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Author | Shivam Sharma; Cody Buntain | ||||
Title | Bang for your Buck: Performance Impact Across Choices in Learning Architectures for Crisis Informatics | 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 | 719-736 | ||
Keywords | Incident Streams; TREC; TRECIS; crisis informatics | ||||
Abstract | Over the years, with the increase in social media engagement, there has been an in increase in various pipelines to analyze, classify and prioritize crisis-related data on various social media platforms. These pipelines utilize various data augmentation methods to counter imbalanced crisis data, sophisticated and off-the-shelf models for training. However, there is a lack of comprehensive study which compares these methods for the various sections of a pipeline. In this study, we split a general crisis-related pipeline into 3 major sections, namely, data augmentation, model selection, and training methodology. We compare various methods for each of these sections and then present a comprehensive evaluation of which section to prioritize based on the results from various pipelines. We compare our results against two separate tasks, information classification and priority scoring for crisis-related tweets. Our results suggest that data augmentation, in general,improves the performance. However, sophisticated, state-of-the-art language models like DeBERTa only show performance gain in information classification tasks, and models like RoBERTa tend to show a consistent performance increase over our presented baseline consisting of BERT. We also show that, though training two separate task-specific BERT models does show better performance than one BERT model with multi-task learning methodology over an imbalanced dataset, multi-task learning does improve performance for more sophisticated model like DeBERTa with a much more balanced dataset after augmentation. | ||||
Address | New Jersey Institute of Technology; New Jersey Institute of Technology | ||||
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 | 2451 | ||
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Author | Shivam Sharma; Cody Buntain | ||||
Title | An Evaluation of Twitter Datasets from Non-Pandemic Crises Applied to Regional COVID-19 Contexts | 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 | 808-815 | ||
Keywords | covid19, twitter, trecis, cross-validation, machine learning, transfer learning | ||||
Abstract | In 2020, we have witnessed an unprecedented crisis event, the COVID-19 pandemic. Various questions arise regarding the nature of this crisis data and the impacts it would have on the existing tools. In this paper, we aim to study whether we can include pandemic-type crisis events with general non-pandemic events and hypothesize that including labeled crisis data from a variety of non-pandemic events will improve classification performance over models trained solely on pandemic events. To test our hypothesis we study the model performance for different models by performing a cross validation test on pandemic only held-out sets for two different types of training sets, one containing only pandemic data and the other a combination of pandemic and non-pandemic crisis data, and comparing the results of the two. Our results approve our hypothesis and give evidence of some crucial information propagation upon inclusion of non-pandemic crisis data to pandemic data. | ||||
Address | New Jersey Institute of Technology; New Jersey Institute of 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 | 2375 | ||
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Author | Shuji Nishikawa; Osamu Uchida; Keisuke Utsu | ||||
Title | Introduction of a Tracking Map to a Web Application for Location Recording and Rescue Request | Type | Conference Article | ||
Year | 2018 | Publication | Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. | Abbreviated Journal | Iscram Ap 2018 |
Volume | Issue | Pages | 459-468 | ||
Keywords | Location information, Rescue request, Disaster | ||||
Abstract | We developed a web application for location recording and rescue request using Twitter (T-Pl@ce). This application helps supported users (e.g., older adults, persons with disabilities, and children) who require support to share their location coordinates via Twitter. Supporting users (e.g., families, relatives, or neighbors) of the supported user can then check the location coordinates of the supported user when required. When the supported user needs to be rescued, he/she can post a rescue request on Twitter by pressing the “Rescue request” button on the application. In this study, we introduce the e-mail notification function to reliably notify a rescue request to the system administrator. In addition, to track the location of the supported user, we introduce a location tracking function. Then, the administrator, the emergency assistance employees (e.g., rescue experts or social workers), or the supporting user can refer to the request and the location tracking page and execute the support and rescue activities. | ||||
Address | Tokai University; Tokai University; Tokai University | ||||
Corporate Author | Thesis | ||||
Publisher | Massey Univeristy | Place of Publication | Albany, Auckland, New Zealand | Editor | Kristin Stock; Deborah Bunker |
Language | English | Summary Language | Original Title | ||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Track | Social Media and Community Engagement Supporting Resilience Building | Expedition | Conference | ||
Notes | Approved | no | |||
Call Number | Serial | 1660 | |||
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Author | Simon Tucker; Vitaveska Lanfranchi; Neil Ireson; Alfonso Sosa; Gregoire Burel; Fabio Ciravegna | ||||
Title | Straight to the information I need: Assessing collational interfaces for emergency response | Type | Conference Article | ||
Year | 2012 | Publication | ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2012 |
Volume | Issue | Pages | |||
Keywords | Information systems; Emergency response; Information overloads; Paper-based interfaces; Situational awareness; Social media; User study; Emergency services | ||||
Abstract | Collational interfaces gather information from a range of sources and present them to users. Information overload is tackled by processing information in the back-end and providing interactive means to filter and browse data. Such interfaces have applications in emergency response – giving users the right information to act effectively. In this paper we explore a collational interface for emergency response, carrying out a user study that compares it to a paper based interface and one which presents data without collating it. We demonstrate that a collational interface allows users to build a picture of an emergency, but not necessarily in less time. © 2012 ISCRAM. | ||||
Address | Department of Computer Science, University of Sheffield, United Kingdom; Knowledge Media Institute, Open University, United Kingdom | ||||
Corporate Author | Thesis | ||||
Publisher | Simon Fraser University | Place of Publication | Vancouver, BC | Editor | L. Rothkrantz, J. Ristvej, Z.Franco |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 2411-3387 | ISBN | 9780864913326 | Medium | |
Track | Social Media and Collaborative Systems | Expedition | Conference | 9th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
Notes | Approved | no | |||
Call Number | Serial | 221 | |||
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Author | Sofia Eleni Spatharioti; Rebecca Govoni; Jennifer S. Carrera; Sara Wylie; Seth Cooper | ||||
Title | A Required Work Payment Scheme for Crowdsourced Disaster Response: Worker Performance and Motivations | Type | Conference Article | ||
Year | 2017 | Publication | Proceedings of the 14th International Conference on Iformation Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2017 |
Volume | Issue | Pages | 475-488 | ||
Keywords | crowdsourcing; Amazon Mechanical Turk; payment; motivation; required work | ||||
Abstract | Crowdsourcing is an increasingly popular approach for processing data in response to disasters. While volunteer crowdsourcing may suÿce for high-profile disasters, paid crowdsourcing may be necessary to recruit workers for less prominent events. Thus, understanding the impact of payment schemes on worker behavior and motivation may improve outcomes. In this work, we presented workers recruited from Amazon Mechanical Turk with a disaster response task in which they could provide a variable number of image ratings. We paid workers a fixed amount to provide a minimum number of image ratings, allowing them to voluntarily provide more if desired; this allowed us to examine the impact of dierent amounts of required work. We found that requiring no ratings resulted in workers voluntary completing more work, and being more likely to indicate motivation related to interest on a post survey, than when small numbers of ratings were required. This is consistent with the motivational crowding-out eect, even in paid crowdsourcing. We additionally found that providing feedback on progress positively impacted the amount of work done. | ||||
Address | Northeastern University; Michigan State University | ||||
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 | 2036 | |||
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Author | Sofia Eleni Spatharioti; Sara Wylie; Seth Cooper | ||||
Title | Does Flight Path Context Matter? Impact on Worker Performance in Crowdsourced Aerial Imagery Analysis | 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 | 621-628 | ||
Keywords | crowdsourcing, Amazon Mechanical Turk, context | ||||
Abstract | Natural disasters result in billions of dollars in damages annually and communities left struggling with the difficult task of response and recovery. To this end, small private aircraft and drones have been deployed to gather images along flight paths over the affected areas, for analyzing aerial photography through crowdsourcing. However, due to the volume of raw data, the context and order of these images is often lost when reaching workers. In this work, we explored the effect of contextualizing a labeling task on Amazon Mechanical Turk, by serving workers images in the order they were collected on the flight and showing them the location of the current image on a map. We did not find a negative impact from the loss of contextual information, and found map context had a negative impact on worker performance. This may indicate that ordering images based on other criteria may be more effective. | ||||
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 | 2136 | |||
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Author | Sofia Eleni Spatharioti; Seth Cooper | ||||
Title | On Variety, Complexity, and Engagement in Crowdsourced Disaster Response Tasks | 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 | 489-498 | ||
Keywords | crowdsourcing; Amazon Mechanical Turk; variety; complexity; engagement | ||||
Abstract | Crowdsourcing is used to enlist workers as a resource for a variety of applications, including disaster response. However, simple tasks such as image labeling often feel monotonous and lead to worker disengagement. This provides a challenge for designing successful crowdsourcing systems. Existing research in the design of work indicates that task variety is a key factor in worker motivation. Therefore, we asked Amazon Mechanical Turk workers to complete a series of disaster response related subtasks, consisting of either image labeling or locating photographed areas on a map. We varied the frequency at which workers encountered the dierent subtask types, and found that switching subtask type at dierent frequencies impacted measures of worker engagement. This indicates that a certain amount of variety in subtasks may engage crowdsourcing workers better than uniform subtask types. | ||||
Address | Northeastern University | ||||
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 | 2037 | |||
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Author | Songhui Yue; Jyothsna Kondari; Aibek Musaev; Songqing Yue; Randy Smith | ||||
Title | Using Twitter Data to Determine Hurricane Category: An Experiment | 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 | 718-726 | ||
Keywords | Social Media Data, Hurricane Category, Twitter, Prediction | ||||
Abstract | Social media posts contain an abundant amount of information about public opinion on major events, especially natural disasters such as hurricanes. Posts related to an event, are usually published by the users who live near the place of the event at the time of the event. Special correlation between the social media data and the events can be obtained using data mining approaches. This paper presents research work to find the mappings between social media data and the severity level of a disaster. Specifically, we have investigated the Twitter data posted during hurricanes Harvey and Irma, and attempted to find the correlation between the Twitter data of a specific area and the hurricane level in that area. Our experimental results indicate a positive correlation between them. We also present a method to predict the hurricane category for a specific area using relevant Twitter data. | ||||
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 | 2145 | |||
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Author | Sooji Han; Fabio Ciravegna | ||||
Title | Rumour Detection on Social Media for Crisis Management | Type | Conference Article | ||
Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
Volume | Issue | Pages | |||
Keywords | Rumours, large-scale data, event summarisation, sub-event detection, social media analysis | ||||
Abstract | We address the problem of making sense of rumour evolution during crises and emergencies. We study how understanding and capturing emerging rumours can benefit decision makers during such event. To this end, we propose a two-step framework for detecting rumours during crises. In the first step, we introduce an algorithm to identify noteworthy sub-events in real time. In the second step, we introduce a graph-based text ranking method for summarising newsworthy sub-events while events unfold. We use temporal and content-based features to achieve the effective and real-time response and management of crises situations. These features can improve efficiency in the detection of key rumours in the context of a real-world application. The effectiveness of our method is evaluated over large-scale Twitter data related to real-world crises. The results show that our framework can efficiently and effectively capture key rumours circulated during natural and human-made disasters. |
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Address | The University of Sheffield, United Kingdom | ||||
Corporate Author | Thesis | ||||
Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
Notes | Approved | no | |||
Call Number | Serial | 1860 | |||
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Author | Sophie Gerstmann; Hans Betke; Stefan Sackmann | ||||
Title | Towards Automated Individual Communication for Coordination of Spontaneous Volunteers | Type | Conference Article | ||
Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
Volume | Issue | Pages | |||
Keywords | Spontaneous volunteers, chatbot, social media, system architecture | ||||
Abstract | In recent years, spontaneous volunteers often turned out to be a critical factor to overcome disaster situations and avoid further damages to life and assets. These Volunteers coordinate their activities using social media and mobile devices but are not integrated in usual command and control structures of disaster responders. The lack of professional disaster response knowledge leads to a waste of potential workforce or even dangerous situations for the volunteers. In this paper, a novel approach for a centralized coordination of spontaneous volunteers through disaster response professionals while using popular communication channels esp. messaging services (e.g. Facebook Messenger, WhatsApp) is presented. The architecture of a volunteer coordination system focusing on automated multi-channel communication is shown and the possibilities of a universal chatbot for individual assignment and scheduling of volunteers are discussed. The paper also provides first insights in a demonstrator system as a practical solution. |
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Address | Martin-Luther University Halle-Wittenberg, Germany | ||||
Corporate Author | Thesis | ||||
Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
Notes | Approved | no | |||
Call Number | Serial | 1965 | |||
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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 | St. Denis, L.A.; Hughes, A.L. | ||||
Title | Use of Statistics in Disaster by Local Individuals: An Examination of Tweets during COVID-19 | Type | Conference Article | ||
Year | 2023 | Publication | Proceedings of the 20th International ISCRAM Conference | Abbreviated Journal | Iscram 2023 |
Volume | Issue | Pages | 449-458 | ||
Keywords | Social Media; Statistics; COVID-19; Pandemic | ||||
Abstract | We report on how individuals local to the US state of Colorado used statistics in tweets to make sense of the early stages of the COVID-19 pandemic. Tweets provided insight into how people interpreted statistical data, sometimes incorrectly, which has implications for crisis responders tasked with understanding public perceptions and providing accurate information. With widespread concerns about the accuracy and quality of online information, we show how monitoring public reactions to and uses of statistics on social media is important for improving crisis communication. Findings suggest that statistics can be a powerful tool for making sense of a crisis and coping with the stress and uncertainty of a global, rapidly evolving event like the COVID-19 pandemic. We conclude with broader implications for how crisis responders might improve their communications around statistics to the public, and suggestions for how this research might be expanded to look at other types of disasters. | ||||
Address | CIRES, Earth Lab University of Colorado; Crisis Informatics Lab Brigham Young 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/KBIJ7756 | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2539 | ||
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Author | Starr Roxanne Hiltz; Amanda Hughes; Muhammad Imran; Linda Plotnick; Robert Power; Murray Turoff | ||||
Title | Requirements for Software to Support the use of Social Media in Emergency Management: A Delphi Study | Type | Conference Article | ||
Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
Volume | Issue | Pages | |||
Keywords | Social media, emergency management, crisis informatics, software requirements, Delphi method | ||||
Abstract | Social Media contain a wealth of information that could improve the situational awareness of Emergency Managers during a crisis, but many barriers stand in the way. These include information overload, making it impossible to deal with the flood of raw posts, and lack of trust in unverified crowdsourced data. The purpose of this project is to build a communications bridge between emergency responders and technologists who can provide the advances needed to realize social media?s full potential. We are employing a Delphi study survey design, which is a technique for exploring and developing consensus among a group of experts around a particular topic. Participants include emergency managers and technologists with experience in software to support the use of social media in crisis response, from many countries. The topics of the study are described and preliminary, partial results presented for Round 1 of the study, based on 33 responses. | ||||
Address | NJIT, United States of America;Brigham Young U.;Qatar Computing Research Inst.;Commonwealth Scientific and Industrial Research Organisation, Australia | ||||
Corporate Author | Thesis | ||||
Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
Notes | Approved | no | |||
Call Number | Serial | 1906 | |||
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Author | Starr Roxanne Hiltz; Jane Kushma; Linda Plotnick | ||||
Title | Use of Social Media by U.S. Public Sector Emergency Managers: Barriers and Wish Lists | 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 | 602-611 | ||
Keywords | Social media, emergency management, Twitter, Facebook | ||||
Abstract | Semi-structured interviews were conducted with U.S. public sector emergency managers to probe barriers to use of social media and reactions to possible software enhancements to support such use. The three most frequently described barriers were lack of personnel time to work on use of social media, lack of policies and guidelines for its use, and concern about the trustworthiness of pulled data. The most popular of the possible technological enhancements described for Twitter are filtering by category of user/contributor, and display of posts on a GIS system with a map-based display. | ||||
Address | NJIT, Newark NJ, United States; Jacksonville State U., AL, 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 | 1171 | |||
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Author | Starr Roxanne Hiltz; Linda Plotnick | ||||
Title | Dealing with information overload when using social media for emergency management: Emerging solutions | 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 | 823-827 | ||
Keywords | Civil defense; Information systems; Natural language processing systems; Risk management; Decision making process; Emergency management; Emergency response; Information overloads; NAtural language processing; Social convention; Social media; Trending topics; Disasters | ||||
Abstract | Several recent studies point the way to enabling emergency response managers to be able to find relevant posts and incorporate them into their sensemaking and decision making processes. Among the approaches that have improved the ability to find the most relevant information are the social conventions of creating topic groups and tags and of “retweeting;” the use of trained volunteers to filter and summarize posts for responders; automated notifications of trending topics; natural language processing of posts; techniques for identifying posts from the disaster site; and the use of GIS and crisis maps to visually represent the distribution of incidents. | ||||
Address | NJIT, Newark NJ, United States; Jacksonville State U., AL, United States | ||||
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 | 583 | |||
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Author | Stephen Kelly; Xiubo Zhang; Khurshid Ahmad | ||||
Title | Mining Multimodal Information on Social Media for Increased Situational Awareness | 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 | 613-622 | ||
Keywords | Spatio-temporal; Social media analysis; Multimodal analysis; Geolocation | ||||
Abstract | Social media platforms have become a source of high volume, real-time information describing significant events in a timely fashion. In this paper we describe a system for the real-time extraction of information from text and image content in Twitter messages and combine the spatio-temporal metadata of the messages to filter the data stream for emergency events and visualize the output on an interactive map. Twitter messages for a geographic region are monitored for flooding events by analysing the text content and images posted. Events detected are compared with a ground truth to see if information in social media correlates with actual events. We propose an Intrusion Index as part of this prototype to facilitate ethical harvesting of data. A map layer is created by the prototype system that visualises the analysis and filtered Twitter messages by geolocation. | ||||
Address | rinity College Dublin, Ireland | ||||
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 | 2049 | |||
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Author | Steve Peterson; Keri Stephens; Hemant Purohit; Amanda Hughes | ||||
Title | When Official Systems Overload: A Framework for Finding Social Media Calls for Help during Evacuations | Type | Conference Article | ||
Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
Volume | Issue | Pages | |||
Keywords | Disasters, social media, hurricanes, data, framework, public safety | ||||
Abstract | During large-scale disasters it is not uncommon for Public Safety Answering Points (e.g., 9-1-1) to encounter service disruptions or become overloaded due to call volume. As observed in the two past United States hurricane seasons, citizens are increasingly turning to social media whether as a consequence of their inability to reach 9-1-1, or as a preferential means of communications. Relying on past research that has examined social media use in disasters, combined with the practical knowledge of the first-hand disaster response experiences, this paper develops a knowledge-driven framework containing parameters useful in identifying patterns of shared information on social media when citizens need help. This effort explores the feasibility of determining differences, similarities, common themes, and time-specific discoveries of social media calls for help associated with hurricane evacuations. At a future date, validation of this framework will be demonstrated using datasets from multiple disasters. The results will lead to recommendations on how the framework can be modified to make it applicable as a generic disaster-type characterization tool. |
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Address | National Institutes of Health, United States of America;The University of Texas at Austin;George Mason University;Brigham Young University | ||||
Corporate Author | Thesis | ||||
Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
Notes | Approved | no | |||
Call Number | Serial | 1928 | |||
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Author | Steven Sheetz; Andrea Kavanaugh; Edward Fox; Riham Hassan; Seungwon Yang; Mohamed Magdy; Shoemaker Donald | ||||
Title | Information Uses and Gratifications Related to Crisis: Student Perceptions since the Egyptian Uprising | Type | Conference Article | ||
Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
Volume | Issue | Pages | |||
Keywords | Uses and gratifications theory; information sources; Internet; social media; structural equation modeling | ||||
Abstract | People use diverse sources of information, e.g., newspapers, TV, Internet news, social media, and face-to-face conversations, to make sense of crises. We apply uses and gratifications theory (UGT) and structural equation modeling to illustrate how using internet-based information sources since the political uprisings in Egypt influence perceptions of information satisfaction. Consistent with expectations we find that content and process gratifications constructs combine to explain information satisfaction, while social gratifications do not significantly influence satisfaction in the context of a crisis. This suggests that UGT is useful for evaluating the use of information technology in a context where information is limited in quantity and reliability. |
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Address | Virginia Tech, United States of America;Microsoft;Louisiana State University;Arab Academy of Science and Technology | ||||
Corporate Author | Thesis | ||||
Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
Notes | Approved | no | |||
Call Number | Serial | 1862 | |||
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Author | Sung-Yueh Perng; Monika Büscher; Lisa Wood; Ragnhild Halvorsrud; Michael E. Stiso; Leonardo Ramirez; Amro Al-Akkad | ||||
Title | Peripheral response: Microblogging during the 22/7/2011 Norway attacks | Type | Conference Article | ||
Year | 2012 | Publication | ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2012 |
Volume | Issue | Pages | |||
Keywords | Information systems; Microblogging; Norway attacks; Peripheral response; Resource coordinations; Situation awareness; Professional aspects | ||||
Abstract | This paper presents a case study of a very recent man-made crisis in Norway on 22 July, 2011, during which a single person first detonated a bomb in downtown Oslo and then killed 69 young people on the island of Utøya. It proposes a novel way of conceptualizing the public contribution to mobilization of resources using microblogging, particularly tweeting. By examining aspects of public and professional response to this crisis, the notion of peripheral response is developed in relation to emergent forms of agile and dialogic emergency response. Through examining the distributed efforts of responding to the crisis, the paper also revisits situation awareness and reflects upon the dynamic and constantly changing environment that social media and crises inhabit together. © 2012 ISCRAM. | ||||
Address | Lancaster University, United Kingdom; SINTEF, Norway; Fraunhofer FIT, Germany | ||||
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 | 187 | |||
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Author | Susanna Nilsson; Joel Brynielsson; Magdalena Granasen; Charlotte Hellgren; Sinna Lindquist; Mikael Lundin; Maribel Narganes Quijano; Jiri Trnka | ||||
Title | Making use of new media for pan-European crisis communication | 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 | Hardware; Alerting; Crisis Information; New media; Screening tool; Social media; Information systems | ||||
Abstract | Social or new media have over the past years become an integrated part of human communication, both as a means to establish and maintain social relationships, but also as a means of sharing and co-creating information. New media comes with an array of possibilities for individuals as well as organisations, corporations and authorities. Within the field of crisis communication new media possibilities, such as online sharing and social networking, has had an impact on the way crisis information is disseminated and updated. This paper addresses the issues related to using new media as a means of communicating crisis information and broadcasting alerting messages to the general population, and also discusses the role of new media in future pan-European alerting. It focuses on current and on-going research on social media for crisis communication. An extensive systematic literature review was done to identify factors that affect the use of social media for alerting and warning. These factors were mirrored in experiences, collected through interviews, in crisis communication organisations in three European regions (Sweden, Czech Republic and Spain). The factors finally form the basis for suggestions regarding the design of technological tools for both communication and information collection as part of a pan-European alerting system. © 2012 ISCRAM. | ||||
Address | Swedish Defence Research Agency, SE-164 90 Stockholm, Sweden; Tecnalia Research and Innovation, Parque Tecnológico de Bizkaia, E-48170 Zamudio, Spain | ||||
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 | 175 | |||
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Author | Sven Schaust; Maximilian Walther; Michael Kaisser | ||||
Title | Avalanche: Prepare, manage, and understand crisis situations using social media analytics | 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 | 852-857 | ||
Keywords | Hardware; Crisis management; Event detection; Natural hazard; Social media analytics; Twitter; Information systems | ||||
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. | ||||
Address | AGT Group (R and D) GmbH, 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 | 919 | |||
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Author | Takuya Oki | ||||
Title | Possibility of Using Tweets to Detect Crowd Congestion: A Case Study Using Tweets just before/after the Great East Japan Earthquake | 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 | 584-596 | ||
Keywords | Twitter, crowd congestion, time-series analysis, linguistic expression, disaster mitigation. | ||||
Abstract | During large earthquakes, it is critical to safely guide evacuation efforts and to prevent accidents caused by congestion. In this paper, we focus on detecting the degree of crowd congestion following an earthquake based on information posted to Social Networking Services (SNSs). This research uses text data posted to Twitter just before/after the occurrence of the Great East Japan Earthquake (11 March 2011 at 02:46 PM JST). First, we extract co-occurring place names, proper nouns, and time-series information from tweets about congestion in the Tokyo metropolitan area (TMA). Next, using these extracted data, we analyze the frequency and spatiotemporal characteristics of these tweets. Finally, we identify expressions that describe the degree of crowd congestion and discuss methods to quantify these expressions based on a questionnaire survey and tweets that contain a photograph. | ||||
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 | 2133 | |||
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Author | Tasneem, F.; Chakraborty, S.; Chy, A.N. | ||||
Title | An Early Synthesis of Deep Neural Networks to Identify Multimodal Informative Disaster Tweets | Type | Conference Article | ||
Year | 2023 | Publication | Proceedings of the 20th International ISCRAM Conference | Abbreviated Journal | Iscram 2023 |
Volume | Issue | Pages | 428-438 | ||
Keywords | Early Fusion; Crisis Tweets; BERT-LSTM; ResNet50; Multimodal Framework | ||||
Abstract | Twitter is always worthwhile in facilitating communication during disasters. It helps in raising situational awareness and undertaking disaster control actions as quickly as possible to alleviate the miseries. But the noisy essence of Twitter causes difficulty in distinguishing relevant information from the heterogeneous contents. Therefore, extracting informative tweets is a substantial task to help in crisis intervention. Analyzing only the text or image content of the tweet often misses necessary insights which might be helpful during disasters. In this paper, we propose a multimodal framework to address the challenges of identifying informative crisis-related tweets containing both texts and images. Our presented approach incorporates an early fusion strategy of BERT-LSTM and ResNet50 networks which effectively learns from the joint representation of texts and images. The experiments and evaluation on the benchmark CrisisMMD dataset show that our fusion method surpasses the baseline by 7% and substantiates its potency over the unimodal systems. | ||||
Address | University of Chittagong; University of Chittagong; University of Chittagong | ||||
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/OMIR7766 | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2537 | ||
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Author | Teun Terpstra; Richard Stronkman; Arnout De Vries; Geerte L. Paradies | ||||
Title | Towards a realtime Twitter analysis during crises for operational crisis management | 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 | Disaster prevention; Information filtering; Information retrieval; Information systems; Monitoring; Storms; Crisis communications; Crisis management; Graphical displays; Information extraction tools; Natural hazard; Self organizations; Social media; Twitter; Social networking (online) | ||||
Abstract | Today's crises attract great attention on social media, from local and distant citizens as well as from news media. This study investigates the possibilities of real-time and automated analysis of Twitter messages during crises. The analysis was performed through application of an information extraction tool to nearly 97,000 tweets that were published shortly before, during and after a storm hit the Pukkelpop 2011 festival in Belgium. As soon as the storm hit the festival tweet activity increased exponentially, peaking at 576 tweets per minute. The extraction tool enabled analyzing tweets through predefined (geo)graphical displays, message content filters (damage, casualties) and tweet type filters (e.g., retweets). Important topics that emerged were 'early warning tweets', 'rumors' and the 'self-organization of disaster relief' on Twitter. Results indicate that automated filtering of information provides valuable information for operational response and crisis communication. Steps for further research are discussed. © 2012 ISCRAM. | ||||
Address | HKV Consultants, Netherlands; Twitcident, Netherlands; TNO, Netherlands | ||||
Corporate Author | Thesis | ||||
Publisher | Simon Fraser University | Place of Publication | Vancouver, BC | Editor | L. Rothkrantz, J. Ristvej, Z.Franco |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 2411-3387 | ISBN | 9780864913326 | Medium | |
Track | Social Media and Collaborative Systems | Expedition | Conference | 9th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
Notes | Approved | no | |||
Call Number | Serial | 215 | |||
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Author | Therese Habig; Richard Lüke; Simon Gehlhar; Torben Sauerland; Daniel Tappe | ||||
Title | A Consolidated Understanding of Disaster Community Technologies | 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 | 778-791 | ||
Keywords | Disaster Community Technologies, social media and crowdsourcing, categorization and classification schema, knowledge base | ||||
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. | ||||
Address | safety innovation center; safety innovation center; safety innovation center; safety innovation center; safety innovation center | ||||
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 | habig@safetyinnovation.center | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2373 | ||
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