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Author |
Pooneh Mousavi; Cody Buntain |
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Title |
“Please Donate for the Affected”: Supporting Emergency Managers in Finding Volunteers and Donations in Twitter Across Disasters |
Type |
Conference Article |
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Year |
2022 |
Publication |
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2022 |
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Volume |
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Issue |
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Pages |
605-622 |
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Keywords |
social media; crisis in formatics; volunteers; donations; emergency support functions |
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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. |
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Address |
University of Maryland, College Park; University of Maryland, College Park |
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Place of Publication |
Tarbes, France |
Editor |
Rob Grace; Hossein Baharmand |
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Language |
English |
Summary Language |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-82-8427-099-9 |
Medium |
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Track |
Social Media for Crisis Management |
Expedition |
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Conference |
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Notes |
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Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2442 |
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Author |
Humaira Waqas; Muhammad Imran |
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Title |
#CampFireMissing: An Analysis of Tweets About Missing and Found People From California Wildfires |
Type |
Conference Article |
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Year |
2019 |
Publication |
Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management |
Abbreviated Journal |
Iscram 2019 |
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Volume |
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Issue |
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Pages |
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Keywords |
social media, Twitter, missing and found people, California wildfires, disaster response |
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Abstract |
Several research studies have shown the importance of social media data for humanitarian aid. Among others,
the issue of missing and lost people during disasters and emergencies is crucial for disaster managers. This work
analyzes Twitter data from a recent wildfire event to determine its usefulness for the mitigation of the missing and
found people issue. Data analysis performed using various filtering techniques, and trend analysis revealed that
Twitter contains important information potentially useful for emergency managers and volunteers to tackle this
issue. Many tweets were found containing full names, partial names, location information, and other vital clues
which could be useful for finding missing people. |
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Address |
Qatar Computing Research Institute, Qatar |
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Corporate Author |
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Thesis |
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Publisher |
Iscram |
Place of Publication |
Valencia, Spain |
Editor |
Franco, Z.; González, J.J.; Canós, J.H. |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-84-09-10498-7 |
Medium |
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Track |
T8- Social Media in Crises and Conflicts |
Expedition |
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Conference |
16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
1915 |
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Author |
Lise Ann St. Denis; Amanda Lee Hughes; Jeremy Diaz; Kylen Solvik; Maxwell B. Joseph; Jennifer K. Balch |
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Title |
'What I Need to Know is What I Don't Know!': Filtering Disaster Twitter Data for Information from Local Individuals |
Type |
Conference Article |
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Year |
2020 |
Publication |
ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2020 |
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Volume |
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Issue |
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Pages |
730-743 |
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Keywords |
Crisis Informatics, Social Media, Emergency Management, Situational Awareness. |
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Abstract |
We report on the design, development, and evaluation of a user labeling framework for social media monitoring by emergency responders. By labeling Twitter user accounts based on behavior and content, this novel approach identifies tweets from accounts belonging to Individuals generating Personalized content and captures information that might otherwise be missed. We evaluate the framework using training data from the 2018 Camp, Woolsey, and Hill fires. Approximately 30% of the Individual-Personalized tweets contain first-hand information, providing a rich stream of content for social media monitoring. Because it can quickly eliminate most redundant tweets, this framework could be a critical first step in an end-to-end information extraction pipeline. It may also generalize more easily for new disaster events since it relies on general user account attributes rather than tweet content. We conclude with next steps for refining and evaluating our framework in near real-time during a disaster response. |
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Address |
CIRES, Earth Lab, University of Colorado, Boulder; Crisis Informatics Lab Brigham Young University; Institute for Computational and Data Sciences, Department of Geography, Penn State University; CIRES, Earth Lab, Department of Geography, University of Colorado, Boulder; CIRES, Earth Lab, University of Colorado, Boulder; CIRES, Earth Lab, Department of Geography, University of Colorado, Boulder |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-27-66 |
ISBN |
2411-3452 |
Medium |
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Track |
Social Media for Disaster Response and Resilie |
Expedition |
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Conference |
17th International Conference on Information Systems for Crisis Response and Management |
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Notes |
Lise.St.Denis@Colorado.edu |
Approved |
no |
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Call Number |
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Serial |
2267 |
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Author |
Francesca Comunello; Simone Mulargia |
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Title |
A #cultural_change is needed. Social media use in emergency communication by Italian local level institutions |
Type |
Conference Article |
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Year |
2017 |
Publication |
Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management |
Abbreviated Journal |
Iscram 2017 |
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Volume |
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Issue |
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Pages |
512-521 |
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Keywords |
Social media; local level; emergency communication; barriers |
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Abstract |
We discuss the results of a research project aimed at exploring the use of social media in emergency communication by officers operating at a local level. We performed 16 semi-structured interviews with national level expert informants, and with officers operating at the municipality and province (prefectures) level in an Italian region (respondents were selected based on their involvement in emergency communication and/or emergency management processes). Social media usage appears distributed over a continuum of engagement, ranging from very basic usage to using social media by adopting a broadcasting approach, to deeper engagement, which also includes continuous interaction with citizens. Two main attitudes emerge both in the narrative style and in social media representations: some respondents seem to adopt an institutional attitude, while others adopt a practical-professional attitude. Among the main barriers to a broader adoption of social media, cultural considerations seem to prevail, along with the lack of personnel, a general concern toward social media communication reliability, and the perceived distance between the formal role of institutions and the informal nature of social media communication. |
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Address |
LUMSA University, Rome, Italy; Sapienza University of Rome, Italy |
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Corporate Author |
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Thesis |
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Publisher |
Iscram |
Place of Publication |
Albi, France |
Editor |
Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
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Medium |
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Track |
Social Media Studies |
Expedition |
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Conference |
14th International Conference on Information Systems for Crisis Response And Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
2039 |
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Author |
Dario Salza; Edoardo Arnaudo; Giacomo Blanco; Claudio Rossi |
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Title |
A 'Glocal' Approach for Real-time Emergency Event Detection in Twitter |
Type |
Conference Article |
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Year |
2022 |
Publication |
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2022 |
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Volume |
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Issue |
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Pages |
570-583 |
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Keywords |
Emergency; Event Detection; Social Media; Twitter; Incremental Clustering |
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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. |
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Address |
LINKS Foundation; LINKS Foundation; LINKS Foundation; LINKS Foundation |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
Tarbes, France |
Editor |
Rob Grace; Hossein Baharmand |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-82-8427-099-9 |
Medium |
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Track |
Social Media for Crisis Management |
Expedition |
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Conference |
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Notes |
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Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2440 |
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Author |
Robert Power; Bella Robinson; John Colton; Mark Cameron |
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Title |
A Case Study for Monitoring Fires with Twitter |
Type |
Conference Article |
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Year |
2015 |
Publication |
ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2015 |
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Volume |
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Issue |
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Pages |
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Keywords |
Disaster Management; Situational Awareness; social media; Twitter |
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Abstract |
This paper presents a user configurable monitoring system to track in near-real-time tweets describing fire events. The system targets fire related words in a user defined region of interest published on Twitter which are further processed by a text classifier to determine if they describe a known fire event of interest. The system was motivated from a case study that examined a corpus of tweets posted during active bushfires. This demonstrated that useful information is available on Twitter about fire events from people who are in the vicinity.
We present an overview of the system describing how it is initially configured by a user to focus on specific fire events in Australia, the development of a text classifier to identify tweets of interest, especially those with accompanying photos, and the monitoring system that can track multiple events at once. |
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Publisher |
University of Agder (UiA) |
Place of Publication |
Kristiansand, Norway |
Editor |
L. Palen; M. Buscher; T. Comes; A. Hughes |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9788271177881 |
Medium |
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Track |
Social Media Studies |
Expedition |
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Conference |
ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
yes |
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Call Number |
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Serial |
1237 |
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Author |
Therese Habig; Richard Lüke; Simon Gehlhar; Torben Sauerland; Daniel Tappe |
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Title |
A Consolidated Understanding of Disaster Community Technologies |
Type |
Conference Article |
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Year |
2021 |
Publication |
ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2021 |
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Volume |
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Issue |
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Pages |
778-791 |
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Keywords |
Disaster Community Technologies, social media and crowdsourcing, categorization and classification schema, knowledge base |
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Abstract |
Since the beginning of this millennium, there has been an increasing use of social media and crowdsourcing (SMCS) technologies in disaster situations (Reuter & Kaufhold, 2018). Disaster management organizations and corresponding research are increasingly working on ways of integrating SMCS into the processes of crisis management. In a changing technological landscape to address disasters, and with increasing diversity of stakeholders in disasters, the purpose of this research is to provide an overview of technologies for SMCS within disasters to improve community resilience. The identified and analyzed technologies are summarized under the term “Disaster Community Technologies” (DCT). The paper presents a classification schema (the “DCT-schema”) for those technologies. The goal is to generate an overview of DCT in a rapidly evolving environment and to provide the practical benefit for different stakeholders to identify the right one from the overview. |
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Address |
safety innovation center; safety innovation center; safety innovation center; safety innovation center; safety innovation center |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-61-5 |
ISBN |
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Medium |
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Track |
Social Media for Disaster Response and Resilience |
Expedition |
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Conference |
18th International Conference on Information Systems for Crisis Response and Management |
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Notes |
habig@safetyinnovation.center |
Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2373 |
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Author |
Daniel Link; Bernd Hellingrath; Jie Ling |
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Title |
A Human-is-the-Loop Approach for Semi-Automated Content Moderation |
Type |
Conference Article |
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Year |
2016 |
Publication |
ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2016 |
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Volume |
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Issue |
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Pages |
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Keywords |
Disaster Management; Social Media Analysis; Human-Is-The-Loop; Content Moderation; Supervised Machine Learning |
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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. |
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Corporate Author |
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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 |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3388 |
ISBN |
978-84-608-7984-9 |
Medium |
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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 |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
1401 |
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Author |
Firoj Alam; Ferda Ofli; Muhammad Imran; Michael Aupetit |
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Title |
A Twitter Tale of Three Hurricanes: Harvey, Irma, and Maria |
Type |
Conference Article |
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Year |
2018 |
Publication |
ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2018 |
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Volume |
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Issue |
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Pages |
553-572 |
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Keywords |
social media, artificial intelligence, image processing, supervised classification, disaster management |
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Abstract |
People increasingly use microblogging platforms such as Twitter during natural disasters and emergencies. Research studies have revealed the usefulness of the data available on Twitter for several disaster response tasks. However, making sense of social media data is a challenging task due to several reasons such as limitations of available tools to analyze high-volume and high-velocity data streams. This work presents an extensive multidimensional analysis of textual and multimedia content from millions of tweets shared on Twitter during the three disaster events. Specifically, we employ various Artificial Intelligence techniques from Natural Language Processing and Computer Vision fields, which exploit different machine learning algorithms to process the data generated during the disaster events. Our study reveals the distributions of various types of useful information that can inform crisis managers and responders as well as facilitate the development of future automated systems for disaster management. |
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Publisher |
Rochester Institute of Technology |
Place of Publication |
Rochester, NY (USA) |
Editor |
Kees Boersma; Brian Tomaszeski |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-0-692-12760-5 |
Medium |
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Track |
Social Media Studies |
Expedition |
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Conference |
ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
2131 |
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Author |
Julien Coche; Jess Kropczynski; Aurélie Montarnal; Andrea Tapia; Frédérick Bénaben |
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Title |
Actionability in a Situation Awareness world: Implications for social media processing system design |
Type |
Conference Article |
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Year |
2021 |
Publication |
ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2021 |
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Volume |
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Issue |
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Pages |
994-1001 |
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Keywords |
Actionable Information, Situation Awareness, Social Media, Crisis Management |
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Abstract |
The field of crisis informatics now has a decade-long history of designing tools that leverage social media to support decision-makers situation awareness. Despite this history, there remains few examples of these tools adopted by practitioners. Recent fieldwork with public safety answering points and first responders has led to an awareness of the need for tools that gather actionable information, rather than situational awareness alone. This paper contributes to an ongoing discussion about these concepts by proposing a model that embeds the concept of actionable information into Endsley's model of situation awareness. We also extend the insights of this model to the design implications of future information processing systems. |
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Address |
IMT Mines Albi; University of Cincinnati; Ecole des Mines d'Albi Carmaux; The Pennsylvania State University; Ecole des Mines d'Albi-Carmaux |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-61-5 |
ISBN |
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Medium |
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Track |
Visions for Future Crisis Management |
Expedition |
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Conference |
18th International Conference on Information Systems for Crisis Response and Management |
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Notes |
coche.emac@gmail.com |
Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2391 |
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Author |
Keri K. Stephens; Jessica L. Ford; Ashley Barrett; Michael J. Mahometa |
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Title |
Alert networks of ICTs and sources in campus emergencies |
Type |
Conference Article |
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Year |
2014 |
Publication |
ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2014 |
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Volume |
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Issue |
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Pages |
652-661 |
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Keywords |
Information systems; Mobile devices; Risk management; Emergency alerts; Emergency management; ICTs; Safety communications; Social media; Social networking (online) |
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Abstract |
This study contributes an understanding of how ICTs and varying information sources work together during emergency alerts. It builds on the prior work on campus active shooter events by examining an organization that used a range of ICTs including mobile devices, social media, organizational tools, and news media, to notify their stakeholders about an emergency. The study design used a survey to capture the responses from a random sample of over 1000 stakeholders-students, faculty, and staff-who were notified of an active shooter emergency. The findings from the first three notifications suggest that messages reaching the most stakeholders were (a) sent by official sources through ICTs like mobile phones; (b) official email communication, and (c) messages that included face-to-face communication. While 11 different ICTs were included in the study, mass media (i.e., television and radio), and social media (Twitter and Facebook) did not function substantially in the emergency alert process. |
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Address |
University of Texas at Austin, United States |
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Publisher |
The Pennsylvania State University |
Place of Publication |
University Park, PA |
Editor |
S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih. |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9780692211946 |
Medium |
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Track |
Social Media in Crisis Response and Management |
Expedition |
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Conference |
11th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
974 |
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Author |
Online Media as a Means to Affect Public Trust in Emergency Responders |
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Title |
Amanda Lee Hughes; Apoorva Chauhan |
Type |
Conference Article |
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Year |
2015 |
Publication |
ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2015 |
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Volume |
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Issue |
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Pages |
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Keywords |
computer-mediated communication; crisis informatics; emergency response; social media; trust |
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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. |
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Address |
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Corporate Author |
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Thesis |
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Publisher |
University of Agder (UiA) |
Place of Publication |
Kristiansand, Norway |
Editor |
L. Palen; M. Buscher; T. Comes; A. Hughes |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
|
Edition |
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ISSN |
2411-3387 |
ISBN |
9788271177881 |
Medium |
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Track |
Social Media Studies |
Expedition |
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Conference |
ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management |
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Notes |
|
Approved |
yes |
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Call Number |
|
Serial |
1226 |
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Author |
Torbjørg Træland Meum |
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Title |
An action design research approach to developing emergency management systems |
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 |
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Volume |
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Issue |
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Pages |
175-179 |
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Keywords |
Civil defense; Disasters; Information systems; Management information systems; Risk management; Action research; Design research; Emergency management; Social media; User participation; Design |
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Abstract |
We propose Action Design Research (ADR) as an approach to promote user participation and mutual learning in the design and development of systems for emergency management based on social media technologies. We outline some design challenges related to the dynamic and evolving nature of social media, and emphasize an iterative design process that is strongly oriented toward collaboration and change involving both the researcher and the user community. In particular, we emphasize the transformative power of social media and argue for design approaches that take into account the new dimension of e-participation throughout the design process. |
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Address |
Department of Information Systems, University of Agder, Norway |
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Corporate Author |
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Thesis |
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Publisher |
The Pennsylvania State University |
Place of Publication |
University Park, PA |
Editor |
S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih. |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9780692211946 |
Medium |
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Track |
Community Engagement in Crisis Informatics Research |
Expedition |
|
Conference |
11th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
|
Serial |
772 |
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Author |
Kenneth Joseph; Peter M. Landwehr; Kathleen M. Carley |
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Title |
An approach to selecting keywords to track on twitter during a disaster |
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 |
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Volume |
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Issue |
|
Pages |
672-676 |
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Keywords |
Data mining; Disasters; Information systems; Keyword searching; Novel methodology; Situational awareness; Social media; Twitter; Social networking (online) |
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Abstract |
Several studies on Twitter usage during disasters analyze tweets collected using ad-hoc keywords pre-defined by researchers. While recent efforts have worked to improve this methodology, open questions remain about which keywords can be used to uncover tweets contributing to situational awareness (SA) and the quality of tweets returned using different terms. Herein we consider a novel methodology for uncovering relevant keywords one can use to search for tweets containing situational awareness. We provide a description of the methodology and initial results which suggest our approach may lead to better keywords to use for keyword searching during disasters. |
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Address |
Carnegie Mellon University, United States |
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Corporate Author |
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Thesis |
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Publisher |
The Pennsylvania State University |
Place of Publication |
University Park, PA |
Editor |
S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih. |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
|
Abbreviated Series Title |
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Series Volume |
|
Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9780692211946 |
Medium |
|
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Track |
Social Media in Crisis Response and Management |
Expedition |
|
Conference |
11th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
|
Approved |
no |
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|
Call Number |
|
Serial |
640 |
|
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Author |
Nathan Elrod; Pranav Mahajan; Monica Katragadda; Shane Halse; Jess Kropczynski |
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Title |
An Exploration of Methods Using Social Media to Examine Local Attitudes Towards Mask-Wearing During a Pandemic |
Type |
Conference Article |
|
Year |
2021 |
Publication |
ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2021 |
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Volume |
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Issue |
|
Pages |
345-358 |
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Keywords |
Social media analytics, situational awareness, sentiment analysis, n-grams, social network analysis |
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Abstract |
During the COVID-19 health crisis, local public offcials expend considerable energy encouraging citizens to comply with prevention measures in order to reduce the spread of infection. During the pandemic, mask-wearing has been accepted among health offcials as a simple preventative measure; however, some local areas have been more likely to comply than others. This paper explores methods to better understand local attitudes towards mask-wearing as a tool for public health offcials' situational awareness when preparing public messaging campaigns. This exploration compares three methods to explore local attitudes: sentiment analysis, n-grams, and hashtags. We also explore hashtag co-occurrence networks as a starting point to begin the filtering process. The results show that while sentiment analysis is quick and easy to employ, the results oer little insight into specific local attitudes towards mask-wearing, while examining hashtags and hashtag co-occurrence networks may be used a tool for a more robust understanding of local areas when attempting to gain situational awareness. |
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Address |
University of Cincinnati; University of Cincinnati; University of Cincinnati; University of Cincinnati; University of Cincinnati |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-61-5 |
ISBN |
|
Medium |
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Track |
Disaster Public Health & Healthcare Informatics in the Pandemic |
Expedition |
|
Conference |
18th International Conference on Information Systems for Crisis Response and Management |
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Notes |
elrodnj@ucmail.uc.edu |
Approved |
no |
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|
Call Number |
ISCRAM @ idladmin @ |
Serial |
2338 |
|
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Author |
Dilini Rajapaksha; Kacper Sokol; Jeffrey Chan; Flora Salim; Mukesh Prasad; Mahendra Samarawickrama |
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Title |
Analysing Donors’ Behaviour in Non-profit Organisations for Disaster Resilience |
Type |
Conference Article |
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Year |
2023 |
Publication |
Proceedings of the ISCRAM Asia Pacific Conference 2022 |
Abbreviated Journal |
Proc. ISCRAM AP 2022 |
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Volume |
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Issue |
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Pages |
258-267 |
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Keywords |
Disaster Response; Social Media; Donors’ Behaviour; Australian Bushfires |
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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. |
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Address |
RMIT University; RMIT University; RMIT University; UNSW Sydney; University of Technology Sydney; Australian Red Cross |
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Corporate Author |
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Thesis |
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Publisher |
Massey Unversity |
Place of Publication |
Palmerston North, New Zealand |
Editor |
Thomas J. Huggins, V.L. |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-0-473-66845-7 |
Medium |
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Track |
Social Media for Disaster Response |
Expedition |
|
Conference |
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Notes |
|
Approved |
no |
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|
Call Number |
ISCRAM @ idladmin @ |
Serial |
2499 |
|
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Author |
Ferda Ofli; Firoj Alam; Muhammad Imran |
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Title |
Analysis of Social Media Data using Multimodal Deep Learning for Disaster Response |
Type |
Conference Article |
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Year |
2020 |
Publication |
ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2020 |
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Volume |
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Issue |
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Pages |
802-811 |
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Keywords |
Multimodal Deep Learning, Multimedia Content, Natural Disasters, Crisis Computing, Social Media. |
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Abstract |
Multimedia content in social media platforms provides significant information during disaster events. The types of information shared include reports of injured or deceased people, infrastructure damage, and missing or found people, among others. Although many studies have shown the usefulness of both text and image content for disaster response purposes, the research has been mostly focused on analyzing only the text modality in the past. In this paper, we propose to use both text and image modalities of social media data to learn a joint representation using state-of-the-art deep learning techniques. Specifically, we utilize convolutional neural networks to define a multimodal deep learning architecture with a modality-agnostic shared representation. Extensive experiments on real-world disaster datasets show that the proposed multimodal architecture yields better performance than models trained using a single modality (e.g., either text or image). |
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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 |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-27-71 |
ISBN |
2411-3457 |
Medium |
|
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Track |
Social Media for Disaster Response and Resilie |
Expedition |
|
Conference |
17th International Conference on Information Systems for Crisis Response and Management |
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Notes |
fofli@hbku.edu.qa |
Approved |
no |
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|
Call Number |
|
Serial |
2272 |
|
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Author |
Hannah Van Wyk; Kate Starbird |
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Title |
Analyzing Social Media Data to Understand How Disaster-Affected Individuals Adapt to Disaster-Related Telecommunications Disruptions |
Type |
Conference Article |
|
Year |
2020 |
Publication |
ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2020 |
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Volume |
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Issue |
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Pages |
704-717 |
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Keywords |
Telecommunications, Adaptations, Social Media, Cellular Phone Service, Wi-Fi Access. |
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Abstract |
Information is a critical need during disasters such as hurricanes. Increasingly, people are relying upon cellular and internet-based technology to communicate that information--modalities that are acutely vulnerable to the disruptions to telecommunication infrastructure that are common during disasters. Focusing on Hurricane Maria (2017) and its long-term impacts on Puerto Rico, this research examines how people affected by severe and sustained disruptions to telecommunications services adapt to those disruptions. Leveraging social media trace data as a window into the real-time activities of people who were actively adapting, we use a primarily qualitative approach to identify and characterize how people changed their telecommunications practices and routines--and especially how they changed their locations--to access Wi-Fi and cellular service in the weeks and months after the hurricane. These findings have implications for researchers seeking to better understand human responses to disasters and responders seeking to identify strategies to support affected populations. |
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Address |
University of Washington; University of Washington |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
|
Series Title |
|
Abbreviated Series Title |
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Series Volume |
|
Series Issue |
|
Edition |
|
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ISSN |
978-1-949373-27-64 |
ISBN |
2411-3450 |
Medium |
|
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Track |
Social Media for Disaster Response and Resilie |
Expedition |
|
Conference |
17th International Conference on Information Systems for Crisis Response and Management |
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Notes |
hcvw@uw.edu |
Approved |
no |
|
|
Call Number |
|
Serial |
2265 |
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Author |
Nada Matta; Thomas Godard; Guillaume Delatour; Ludovic Blay; Franck Pouzet; Audrey Senator |
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Title |
Analyzing Social Media in Crisis Management Using Expertise Feedback Modelling |
Type |
Conference Article |
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Year |
2021 |
Publication |
ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2021 |
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Volume |
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Issue |
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Pages |
17-27 |
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Keywords |
Social Media analysis, TextMining, sentiment analysis, crisis management, decision making |
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Abstract |
Currently social media are largely used in interactions, especially in crisis situations. We note a big volume of interactions around events. Observing these interactions give information even to alert the existence of an incident, event, or to understand the expansion of a problem. Crisis management actors observe social media to be aware about this type of information in order to consider them in their decisions. Specific organizations are founded in order to observe social media interactions and send their analysis to rescue and crisis management actors. In our work, an experience feedback of this type of organizations (VISOV, a crisis social media analysis association) is capitalized in order to emphasize from one side, main dimensions of this analysis and from another side, to simulate some aspects using TextMining that help to explore big volume of data. |
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Address |
University of Technology of Troyes; University of Technology of Troyes; University of Technology of Troyes; VISOV; CS Group; ENSOSP |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-61-5 |
ISBN |
|
Medium |
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Track |
AI and Intelligent Systems for Crises and Risks |
Expedition |
|
Conference |
18th International Conference on Information Systems for Crisis Response and Management |
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Notes |
nada.matta@utt.fr |
Approved |
no |
|
|
Call Number |
ISCRAM @ idladmin @ |
Serial |
2309 |
|
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Author |
Nils Bourgon; Benamara Farah; Alda Mari; Véronique Moriceau; Gaetan Chevalier; Laurent Leygue; Yasmine Djadda |
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Title |
Are Sudden Crises Making me Collapse? Measuring Transfer Learning Performances on Urgency Detection |
Type |
Conference Article |
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Year |
2022 |
Publication |
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2022 |
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Volume |
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Issue |
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Pages |
701-709 |
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Keywords |
Sudden crises; Transfer learning; Few-shot learning; Zero-shot learning; Social media content |
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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. |
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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 |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
Tarbes, France |
Editor |
Rob Grace; Hossein Baharmand |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-82-8427-099-9 |
Medium |
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Track |
Social Media for Crisis Management |
Expedition |
|
Conference |
|
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Notes |
|
Approved |
no |
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|
Call Number |
ISCRAM @ idladmin @ |
Serial |
2449 |
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Author |
Arjen Schmidt; Jeroen Wolbers; Kees Boersma; Julie Ferguson; Peter Groenwegen |
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Title |
Are you Ready2Help? Dilemmas in organizing citizen response to disaster |
Type |
Conference Article |
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Year |
2016 |
Publication |
ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2016 |
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Volume |
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Issue |
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Pages |
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Keywords |
Citizen Response; Social Media; Net-Centric Coordination; Command And Control |
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Abstract |
Over the last decade, the disaster response landscape is increasingly complemented by voluntary citizen initiatives on digital platforms. These developments have opened up opportunities for response agencies and NGOs to organize local community involvement. In this paper we focus on the question how citizen involvement can be proactively organized toward disaster relief and what kind of dilemmas may arise in this process. We studied Ready2Help, an online platform developed by the Dutch Red Cross. Bringing together 36.000 volunteers, the platform plays a significant role in addressing the current refugee crisis. In our analysis we demonstrate the platform?s potential, but also note a tension between control and cooperation. Our results indicate that, in contrast to their initial objective, during the crisis the Red Cross falls back on principles of control to organize citizen response efforts. We end by discussing our future research agenda aimed at bridging formal and emergent citizen responses. |
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Address |
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Corporate Author |
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Thesis |
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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 |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3388 |
ISBN |
978-84-608-7984-9 |
Medium |
|
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Track |
Community Engagement and Practitioner Studies |
Expedition |
|
Conference |
13th International Conference on Information Systems for Crisis Response and Management |
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Notes |
|
Approved |
no |
|
|
Call Number |
ISCRAM @ idladmin @ |
Serial |
1411 |
|
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Author |
Oleg Aulov; Adam Price; Milton Halem |
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Title |
AsonMaps: A platform for aggregation visualization and analysis of disaster related human sensor network observations |
Type |
Conference Article |
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Year |
2014 |
Publication |
ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2014 |
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Volume |
|
Issue |
|
Pages |
802-806 |
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Keywords |
Data visualization; Disaster prevention; Disasters; Information systems; Population statistics; Sensor networks; Visualization; Citizen science; Crowdsourcing; Disaster management; Human sensor networks; Situational awareness; Social media datum; Emergency services |
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Abstract |
In this paper, we describe AsonMaps, a platform for collection, aggregation, visualization and analysis of near real-time, geolocated quantifiable information from a variety of heterogeneous social media outlets in order to provide emergency responders and other coordinating federal agencies not only with the means of listening to the affected population, but also to be able to incorporate this data into geophysical and probabilistic disaster forecast models that guide their response actions. Hurricane Sandy disaster is examined as a use-case scenario discussing the different types of quantifiable information that can be extracted from Instagram and Twitter. |
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Address |
University of Maryland Baltimore County, United States |
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Corporate Author |
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Thesis |
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Publisher |
The Pennsylvania State University |
Place of Publication |
University Park, PA |
Editor |
S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih. |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
|
Series Issue |
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Edition |
|
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ISSN |
2411-3387 |
ISBN |
9780692211946 |
Medium |
|
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Track |
Visual Analytics for Crisis Management |
Expedition |
|
Conference |
11th International ISCRAM Conference on Information Systems for Crisis Response and Management |
|
|
Notes |
|
Approved |
no |
|
|
Call Number |
|
Serial |
280 |
|
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Author |
Dat T. Nguyen; Firoj Alam; Ferda Ofli; Muhammad Imran |
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Title |
Automatic Image Filtering on Social Networks Using Deep Learning and Perceptual Hashing During Crises |
Type |
Conference Article |
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Year |
2017 |
Publication |
Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management |
Abbreviated Journal |
Iscram 2017 |
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Volume |
|
Issue |
|
Pages |
499-511 |
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Keywords |
social media; image processing; supervised classification; disaster management |
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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. |
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Address |
Qatar Computing Research Institute Hamad Bin Khalifa University Doha, Qatar |
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Publisher |
Iscram |
Place of Publication |
Albi, France |
Editor |
Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds |
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Language |
English |
Summary Language |
English |
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ISSN |
2411-3387 |
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Track |
Social Media Studies |
Expedition |
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Conference |
14th International Conference on Information Systems for Crisis Response And Management |
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Approved |
no |
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Call Number |
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Serial |
2038 |
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Author |
Sven Schaust; Maximilian Walther; Michael Kaisser |
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Title |
Avalanche: Prepare, manage, and understand crisis situations using social media analytics |
Type |
Conference Article |
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Year |
2013 |
Publication |
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2013 |
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Pages |
852-857 |
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Keywords |
Hardware; Crisis management; Event detection; Natural hazard; Social media analytics; Twitter; Information systems |
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Abstract |
The recent rise of Social Media services has created huge streams of information which can be very valuable in a variety of scenarios. One specific scenario that has received interest is how Social Media analytics can be beneficial in crisis situations. In this paper, we describe our vision for a Social Media-ready command and control center. As motivation for our work, we present a short analysis of tweets issued in NYC during Hurricane Sandy in late October 2012 and we give an overview of the architecture of our event detection subsystem. |
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Address |
AGT Group (R and D) GmbH, Germany |
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Publisher |
Karlsruher Institut fur Technologie |
Place of Publication |
KIT; Baden-Baden |
Editor |
T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
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Language |
English |
Summary Language |
English |
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ISSN |
2411-3387 |
ISBN |
9783923704804 |
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Track |
Social Media |
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Conference |
10th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
919 |
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Author |
Shane Errol Halse; Aurélie Montarnal; Andrea Tapia; Frederick Benaben |
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Title |
Bad Weather Coming: Linking social media and weather sensor data |
Type |
Conference Article |
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Year |
2018 |
Publication |
ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2018 |
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Pages |
507-515 |
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Keywords |
Twitter; weather; sensor data; social media |
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Abstract |
In this paper we leverage the power of citizen supplied data. We examined how both physical weather sensor data (obtained from the weather underground API) and social media data (obtained from Twitter) can serve to improve local community awareness during a severe weather event. A local tornado warning was selected due to its small scale and isolated geographic area, and only Twitter data found from within this geo-locational area was used. Our results indicate that during a severe weather event, an increase in weather activity obtained from the local weather sensors does correlate with an increase in local social media usage. The data found on social media also contains additional information from, and about the community of interest during the event. While this study focuses on a small scale event, it provides the groundwork for use during a much larger weather event. |
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Publisher |
Rochester Institute of Technology |
Place of Publication |
Rochester, NY (USA) |
Editor |
Kees Boersma; Brian Tomaszeski |
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Language |
English |
Summary Language |
English |
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ISSN |
2411-3387 |
ISBN |
978-0-692-12760-5 |
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Track |
Social Media Studies |
Expedition |
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Conference |
ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
2127 |
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