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| Author | Sherri L. Condon; Jason R. Robinson | ||||
| Title | Communication media use in emergency response management | Type | Conference Article | ||
| Year | 2014 | Publication | ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2014 |
| Volume | Issue | Pages | 687-696 | ||
| Keywords | Information systems; Managers; Catastrophic event; Communication media; Emergency response; Emergency response management; Information and Communication Technologies; Instant messaging; Social media; University campus; Emergency services | ||||
Abstract  |
The communications of emergency response managers were tracked during simulated catastrophic events at a university campus in the Washington, D.C. region. Local, state, and federal response managers interacted with each other and with students using a variety of communication media in order to investigate the utility of new communication channels for emergency response management. Students and emergency managers interacted using a Twitter-like platform and a portal built with Ushahidi crowd-sourcing software. The emergency managers also used a chat interface that included private instant messaging, telephone, and the county's existing emergency web portal. Their media use was analyzed along with the functions of their communications, and the patterns that emerged are described and quantified. | ||||
| Address | MITRE Corporation, United States | ||||
| Corporate Author | 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 | 412 | |||
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| Author | Patrick C. Shih; Kyungsik Han; John M. Carroll | ||||
| Title | Community incident chatter: Informing local incidents by aggregating local news and social media content | Type | Conference Article | ||
| Year | 2014 | Publication | ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2014 |
| Volume | Issue | Pages | 772-776 | ||
| Keywords | Hardware; Civic awareness and participation; Large-scale event; Local incidents and emergencies; News agencies; Smart-phone applications; Social media; Two way communications; User study; Information systems | ||||
| Abstract |
The emergence of social media provides an additional channel for broadcasting information to the public and support two-way communication between governmental stakeholders and the public during crisis. Research has focused on large-scale events, and few have investigated how social media can contribute to civic awareness and participation of small-scale incidents in a community-oriented context. Moreover, social media have been criticized because it is overabundant with noisy, inaccurate, and unprofessional information that are often misleading. This presents a serious challenge for community members to identify information that are relevant to a local incident. We introduce Community Incident Chatter (CIC), a smartphone application that is designed to aggregate information reported by formal news agencies and social media surrounding local incidents. Participants in a preliminary user study indicate that the community-oriented information presented in CIC is informative, relevant to the community, and has the potential of empowering community residents for responding to and managing local incidents. | ||||
| Address | Pennsylvania State University, United States | ||||
| Corporate Author | Thesis | ||||
| Publisher | The Pennsylvania State University | Place of Publication | University Park, PA | Editor | S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9780692211946 | Medium | |
| Track | Social Media in Crisis Response and Management | Expedition | Conference | 11th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 949 | |||
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| Author | Robert Power; Bella Robinson; Mark Cameron | ||||
| Title | Insights from a Decade of Twitter Monitoring for Emergency Management | Type | Conference Article | ||
| Year | 2023 | Publication | Proceedings of the ISCRAM Asia Pacific Conference 2022 | Abbreviated Journal | Proc. ISCRAM AP 2022 |
| Volume | Issue | Pages | 247-257 | ||
| Keywords | Crisis Coordination; Disaster Management; Situation Awareness; Social Media; System Architecture; Twitter | ||||
| Abstract |
The Emergency Situation Awareness (ESA) tool began as a research study into automated web text mining to support emergency management use cases. It started in late 2009 by investigating how people respond on Twitter to specific emergency events and we quickly realized that every emergency situation is different and preemptively defining keywords to search for content on Twitter beforehand would likely miss important information. So, in late September 2011 we established location-based searches with the aim of collecting all the tweets published in Australia and New Zealand. This was the beginning of over a decade of collecting and processing tweets to help emergency response agencies and crisis coordination centres use social media content as a new channel of information to support their work practices and to engage with the community impacted by emergency events. This journey has seen numerous challenges overcome to continuously maintain a tweet stream for an operational system. This experience allows us to derive insights into the changing use of Twitter over this time. In this paper we present some of the lessons we’ve learned from maintaining a Twitter monitoring system for emergency management use cases and we provide some insights into the changing nature of Twitter usage by users over this period. | ||||
| Address | CSIRO Data61; CSIRO Data61; CSIRO Data61 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Massey Unversity | Place of Publication | Palmerston North, New Zealand | Editor | Thomas J. Huggins, V.L. |
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-0-473-66845-7 | Medium | |
| Track | Social Media for Disaster Response | Expedition | Conference | ||
| Notes | Approved | no | |||
| Call Number | ISCRAM @ idladmin @ | Serial | 2498 | ||
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| Author | Dat T. Nguyen; Firoj Alam; Ferda Ofli; Muhammad Imran | ||||
| Title | Automatic Image Filtering on Social Networks Using Deep Learning and Perceptual Hashing During Crises | Type | Conference Article | ||
| Year | 2017 | Publication | Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2017 |
| Volume | Issue | Pages | 499-511 | ||
| Keywords | social media; image processing; supervised classification; disaster management | ||||
| Abstract |
The extensive use of social media platforms, especially during disasters, creates unique opportunities for humanitarian organizations to gain situational awareness and launch relief operations accordingly. In addition to the textual content, people post overwhelming amounts of imagery data on social networks within minutes of a disaster hit. Studies point to the importance of this online imagery content for emergency response. Despite recent advances in the computer vision field, automatic processing of the crisis-related social media imagery data remains a challenging task. It is because a majority of which consists of redundant and irrelevant content. In this paper, we present an image processing pipeline that comprises de-duplication and relevancy filtering mechanisms to collect and filter social media image content in real-time during a crisis event. Results obtained from extensive experiments on real-world crisis datasets demonstrate the significance of the proposed pipeline for optimal utilization of both human and machine computing resources. | ||||
| Address | Qatar Computing Research Institute Hamad Bin Khalifa University Doha, Qatar | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Albi, France | Editor | Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | Medium | ||
| Track | Social Media Studies | Expedition | Conference | 14th International Conference on Information Systems for Crisis Response And Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 2038 | |||
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| Author | Seungwon Yang; Haeyong Chung; Xiao Lin; Sunshin Lee; Liangzhe Chen; Andrew Wood; Andrea Kavanaugh; Steven D. Sheetz; Donald J. Shoemaker; Edward A. Fox | ||||
| Title | PhaseVis1: What, when, where, and who in visualizing the four phases of emergency management through the lens of social media | Type | Conference Article | ||
| Year | 2013 | Publication | ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2013 |
| Volume | Issue | Pages | 912-917 | ||
| Keywords | Civil defense; Classification (of information); Data visualization; Information systems; Risk management; 10-fold cross-validation; Classification algorithm; Classification evaluation; Emergency management; Potential utility; ThemeRiver; Through the lens; Twitter; Disasters | ||||
| Abstract |
The Four Phase Model of Emergency Management has been widely used in developing emergency/disaster response plans. However, the model has received criticism contrasting the clear phase distinctions in the model with the complex and overlapping nature of phases indicated by empirical evidence. To investigate how phases actually occur, we designed PhaseVis based on visualization principles, and applied it to Hurricane Isaac tweet data. We trained three classification algorithms using the four phases as categories. The 10-fold cross-validation showed that Multi-class SVM performed the best in Precision (0.8) and Naïve Bayes Multinomial performed the best in F-1 score (0.782). The tweet volume in each category was visualized as a ThemeRiver[TM], which shows the 'What' aspect. Other aspects – 'When', 'Where', and 'Who' – Are also integrated. The classification evaluation and a sample use case indicate that PhaseVis has potential utility in disasters, aiding those investigating a large disaster tweet dataset. | ||||
| Address | Department of Computer Science, Virginia Tech, Blacksburg, VA 24061, United States; Department of Accounting and Information Systems, Virginia Tech, Blacksburg, VA 24061, United States; Department of Sociology, Virginia Tech, Blacksburg, VA 24061, 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 | 1122 | |||
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| Author | Thomas Papadimos; Nick Pantelidis; Stelios Andreadis; Aristeidis Bozas; Ilias Gialampoukidis; Stefanos Vrochidis; Ioannis Kompatsiaris | ||||
| Title | Real-time Alert Framework for Fire Incidents Using Multimodal Event Detection on Social Media Streams | 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 | 623-635 | ||
| Keywords | Alert framework; social media; event detection; kernel density estimation; community detection | ||||
| Abstract |
The frequency of wildfires is growing day by day due to vastly climate changes. Forest fires can have a severe impact on human lives and the environment, which can be minimised if the population has early and accurate warning mechanisms. To date, social media are able to contribute to early warning with the additional, crowd-sourced information they can provide to the emergency response workers during a crisis event. Nevertheless, the detection of real-world fire incidents using social media data, while filtering out the unavoidable noise, remains a challenging task. In this paper, we present an alert framework for the real-time detection of fire events and we propose a novel multimodal event detection model, which fuses both probabilistic and graph methodologies and is evaluated on the largest fires in Spain during 2019. | ||||
| Address | Centre for Research & Technology Hellas Information Technologies Institute Thessaloniki, Greece;Centre for Research & Technology Hellas Information Technologies Institute Thessaloniki, Greece;Centre for Research & Technology Hellas Information Technologie | ||||
| 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 | 2443 | ||
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| Author | Hiroko Wilensky | ||||
| Title | Twitter as a navigator for stranded commuters during the great east Japan earthquake | 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 | 697-706 | ||
| Keywords | Disasters; Earthquakes; Information systems; Crisis informatics; Disaster situations; Great east japan earthquakes; Railroad systems; Social media; Tokyo metropolitan areas; Twitter; Social networking (online) | ||||
| Abstract |
The increased use of social media, such as Twitter, was widely reported on Japanese media after the Great East Japan Earthquake of March 11, 2011. This study is a qualitative investigation of the use of Twitter by the stranded commuters and their supporters in the Tokyo metropolitan area immediately after the earthquake. This paper describes the possibilities and problems of Twitter use under a rapidly changing disaster situation. During the first evening of this disaster, the Japan Railroad and other railroad systems ceased their operations in the Tokyo area. This left more than five million commuters stranded in the area. Many commuters walked hours to return home, while others struggled to find temporary shelter and stayed overnight in the city. This study also explores if Twitter was an effective navigator for helping stranded commuters return home or find shelter. | ||||
| Address | University of California, Irvine, 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 | 1091 | |||
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| Author | Ahmed Alnuhayt; Suvodeep Mazumdar; Vitaveska Lanfranchi; Frank Hopfgartner | ||||
| Title | Understanding Reactions to Misinformation – A Covid-19 Perspective | 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 | 687-700 | ||
| Keywords | Misinformation; social reactions; twitter; people; COVID-19 | ||||
| Abstract |
The increasing use of social media as an information source brings further challenges – social media platforms can be an excellent medium for disseminating public awareness and critical information, that can be shared across large populations. However, misinformation in social media can have immense implications on public health, risking the effectiveness of health interventions as well as lives. This has been particularly true in the case of COVID-19 pandemic, with a range of misinformation, conspiracy theories and propaganda being spread across social channels. In our study, through a questionnaire survey, we set out to understand how members of the public interact with different sources when looking for information on COVID-19. We explored how participants react when they encounter information they believe to be misinformation. Through a set of three behaviour tasks, synthetic misinformation posts were provided to the participants who chose how they would react to them. In this work in progress study, we present initial findings and insights into our analysis of the data collected. We highlight what are the most common reactions to misinformation and also how these reactions are different based on the type of misinformation. | ||||
| Address | Information School University of Sheffield; Information School University of Sheffield; Computer Science University of Sheffield; Information School University of Sheffield | ||||
| 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 | 2448 | ||
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| Author | Haiyan Hao; Yan Wang | ||||
| Title | Hurricane Damage Assessment with Multi-, Crowd-Sourced Image Data: A Case Study of Hurricane Irma in the City of Miami | Type | Conference Article | ||
| Year | 2020 | Publication | ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2020 |
| Volume | Issue | Pages | 825-837 | ||
| Keywords | Computer Vision, Damage Assessment, Disaster Management, Insurance Claims, Social Networking Platforms. | ||||
| Abstract |
The massive crowdsourced data generated on social networking platforms (e.g. Twitter and Flickr) provide free, real-time data for damage assessment (DA) even during catastrophes. Recent studies leveraging crowdsourced data for DA mainly focused on analyzing textual formats. Crowdsourced images can provide rich and objective information about damage conditions, however, are rarely researched for DA purposes. The highly-varied content and loosely-defined damage forms make it difficult to process and analyze the crowdsourced images. To address this problem, we propose a data-driven DA method based on multi-, crowd-sourced images, which includes five machine learning classifiers organized in a hierarchical structure. The method is validated with a case study investigating the damage condition of the City of Miami caused by Hurricane Irma. The outcome is then compared with a metric derived from NFIP insurance claims data. The proposed method offers a resource for rapid DA that supplements conventional DA methods. | ||||
| Address | University of Florida; University of Florida | ||||
| Corporate Author | Thesis | ||||
| Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 978-1-949373-27-73 | ISBN | 2411-3459 | Medium | |
| Track | Social Media for Disaster Response and Resilie | Expedition | Conference | 17th International Conference on Information Systems for Crisis Response and Management | |
| Notes | hhao@ufl.edu | Approved | no | ||
| Call Number | Serial | 2274 | |||
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| Author | André Dittrich; Christian Lucas | ||||
| Title | A step towards real-time analysis of major disaster events based on tweets | Type | Conference Article | ||
| Year | 2013 | Publication | ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2013 |
| Volume | Issue | Pages | 868-874 | ||
| Keywords | Information systems; Semantics; Social networking (online); Crisis management; Event detection; Functional model; Micro-blogging platforms; Real time analysis; Semantic content analysis; Social sensors; Twitter; Disasters | ||||
| Abstract |
The most popular micro blogging platform Twitter has been the topic of a variety of research papers related to disaster and crisis management. As an essential first step and basis for a real-time methodology to exploit Twitter for event detection, localization and ultimately semantic content analysis, a functional model to describe the amount of tweets during a day has been developed. It was derived from a corpus of messages in an exemplary area of investigation. To satisfy the different daily behavior on particular days, two types of days are distinguished in this paper. Moreover, keyword-adjusted data is used to point out the potential of semantic tweet analysis in following steps. The consideration of spatial event descriptions in relevant tweets could significantly improve and accelerate the perception of a disaster. The results from the conducted tests demonstrate the capability of the functional model to detect events with significant social impact in Twitter data. | ||||
| Address | Karlsruhe Institute of Technology (KIT), Germany | ||||
| Corporate Author | Thesis | ||||
| Publisher | Karlsruher Institut fur Technologie | Place of Publication | KIT; Baden-Baden | Editor | T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9783923704804 | Medium | |
| Track | Social Media | Expedition | Conference | 10th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 452 | |||
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| Author | Roser Beneito-Montagut; Susan Anson; Duncan Shaw; Christopher Brewster | ||||
| Title | Governmental social media use for emergency communication | 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 | 828-833 | ||
| Keywords | Civil defense; Disasters; Information systems; Risk management; Emergency communication; Emergency management; Governmental agency; Information flows; Institutional resilience; Social media; Web 2.0 tools; Societies and institutions | ||||
| Abstract |
The possibility of crowdsourced information, multi-geographical and multi-organisational information flows during emergencies and crises provided by web 2.0 tools are providing emergency management centres with new communication challenges and opportunities. Building on the existing emergency management and social media literature, this article explores how institutions are using and adopting social media for emergency communication. By examining the drivers and barriers of social media adoption in two European governmental agencies dealing with emergencies, the paper aims to establish a framework to examine whether and how institutional resilience could be improved. | ||||
| Address | Aston Business School, United Kingdom; Warwick Business School, United Kingdom | ||||
| Corporate Author | Thesis | ||||
| Publisher | Karlsruher Institut fur Technologie | Place of Publication | KIT; Baden-Baden | Editor | T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9783923704804 | Medium | |
| Track | Social Media | Expedition | Conference | 10th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 302 | |||
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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 | Yuhong Li; Christopher Zobel | ||||
| Title | Small Businesses and Social Media Usage in the 2013 Colorado Floods | Type | Conference Article | ||
| Year | 2016 | Publication | ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2016 |
| Volume | Issue | Pages | |||
| Keywords | Social Media; Small Business; Recovery; Disaster | ||||
| Abstract |
The recovery of small businesses from a disaster is critical to community recovery. Such businesses can be extremely vulnerable to disasters, particularly because they often occupy a single location and have a localized customer base. Although social media is an effective platform for information dissemination, and has been extensively used in a disaster context, the way in which small businesses use social media in this context, and the effectiveness of those efforts, are still not well understood. With this in mind, this paper uses the 2013 floods along the Front Range in Colorado as a case study to help improve our understanding of how small businesses use social media in disaster situations. Characterizing the organizations' behavior involves using both qualitative and quantitative approaches, and the paper focuses on an initial qualitative analysis. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Federal University of Rio de Janeiro | Place of Publication | Rio de Janeiro, Brasil | Editor | A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3388 | ISBN | 978-84-608-7984-9 | Medium | |
| Track | Social Media Studies | Expedition | Conference | 13th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 1392 | |||
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| Author | Ntalla Athanasia; Ponis T. Stavros | ||||
| Title | Twitter as an instrument for crisis response: The Typhoon Haiyan case study | Type | Conference Article | ||
| Year | 2015 | Publication | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2015 |
| Volume | Issue | Pages | |||
| Keywords | Crisis Management; emergency response; Haiyan; social media; Twitter | ||||
| Abstract |
The research presented in this paper attempts an initial evaluation of Twitter as an instrument for emergency response in the context of a recent crisis event. The case of the 2013 disaster, when typhoon Haiyan hit Philippines is examined by analyzing nine consecutive days of Twitter messages and comparing them to the actual events. The results indicate that during disasters, Twitter users tend to post messages to enhance situation awareness and to motivate people to act. Furthermore, tweets were found reliable and provided valuable information content, supporting the argument that Twitter presents a very good potential to become a useful tool in situations where rapid emergency response is essential. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | University of Agder (UiA) | Place of Publication | Kristiansand, Norway | Editor | L. Palen; M. Buscher; T. Comes; A. Hughes |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9788271177881 | Medium | |
| Track | Social Media Studies | Expedition | Conference | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | yes | |||
| Call Number | Serial | 1238 | |||
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| Author | Zou, H.P.; Caragea, C.; Zhou, Y.; Caragea, D. | ||||
| Title | Semi-Supervised Few-Shot Learning for Fine-Grained Disaster Tweet Classification | Type | Conference Article | ||
| Year | 2023 | Publication | Proceedings of the 20th International ISCRAM Conference | Abbreviated Journal | Iscram 2023 |
| Volume | Issue | Pages | 385-395 | ||
| Keywords | Crisis Tweet Classification; Semi-Supervised Few-Shot Learning; Pseudo-Labeling; TextMixUp. | ||||
| Abstract |
The shared real-time information about natural disasters on social media platforms like Twitter and Facebook plays a critical role in informing volunteers, emergency managers, and response organizations. However, supervised learning models for monitoring disaster events require large amounts of annotated data, making them unrealistic for real-time use in disaster events. To address this challenge, we present a fine-grained disaster tweet classification model under the semi-supervised, few-shot learning setting where only a small number of annotated data is required. Our model, CrisisMatch, effectively classifies tweets into fine-grained classes of interest using few labeled data and large amounts of unlabeled data, mimicking the early stage of a disaster. Through integrating effective semi-supervised learning ideas and incorporating TextMixUp, CrisisMatch achieves performance improvement on two disaster datasets of 11.2% on average. Further analyses are also provided for the influence of the number of labeled data and out-of-domain results. | ||||
| Address | University of Illinois Chicago; Kansas State 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 | 2411-3387 | ISBN | 979-8-218-21749-5 | Medium | |
| Track | Social Media for Crisis Management | Expedition | Conference | ||
| Notes | http://dx.doi.org/10.59297/FWXE4933 | Approved | no | ||
| Call Number | ISCRAM @ idladmin @ | Serial | 2533 | ||
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| Author | Richard McCreadie; Cody Buntain; Ian Soboroff | ||||
| Title | TREC Incident Streams: Finding Actionable Information on Social Media | 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 | Emergency Management, Crisis Informatics, Real-time, Twitter, Categorization | ||||
| Abstract |
The Text Retrieval Conference (TREC) Incident Streams track is a new initiative that aims to mature social media-based emergency response technology. This initiative advances the state of the art in this area through an evaluation challenge, which attracts researchers and developers from across the globe. The 2018 edition of the track provides a standardized evaluation methodology, an ontology of emergency-relevant social media information types, proposes a scale for information criticality, and releases a dataset containing fifteen test events and approximately 20,000 labeled tweets. Analysis of this dataset reveals a significant amount of actionable information on social media during emergencies (> 10%). While this data is valuable for emergency response efforts, analysis of the 39 state-of-the-art systems demonstrate a performance gap in identifying this data. We therefore find the current state-of-the-art is insufficient for emergency responders? requirements, particularly for rare actionable information for which there is little prior training data available. |
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| Address | University of Glasgow, United Kingdom;New York University, USA;National Institute of Standards and Technology, USA | ||||
| 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 | 1867 | |||
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| Author | Richard McCreadie; Cody Buntain; Ian Soboroff | ||||
| Title | Incident Streams 2019: Actionable Insights and How to Find Them | Type | Conference Article | ||
| Year | 2020 | Publication | ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2020 |
| Volume | Issue | Pages | 744-760 | ||
| Keywords | Emergency Management, Crisis Informatics, Real-time, Twitter, Categorization. | ||||
| Abstract |
The ubiquity of mobile internet-enabled devices combined with wide-spread social media use during emergencies is posing new challenges for response personnel. In particular, service operators are now expected to monitor these online channels to extract actionable insights and answer questions from the public. A lack of adequate tools makes this monitoring impractical at the scale of many emergencies. The TREC Incident Streams (TREC-IS) track drives research into solving this technology gap by bringing together academia and industry to develop techniques for extracting actionable insights from social media streams during emergencies. This paper covers the second year of TREC-IS, hosted in 2019 with two editions, 2019-A and 2019-B, contributing 12 new events and approximately 20,000 new tweets across 25 information categories, with 15 research groups participating across the world. This paper provides an overview of these new editions, actionable insights from data labelling, and the automated techniques employed by participant systems that appear most effective. | ||||
| Address | University of Glasgow; InfEco Lab, New Jersey Institute of Technology (NJIT); National Institute of Standards and Technology (NIST) | ||||
| Corporate Author | Thesis | ||||
| Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 978-1-949373-27-67 | ISBN | 2411-3453 | Medium | |
| Track | Social Media for Disaster Response and Resilie | Expedition | Conference | 17th International Conference on Information Systems for Crisis Response and Management | |
| Notes | richard.mccreadie@glasgow.ac.uk | Approved | no | ||
| Call Number | Serial | 2268 | |||
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| Author | Tom Wilson; Stephanie A. Stanek; Emma S. Spiro; Kate Starbird | ||||
| Title | Language Limitations in Rumor Research? Comparing French and English Tweets Sent During the 2015 Paris Attacks | 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 | 546-553 | ||
| Keywords | social media; rumoring, language; crisis informatics; information diffusion | ||||
| Abstract |
The ubiquity of social media facilitates widespread participation in crises. As individuals converge online to understand a developing situation, rumors can emerge. Little is currently known about how online rumoring behavior varies by language. Exploring a rumor from the 2015 Paris Attacks, we investigate Twitter rumoring behaviors across two languages: French, the primary language of the affected population; and English, the dominant language of Internet communication. We utilize mixed methods to qualitatively code and quantitatively analyze rumoring behaviors across French and English language tweets. Most interestingly, temporal engagement in the rumor varies across languages, but proportions of tweets affirming and denying a rumor are very similar. Analyzing tweet deletions and retweet counts, we find slight (but not significant) differences between languages. This work offers insight into potential limitations of previous research of online rumoring, which often focused exclusively on English language content, and demonstrates the importance of considering language in future work. | ||||
| Address | Human Centered Design and Engineering, University of Washington ; Information School, Department of Sociology, University of Washington | ||||
| 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 | 2042 | |||
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| Author | Valerio Lorini; Javier Rando; Diego Saez-Trumper; Carlos Castillo | ||||
| Title | Uneven Coverage of Natural Disasters in Wikipedia: The Case of Floods | Type | Conference Article | ||
| Year | 2020 | Publication | ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2020 |
| Volume | Issue | Pages | 688-703 | ||
| Keywords | Social Media, News Values, Wikipedia, Natural Disasters, Floods. | ||||
| Abstract |
The usage of non-authoritative data for disaster management provides timely information that might not be available through other means. Wikipedia, a collaboratively-produced encyclopedia, includes in-depth information about many natural disasters, and its editors are particularly good at adding information in real-time as a crisis unfolds. In this study, we focus on the most comprehensive version of Wikipedia, the English one. Wikipedia offers good coverage of disasters, particularly those having a large number of fatalities. However, by performing automatic content analysis at a global scale, we also show how the coverage of floods in Wikipedia is skewed towards rich, English-speaking countries, in particular the US and Canada. We also note how coverage of floods in countries with the lowest income is substantially lower than the coverage of floods in middle-income countries. These results have implications for analysts and systems using Wikipedia as an information source about disasters. | ||||
| Address | European Commission, Joint Research Centre (JRC), Ispra, Italy Universitat Pompeu Fabra, Barcelona, Spain; Universitat Pompeu Fabra, Barcelona, Spain; Wikimedia Foundation; Universitat Pompeu Fabra, Barcelona, Spain | ||||
| Corporate Author | Thesis | ||||
| Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 978-1-949373-27-63 | ISBN | 2411-3449 | Medium | |
| Track | Social Media for Disaster Response and Resilie | Expedition | Conference | 17th International Conference on Information Systems for Crisis Response and Management | |
| Notes | valerio.lorini@ec.europa.eu | Approved | no | ||
| Call Number | Serial | 2264 | |||
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| Author | Robin Peters; João Porto de Albuquerque | ||||
| Title | Investigating images as indicators for relevant social media messages in disaster management | Type | Conference Article | ||
| Year | 2015 | Publication | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2015 |
| Volume | Issue | Pages | |||
| Keywords | Disaster Management; Flood; Germany; social media; Volunteered Geographic Information | ||||
| Abstract |
The use of social media during disasters has received increasing attention in studies of the past few years. Existing research is mostly focused upon analyzing text-based messages from social media platforms such as Twitter, while image-based platforms have not been extensively addressed hitherto. However, pictures taken on-the-ground can offer reliable and valuable information for improving situation awareness and could be used as proxy indicators for relevance. To test this hypothesis, this work explores various social media platforms, including image- and text-based ones in the case of floods in Saxony 2013, Germany. Results show that there is a significant association between disaster-related messages containing images and their proximity to the disaster event. Hence, the existence of an image within a social media message can serve as an indicator for high probability of relevant content, and thus can be used for enhancing information extraction from social media towards improving situation awareness. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | University of Agder (UiA) | Place of Publication | Kristiansand, Norway | Editor | L. Palen; M. Buscher; T. Comes; A. Hughes |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9788271177881 | Medium | |
| Track | Social Media Studies | Expedition | Conference | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | yes | |||
| Call Number | Serial | 1240 | |||
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| Author | Christian Reuter; Marc-André Kaufhold; René Steinfort | ||||
| Title | Rumors, Fake News and Social Bots in Conflicts and Emergencies: Towards a Model for Believability in Social Media | Type | Conference Article | ||
| Year | 2017 | Publication | Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2017 |
| Volume | Issue | Pages | 583-591 | ||
| Keywords | Social media; believability; measurement | ||||
| Abstract |
The use of social media is gaining more and more in importance in ordinary life, but also in conflicts and emer-gencies. The social big data, generated by users, is partially also used as a source for situation assessment, e.g. to receive pictures or to assess the general mood. However, the information's believability is hard to control and can deceive. Rumors, fake news and social bots are phenomenons that challenge the easy consumption of social media. To address this, our paper explores the believability of content in social media. Based on foundations of infor-mation quality we conducted a literature study to derive a three-level model for assessing believability. It summa-rizes existing assessment approaches, assessment criteria and related measures. On this basis, we describe several steps towards the development of an assessment approach that works across different types of social media. | ||||
| Address | University of Siegen, Institute for Information Systems | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Albi, France | Editor | Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | Medium | ||
| Track | Social Media Studies | Expedition | Conference | 14th International Conference on Information Systems for Crisis Response And Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 2046 | |||
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| Author | Marc-André Kaufhold; Christian Reuter | ||||
| Title | The Impact of Social Media for Emergency Services: A Case Study with the Fire Department Frankfurt | 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 | 603-612 | ||
| Keywords | Social media; emergency services; facilitators and obstacles; comparative case studies | ||||
| Abstract |
The use of social media is not only part of everyday life but also of crises and emergencies. Many studies focus on the concrete use of social media during a specific emergency, but the prevalence of social media, data access and published research studies allows the examination in a broader and more integrated manner. This work-in-progress paper presents the results of a case study with the Fire Department Frankfurt, which is one of the biggest and most modern fire departments in Germany. The findings relate to social media technologies, organizational structure and roles, information validation, staff skills and resources, and the importance of volunteer communities. In the next step, the results will be integrated into the frame of a comparative case study with the overall aim of examining the impact of social media on how emergency services respond and react in an emergency. | ||||
| Address | University of Siegen, Institute for Information Systems | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Albi, France | Editor | Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | Medium | ||
| Track | Social Media Studies | Expedition | Conference | 14th International Conference on Information Systems for Crisis Response And Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 2048 | |||
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| Author | Sara Barozzi; Jose Luis Fernandez Marquez; Amudha Ravi Shankar; Barbara Pernici | ||||
| Title | Filtering images extracted from social media in the response phase of emergency events | 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 | rapid mapping, floods, information extraction, filtering, crowdsourcing | ||||
| Abstract |
The use of social media to support emergency operators in the first hours of the response phases can improve the quality of the information available and awareness on ongoing emergency events. Social media contain both textual and visual information, in the form of pictures and videos. The problem related to the use of social media posts as a source of information during emergencies lies in the difficulty of selecting the relevant information among a very large amount of irrelevant information. In particular, we focus on the extraction of images relevant to an event for rapid mapping purpose. In this paper, a set of possible filters is proposed and analyzed with the goal of selecting useful images from posts and of evaluating how precision and recall are impacted. Filtering techniques, which include both automated and crowdsourced steps, have the goal of providing better quality posts and easy manageable data volumes both to emergency responders and rapid mapping operators. The impact of the filters on precision and recall in extracting relevant images is discussed in the paper in two different case studies. |
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| Address | Politecnico di Milano;University of Geneva | ||||
| 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 | 1881 | |||
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| Author | Zijun Long; Richard McCreadie | ||||
| Title | Is Multi-Modal Data Key for Crisis Content Categorization on Social Media? | 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 | 1068-1080 | ||
| Keywords | Social Media Classification; Multi-modal Learning; Crisis Management; Deep Learning, BERT; Supervised Learning | ||||
| Abstract |
The user-base of social media platforms, like Twitter, has grown dramatically around the world over the last decade. As people post everything they experience on social media, large volumes of valuable multimedia content are being recorded online, which can be analysed to help for a range of tasks. Here we specifically focus on crisis response. The majority of prior works in this space focus on using machine learning to categorize single-modality content (e.g. text of the posts, or images shared), with few works jointly utilizing multiple modalities. Hence, in this paper, we examine to what extent integrating multiple modalities is important for crisis content categorization. In particular, we design a pipeline for multi-modal learning that fuses textual and visual inputs, leverages both, and then classifies that content based on the specified task. Through evaluation using the CrisisMMD dataset, we demonstrate that effective automatic labelling for this task is possible, with an average of 88.31% F1 performance across two significant tasks (relevance and humanitarian category classification). while also analysing cases that unimodal models and multi-modal models success and fail. | ||||
| Address | University of Glasgow; University of Glasgow | ||||
| 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 | 2472 | ||
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| Author | Briony Gray; Mark Weal; David Martin | ||||
| Title | Building Resilience in Small Island Developing States: Social Media during the 2017 Atlantic Hurricane Season | 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 | 469-479 | ||
| Keywords | Social Media, Hurricanes, Resiliency, Community Engagement, SIDS | ||||
| Abstract |
There are growing concerns that future Atlantic hurricane seasons will be severe and unpredictable due to underlying factors such as climate change. The 2017 season may offer a range of lessons, especially to small island developing states (SIDS), who are looking to build community resilience and heighten community engagement to cope with disaster. While many SIDS utilise a range of media and technology for these purposes, there has been a recent uptake in the use of social media, which may have further potential to support their goals. This paper scopes the use and users of social media in the case of Antigua and Barbuda during the 2017 Atlantic hurricane season. Through a series of qualitative interviews it explains the role that social media currently has, and concludes with suggestions for its improvement in future seasons that are contextualized over the disaster lifecycle phases. | ||||
| Address | University of Southampton; University of Southampton; University of Southampton | ||||
| Corporate Author | Thesis | ||||
| Publisher | Massey Univeristy | Place of Publication | Albany, Auckland, New Zealand | Editor | Kristin Stock; Deborah Bunker |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-0-473-45447-0 | Medium | ||
| Track | Social Media and Community Engagement Supporting Resilience Building | Expedition | Conference | ISCRAM Asia Pacific 2018: Innovating for Resilience - 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific | |
| Notes | bjg1g11@soton.ac.uk | Approved | no | ||
| Call Number | Serial | 1688 | |||
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