hazards data will enhance scientific inquiry and accelerate the building of disaster-resilient cities. In this paper, we explore ways to support post-event reconnaissance through the strategic collection and reuse of social media data and other remote sources of information, in response to the September 2013 flooding in Colorado. We show how tweets, particularly with postings of visual data and references to location, may be used to directly support geotechnical experts by helping to digitally survey the affected region and to navigate optimal paths through the physical space in preparation for direct observation. |
| Address |
University of Colorado Boulder, United States; Federal Highway Administration, 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 |
423 |
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| |
| Author |
Dat T. Nguyen; Firoj Alam; Ferda Ofli; Muhammad Imran |
| Title |
Automatic Image Filtering on Social Networks Using Deep Learning and Perceptual Hashing During Crises |
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 |
499-511 |
| Keywords |
social media; image processing; supervised classification; disaster management |
| Abstract |
The extensive use of social media platforms, especially during disasters, creates unique opportunities for humanitarian organizations to gain situational awareness and launch relief operations accordingly. In addition to the textual content, people post overwhelming amounts of imagery data on social networks within minutes of a disaster hit. Studies point to the importance of this online imagery content for emergency response. Despite recent advances in the computer vision field, automatic processing of the crisis-related social media imagery data remains a challenging task. It is because a majority of which consists of redundant and irrelevant content. In this paper, we present an image processing pipeline that comprises de-duplication and relevancy filtering mechanisms to collect and filter social media image content in real-time during a crisis event. Results obtained from extensive experiments on real-world crisis datasets demonstrate the significance of the proposed pipeline for optimal utilization of both human and machine computing resources. |
| Address |
Qatar Computing Research Institute Hamad Bin Khalifa University 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 |
|
Serial |
2038 |
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| |
| Author |
Diana Fischer; Carsten Schwemmer; Kai Fischbach |
| Title |
Terror Management and Twitter: The Case of the 2016 Berlin Terrorist Attack |
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 |
459-468 |
| Keywords |
Terrorist attacks, social networking sites, social media, Twitter, topic modeling, terror management, sense-making |
| Abstract |
There is evidence that people increasingly use social networking sites like Twitter in the aftermath of terrorist attacks to make sense of the events at the collective level. This work-in-progress paper focuses on the content of Twitter messages related to the 2016 terrorist attack on the Berlin Christmas market. We chose topic modeling to investigate the Twitter data and the terror management theory perspective to understand why people used Twitter in the aftermath of the attack. In particular, by connecting people and providing a real-time communication channel, Twitter helps its users collectively negotiate their worldviews and re-establish self-esteem. We provide first results and discuss next steps. |
| 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 |
2123 |
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| Author |
Dilini Rajapaksha; Kacper Sokol; Jeffrey Chan; Flora Salim; Mukesh Prasad; Mahendra Samarawickrama |
| Title |
Analysing Donors’ Behaviour in Non-profit Organisations for Disaster Resilience |
Type |
Conference Article |
| Year |
2023 |
Publication |
Proceedings of the ISCRAM Asia Pacific Conference 2022 |
Abbreviated Journal |
Proc. ISCRAM AP 2022 |
| Volume |
|
Issue |
|
Pages |
258-267 |
| Keywords |
Disaster Response; Social Media; Donors’ Behaviour; Australian Bushfires |
| Abstract |
With the advancement and proliferation of technology, non-profit organisations have embraced social media platforms to improve their operational capabilities through brand advocacy, among many other strategies. The effect of such social media campaigns on these institutions, however, remains largely underexplored, especially during disaster periods. This work introduces and applies a quantitative investigative framework to understand how social media influence the behaviour of donors and their usage of these platforms throughout (natural) disasters. More specifically, we explore how on-line engagement – as captured by Facebook interactions and Google search trends – corresponds to the donors’ behaviour during the catastrophic 2019–2020 Australian bushfire season. To discover this relationship, we analyse the record of donations made to the Australian Red Cross throughout this period. Our exploratory study reveals that social media campaigns are effective in encouraging on-line donations made via a dedicated website. We also compare this mode of giving to more regular, direct deposit gifting. |
| Address |
RMIT University; RMIT University; RMIT University; UNSW Sydney; University of Technology Sydney; Australian Red Cross |
| 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 |
2499 |
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| |
| Author |
André Dittrich; Christian Lucas |
| Title |
A step towards real-time analysis of major disaster events based on tweets |
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 |
868-874 |
| Keywords |
Information systems; Semantics; Social networking (online); Crisis management; Event detection; Functional model; Micro-blogging platforms; Real time analysis; Semantic content analysis; Social sensors; Twitter; Disasters |
| Abstract |
The most popular micro blogging platform Twitter has been the topic of a variety of research papers related to disaster and crisis management. As an essential first step and basis for a real-time methodology to exploit Twitter for event detection, localization and ultimately semantic content analysis, a functional model to describe the amount of tweets during a day has been developed. It was derived from a corpus of messages in an exemplary area of investigation. To satisfy the different daily behavior on particular days, two types of days are distinguished in this paper. Moreover, keyword-adjusted data is used to point out the potential of semantic tweet analysis in following steps. The consideration of spatial event descriptions in relevant tweets could significantly improve and accelerate the perception of a disaster. The results from the conducted tests demonstrate the capability of the functional model to detect events with significant social impact in Twitter data. |
| Address |
Karlsruhe Institute of Technology (KIT), 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 |
452 |
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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 |
Tom Duffy; Richard McMaster; Chris Baber; Robert Houghton |
| Title |
Towards an ontology broker to improve cross-agency sharing in 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 |
Disasters; Information services; Information systems; Terrorism; Communication and collaborations; Disaster response; Emergency response; Information networks; Organisational boundaries; Shared understanding; Socio-technical networks; Standard operating procedures; Emergency services |
| Abstract |
Major incidents and disasters tend to be highly complex, contain high levels of uncertainty and may often force official responders to set aside their standard operating procedures and work collaboratively with a range of agencies and actors on the ground. Prior work has shown that establishing clear lines of communication and maintaining a shared understanding across organisational boundaries can be challenging to achieve, particularly in stressful and unusual circumstances. In the present paper we discuss ongoing work into specifying a meta-process for facilitating communication and collaboration based on the observation that common themes that emerge in communication within and across organisational boundaries can subsequently be tracked and built into an Ontology Broker. This work draws on experimental work in our laboratory, observations made in emergency control environments and, emphasised in this paper, lessons learned in the 2005 London bombings. © 2012 ISCRAM. |
| Address |
University of Birmingham, United Kingdom; University of Nottingham, 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 |
103 |
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| Author |
Elodie Fichet; John Robinson; Dharma Dailey; Kate Starbird |
| Title |
Eyes on the Ground: Emerging Practices in Periscope Use during Crisis Events |
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; Periscope; Twitter; Crisis Informatics; Emergency Management |
| Abstract |
This empirical analysis examines the use of the live-streaming application Periscope in three crises that occurred in 2015. Qualitative analyses of tweets relating to the Amtrak derailment in Philadelphia, Baltimore protests after Freddie Grey?s death, and Hurricane Joaquin flooding in South Carolina reveal that this recently deployed application is being used by both citizens and journalists for information sharing, crisis coverage and commentary. The accessibility and immediacy of live video directly from crisis situations, and the embedded chats which overlay on top of a video feed, extend the possibilities of real-time interaction between remote crowds and those on the ground in a crisis. These empirical findings suggest several potential challenges and opportunities for responders. |
| 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 |
ISCRAM @ idladmin @ |
Serial |
1391 |
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| Author |
Emma Potter |
| Title |
Balancing conflicting operational and communications priorities: social media use in an emergency management organization |
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 |
Emergency Management; Social Media; Internal Communication; Disasters; Ethnography |
| Abstract |
Social media are now widely used by affected members of the public during an emergency. As these platforms have become mainstream, governments have responded to the public?s expectation that information is available online, particularly during disasters. Emergency management organizations (EMOs) now widely use social media to communicate with the public alongside occasional intelligence gathering. While EMOs increasingly use social media, breakdowns in internal communication can inhibit the dissemination of timely information to their online followers. Drawing on a two-year ethnography at the Queensland Fire and Emergency Services (QFES), an Australian EMO, this paper outlines how the organization uses social media to disseminate information during emergencies and identifies the internal tensions around its use. These tensions include the prioritization of operational duties over public information responsibilities, and the difficulties around requesting and receiving information from operational personnel located on the ground. |
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| 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 |
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Edition |
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| ISSN |
2411-3388 |
ISBN |
978-84-608-7984-9 |
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| Track |
Social Media Studies |
Expedition |
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Conference |
13th International Conference on Information Systems for Crisis Response and Management |
| Notes |
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Approved |
no |
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Serial |
1398 |
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