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Author Pooneh Mousavi; Cody Buntain pdf  isbn
openurl 
  Title (up) “Please Donate for the Affected”: Supporting Emergency Managers in Finding Volunteers and Donations in Twitter Across Disasters Type Conference Article
  Year 2022 Publication ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2022  
  Volume Issue Pages 605-622  
  Keywords social media; crisis in formatics; volunteers; donations; emergency support functions  
  Abstract Despite the outpouring of social support posted to social media channels in the aftermath of disaster, finding and managing content that can translate into community relief, donations, volunteering, or other recovery support is difficult due to the lack of sufficient annotated data around volunteerism. This paper outlines three experiments to alleviate these difficulties. First, we estimate to what degree volunteerism content from one crisis is transferable to another by evaluating the consistency of language in volunteer-and donation-related social media content across 78 disasters. Second it introduces methods for providing computational support in this emergency support function and developing semi-automated models for classifying volunteer-and donation-related social media content in new disaster events. Results show volunteer-and donation-related social media content is sufficiently similar across disasters and disaster types to warrant transferring models across disasters, and we evaluate simple resampling techniques for tuning these models. We then introduce and evaluate a weak-supervision approach to integrate domain knowledge from emergency response officers with machine learningmodelstoimproveclassification accuracy andacceleratethisemergencysupportinnewevents. This method helps to overcome the scarcity in data that we observe related to volunteer-and donation-related social media content.  
  Address University of Maryland, College Park; University of Maryland, College Park  
  Corporate Author Thesis  
  Publisher Place of Publication Tarbes, France Editor Rob Grace; Hossein Baharmand  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 978-82-8427-099-9 Medium  
  Track Social Media for Crisis Management Expedition Conference  
  Notes Approved no  
  Call Number ISCRAM @ idladmin @ Serial 2442  
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Author Humaira Waqas; Muhammad Imran pdf  isbn
openurl 
  Title (up) #CampFireMissing: An Analysis of Tweets About Missing and Found People From California Wildfires 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, Twitter, missing and found people, California wildfires, disaster response  
  Abstract Several research studies have shown the importance of social media data for humanitarian aid. Among others,

the issue of missing and lost people during disasters and emergencies is crucial for disaster managers. This work

analyzes Twitter data from a recent wildfire event to determine its usefulness for the mitigation of the missing and

found people issue. Data analysis performed using various filtering techniques, and trend analysis revealed that

Twitter contains important information potentially useful for emergency managers and volunteers to tackle this

issue. Many tweets were found containing full names, partial names, location information, and other vital clues

which could be useful for finding missing people.
 
  Address Qatar Computing Research Institute, Qatar  
  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 1915  
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Author Antonin Segault; Federico Tajariol; Yang Ishigaki; Ioan Roxin pdf  isbn
openurl 
  Title (up) #geiger 2: Developing Guidelines for Radiation Measurements Sharing on Social Media 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 Twitter; Nuclear Post-Accident; Radiation; Robots; Syntax  
  Abstract Radiation measurements are key information in post-nuclear accident situations. Automated Twitter accounts have been used to share the readings, but often in an incomplete way from the perspective of data sharing and risk communication between citizen and radiation experts. In this paper, we investigate the requirements for radiation measurements completeness, by analyzing the perceived usefulness of several metadata items that may go along the measurement itself. We carried out a benchmark of existing uses, and conducted a survey with both experts and lay citizens. We thus produced a set of guidelines regarding the metadata that should be used, and the way to publish it.  
  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 1394  
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Author Antonin Segault; Federico Tajariol; Ioan Roxin pdf  isbn
openurl 
  Title (up) #geiger : Radiation Monitoring Twitter Bots for Nuclear Post-Accident Situations 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 bots; long-term period; nuclear post-accident; radiations; Twitter  
  Abstract In the last decade, people have increasingly relied on social media platforms such as Twitter to share information on the response to a natural or a man-made disaster. This paper focuses on the aftermath of the Fukushima Daiichi nuclear disaster. Since the disaster, victims and volunteers have been sharing relevant information about radiation measurements by means of social media. The aim of this research is to explore the diffusion of information produced and shared by Twitter bots, to understand the degree of popularity of these sources and to check if these bots deliver original radiation measurements.  
  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 1239  
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Author Lise Ann St. Denis; Amanda Lee Hughes; Jeremy Diaz; Kylen Solvik; Maxwell B. Joseph; Jennifer K. Balch pdf  isbn
openurl 
  Title (up) 'What I Need to Know is What I Don't Know!': Filtering Disaster Twitter Data for Information from Local Individuals 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 730-743  
  Keywords Crisis Informatics, Social Media, Emergency Management, Situational Awareness.  
  Abstract We report on the design, development, and evaluation of a user labeling framework for social media monitoring by emergency responders. By labeling Twitter user accounts based on behavior and content, this novel approach identifies tweets from accounts belonging to Individuals generating Personalized content and captures information that might otherwise be missed. We evaluate the framework using training data from the 2018 Camp, Woolsey, and Hill fires. Approximately 30% of the Individual-Personalized tweets contain first-hand information, providing a rich stream of content for social media monitoring. Because it can quickly eliminate most redundant tweets, this framework could be a critical first step in an end-to-end information extraction pipeline. It may also generalize more easily for new disaster events since it relies on general user account attributes rather than tweet content. We conclude with next steps for refining and evaluating our framework in near real-time during a disaster response.  
  Address CIRES, Earth Lab, University of Colorado, Boulder; Crisis Informatics Lab Brigham Young University; Institute for Computational and Data Sciences, Department of Geography, Penn State University; CIRES, Earth Lab, Department of Geography, University of Colorado, Boulder; CIRES, Earth Lab, University of Colorado, Boulder; CIRES, Earth Lab, Department of Geography, University of Colorado, Boulder  
  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 978-1-949373-27-66 ISBN 2411-3452 Medium  
  Track Social Media for Disaster Response and Resilie Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes Lise.St.Denis@Colorado.edu Approved no  
  Call Number Serial 2267  
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Author Francesca Comunello; Simone Mulargia pdf  openurl
  Title (up) A #cultural_change is needed. Social media use in emergency communication by Italian local level institutions 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 512-521  
  Keywords Social media; local level; emergency communication; barriers  
  Abstract We discuss the results of a research project aimed at exploring the use of social media in emergency communication by officers operating at a local level. We performed 16 semi-structured interviews with national level expert informants, and with officers operating at the municipality and province (prefectures) level in an Italian region (respondents were selected based on their involvement in emergency communication and/or emergency management processes). Social media usage appears distributed over a continuum of engagement, ranging from very basic usage to using social media by adopting a broadcasting approach, to deeper engagement, which also includes continuous interaction with citizens. Two main attitudes emerge both in the narrative style and in social media representations: some respondents seem to adopt an institutional attitude, while others adopt a practical-professional attitude. Among the main barriers to a broader adoption of social media, cultural considerations seem to prevail, along with the lack of personnel, a general concern toward social media communication reliability, and the perceived distance between the formal role of institutions and the informal nature of social media communication.  
  Address LUMSA University, Rome, Italy; Sapienza University of Rome, Italy  
  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 2039  
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Author Dario Salza; Edoardo Arnaudo; Giacomo Blanco; Claudio Rossi pdf  isbn
openurl 
  Title (up) A 'Glocal' Approach for Real-time Emergency Event Detection in Twitter Type Conference Article
  Year 2022 Publication ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2022  
  Volume Issue Pages 570-583  
  Keywords Emergency; Event Detection; Social Media; Twitter; Incremental Clustering  
  Abstract Social media like Twitter offer not only an unprecedented amount of user-generated content covering developing emergencies but also act as a collector of news produced by heterogeneous sources, including big and small media companies as well as public authorities. However, this volume, velocity, and variety of data constitute the main value and, at the same time, the key challenge to implement and automatic detection and tracking of independent emergency events from the real-time stream of tweets. Leveraging online clustering and considering both textual and geographical features, we propose, implement, and evaluate an algorithm to automatically detect emergency events applying a ‘glocal’ approach, i.e., offering a global coverage while detecting events at local (municipality level) scale.  
  Address LINKS Foundation; LINKS Foundation; LINKS Foundation; LINKS Foundation  
  Corporate Author Thesis  
  Publisher Place of Publication Tarbes, France Editor Rob Grace; Hossein Baharmand  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 978-82-8427-099-9 Medium  
  Track Social Media for Crisis Management Expedition Conference  
  Notes Approved no  
  Call Number ISCRAM @ idladmin @ Serial 2440  
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Author Robert Power; Bella Robinson; John Colton; Mark Cameron pdf  isbn
openurl 
  Title (up) A Case Study for Monitoring Fires with Twitter 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; Situational Awareness; social media; Twitter  
  Abstract This paper presents a user configurable monitoring system to track in near-real-time tweets describing fire events. The system targets fire related words in a user defined region of interest published on Twitter which are further processed by a text classifier to determine if they describe a known fire event of interest. The system was motivated from a case study that examined a corpus of tweets posted during active bushfires. This demonstrated that useful information is available on Twitter about fire events from people who are in the vicinity.

We present an overview of the system describing how it is initially configured by a user to focus on specific fire events in Australia, the development of a text classifier to identify tweets of interest, especially those with accompanying photos, and the monitoring system that can track multiple events at once.
 
  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 1237  
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Author Imen Bizid; Patrice Boursier; Jacques Morcos; Sami Faiz pdf  isbn
openurl 
  Title (up) A Classification Model for the Identification of Prominent Microblogs Users during a Disaster 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; Information retrieval; Microblogs  
  Abstract Content shared in microblogs during disasters is expressed in various formats and languages. This diversity makes the information retrieval process more complex and computationally infeasible in real time. To address this, we propose a classification model for the identification of prominent users who are sharing relevant and exclusive information during the disaster. Users who have shared at least one tweet about the disaster are modeled using three kinds of time-sensitive features, including topical, social and geographical features. Then, these users are classified into two classes using a linear Support Vector Machine (SVM) to evaluate them over the extracted features and identify the most prominent ones. The first results using the actual dataset, show that our model has a high accuracy by detecting most of the prominent users. Moreover, we demonstrate that all the proposed features used by our model are indispensable to achieve this high accuracy.  
  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 1241  
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Author Therese Habig; Richard Lüke; Simon Gehlhar; Torben Sauerland; Daniel Tappe pdf  openurl
  Title (up) 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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Author Axel Schulz; Tung Dang Thanh; Heiko Paulheim; Immanuel Schweizer pdf  isbn
openurl 
  Title (up) A fine-grained sentiment analysis approach for detecting crisis related microposts 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 846-851  
  Keywords Artificial intelligence; Information systems; Learning systems; Risk management; Social networking (online); Amount of information; Emergency management; Microposts; Real-time information; Sentiment analysis; Situational awareness; Systematic evaluation; Twitter; Data mining  
  Abstract Real-time information from microposts like Twitter is useful for applications in the crisis management domain. Currently, that potentially valuable information remains mostly unused by the command staff, mainly because the sheer amount of information cannot be handled efficiently. Sentiment analysis has been shown as an effective tool to detect microposts (such as tweets) that contribute to situational awareness. However, current approaches only focus on two or three emotion classes. But using only tweets with negative emotions for crisis management is not always sufficient. The amount of remaining information is still not manageable or most of the tweets are irrelevant. Thus, a more fine-grained differentiation is needed to identify relevant microposts. In this paper, we show the systematic evaluation of an approach for sentiment analysis on microposts that allows detecting seven emotion classes. A preliminary evaluation of our approach in a crisis related scenario demonstrates the applicability and usefulness.  
  Address Technische Universität Darmstadt, Germany; Universität Mannheim, 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 927  
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Author Kartikeya Bajpai; Anuj Jaiswal pdf  isbn
openurl 
  Title (up) A framework for analyzing collective action events on Twitter Type Conference Article
  Year 2011 Publication 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011 Abbreviated Journal ISCRAM 2011  
  Volume Issue Pages  
  Keywords Information systems; Collective action; Content and structure; Government censorships; Micro-blogging platforms; Research goals; Social movements; Thailand; Twitter; Social networking (online)  
  Abstract Recent years have witnessed multiple international protest movements which have purportedly been greatly affected by the use of Twitter, a micro-blogging platform. Social movement actors in Iran, Moldova, Kyrgyzstan and Thailand are thought to have utilized Twitter to spread information, co-ordinate protest activities, evade government censorship and, in some cases, to spread misinformation. We propose a framework for conceptualizing and analyzing Twitter data related to contentious collective action crises. Our primary research goal is to delineate a framework informed with a social movements lens and to demonstrate the framework by means of Twitter usage data related to the Thailand protests of 2010. Our proposed framework concerns itself with two aspects of protest activities and Twitter usage, namely, analyzing the content and structure of messages and our construct of Twitter protest waves.  
  Address Pennsylvania State University, United States  
  Corporate Author Thesis  
  Publisher Information Systems for Crisis Response and Management, ISCRAM Place of Publication Lisbon Editor M.A. Santos, L. Sousa, E. Portela  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 9789724922478 Medium  
  Track Social Media and Collaborative Systems Expedition Conference 8th International ISCRAM Conference on Information Systems for Crisis Response and Management  
  Notes Approved no  
  Call Number Serial 283  
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Author Lívia Castro Degrossi; João Porto de Albuquerque; Roberto dos Santos Rocha; Alexander Zipf pdf  openurl
  Title (up) A Framework of Quality Assessment Methods for Crowdsourced Geographic Information: a Systematic Literature Review 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 532-545  
  Keywords Volunteered Geographic Information; VGI; Crowdsourced Geographic Information; Quality Assessment; Systematic Literature Review  
  Abstract Crowdsourced Geographic Information (CGI) has emerged as a potential source of geographic information in different application domains. Despite the advantages associated with it, this information lacks quality assurance, since it is provided by different people. Therefore, several authors have started investigating different methods to assess the quality of CGI. Some of the existing methods have been summarized in different classification scheme. However, there is not an overview of the methods employed to assess the quality of CGI in the absence of authoritative data. On the basis of a systematic literature review, we found 13 methods that can be employed to this end.  
  Address Department of Computer Systems University of São Paulo, São Carlos, Brazil; Centre for Interdisciplinary Methodologies University of Warwick, Coventry, UK; GIScience Research Group, Heidelberg University, Germany  
  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 2041  
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Author Daniel Link; Bernd Hellingrath; Jie Ling pdf  isbn
openurl 
  Title (up) A Human-is-the-Loop Approach for Semi-Automated Content Moderation Type Conference Article
  Year 2016 Publication ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2016  
  Volume Issue Pages  
  Keywords Disaster Management; Social Media Analysis; Human-Is-The-Loop; Content Moderation; Supervised Machine Learning  
  Abstract Online social media has been recognized as a valuable information source for disaster management whose volume, velocity and variety exceed manual processing capacity. Current machine learning systems that support the processing of such data generally follow a human-in-the-loop approach, which has several inherent limitations. This work applies the human-is-the-loop concept from visual analytics to semi-automate a manual content moderation workflow, wherein human moderators take the dominant role. The workflow is instantiated with a supervised machine learning system that supports moderators with suggestions regarding the relevance and categorization of content. The instantiated workflow has been evaluated using in-depth interviews with practitioners and serious games. which suggest that it offers good compatibility with work practices in humanitarian assessment as well as improved moderation quality and higher flexibility than common approaches.  
  Address  
  Corporate Author Thesis  
  Publisher Federal University of Rio de Janeiro Place of Publication Rio de Janeiro, Brasil Editor A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3388 ISBN 978-84-608-7984-9 Medium  
  Track Social Media Studies Expedition Conference 13th International Conference on Information Systems for Crisis Response and Management  
  Notes Approved no  
  Call Number Serial 1401  
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Author Sofia Eleni Spatharioti; Rebecca Govoni; Jennifer S. Carrera; Sara Wylie; Seth Cooper pdf  openurl
  Title (up) 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 André Dittrich; Christian Lucas pdf  isbn
openurl 
  Title (up) 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 Daniel E. Lane; Tracey L. O'Sullivan; Craig E. Kuziemsky; Fikret Berkes; Anthony Charles pdf  isbn
openurl 
  Title (up) A structured equation model of collaborative community response 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 906-911  
  Keywords Computer simulation; Decision theory; Information systems; Mathematical models; Risk analysis; Adaptation; C-change; Community collaboration; Community engagement; Emergency response; EnRiCH; Preparedness; Simulation; Structured equation modeling; Emergency services  
  Abstract This paper analyses the collaborative dynamic of community in response to urgent situations. Community emergencies arising from natural or man-induced threats are considered as exogenous events that stimulate community resources to be unified around the response, action, and recovery activities related to the emergency. A structured equation model is derived to depict the actions of the community system. The system is described in terms of its resources including the propensity to trigger community action and collaboration among diverse groups. The community is profiled with respect to its ability to respond. The system defines the trigger mechanisms that are considered to be the drivers of collaborative action. A simulation model is presented to enact the system emergencies, community profiles, and collaborative response. The results develop an improved understanding of conditions that engage community collaborative actions as illustrated by examples from community research in the EnRiCH and the C-Change community research projects.  
  Address Telfer School of Management, University of Ottawa, Canada; Interdisciplinary Faculty of Health Sciences, University of Ottawa, Canada; Natural Resources Institute, University of Manitoba, Canada; Department of Finance and Management Science, Saint Mary's University, Canada  
  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 677  
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Author Lamsal, R.; Read, M.R.; Karunasekera, S. pdf  doi
openurl 
  Title (up) A Twitter narrative of the COVID-19 pandemic in Australia Type Conference Article
  Year 2023 Publication Proceedings of the 20th International ISCRAM Conference Abbreviated Journal Iscram 2023  
  Volume Issue Pages 353-370  
  Keywords Crisis Informatics; Situational Awareness; Topic Modeling; Granger Causality; Network Analysis  
  Abstract Social media platforms contain abundant data that can provide comprehensive knowledge of historical and real-time events. During crisis events, the use of social media peaks, as people discuss what they have seen, heard, or felt. Previous studies confirm the usefulness of such socially generated discussions for the public, first responders, and decision-makers to gain a better understanding of events as they unfold at the ground level. This study performs an extensive analysis of COVID-19-related Twitter discussions generated in Australia between January 2020, and October 2022. We explore the Australian Twitterverse by employing state-of-the-art approaches from both supervised and unsupervised domains to perform network analysis, topic modeling, sentiment analysis, and causality analysis. As the presented results provide a comprehensive understanding of the Australian Twitterverse during the COVID-19 pandemic, this study aims to explore the discussion dynamics to aid the development of future automated information systems for epidemic/pandemic management.  
  Address The University of Melbourne  
  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/GQED8281 Approved no  
  Call Number ISCRAM @ idladmin @ Serial 2531  
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Author Firoj Alam; Ferda Ofli; Muhammad Imran; Michael Aupetit pdf  isbn
openurl 
  Title (up) A Twitter Tale of Three Hurricanes: Harvey, Irma, and Maria 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 553-572  
  Keywords social media, artificial intelligence, image processing, supervised classification, disaster management  
  Abstract People increasingly use microblogging platforms such as Twitter during natural disasters and emergencies. Research studies have revealed the usefulness of the data available on Twitter for several disaster response tasks. However, making sense of social media data is a challenging task due to several reasons such as limitations of available tools to analyze high-volume and high-velocity data streams. This work presents an extensive multidimensional analysis of textual and multimedia content from millions of tweets shared on Twitter during the three disaster events. Specifically, we employ various Artificial Intelligence techniques from Natural Language Processing and Computer Vision fields, which exploit different machine learning algorithms to process the data generated during the disaster events. Our study reveals the distributions of various types of useful information that can inform crisis managers and responders as well as facilitate the development of future automated systems for disaster management.  
  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 2131  
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Author Nasik Muhammad Nafi; Avishek Bose; Sarthak Khanal; Doina Caragea; William H. Hsu pdf  isbn
openurl 
  Title (up) Abstractive Text Summarization of Disaster-Related Documents Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 881-892  
  Keywords Disaster Reporting; Text Summarization; Information Extraction; Reinforcement Learning; Evaluation Metrics  
  Abstract Abstractive summarization is intended to capture key information from the full text of documents. In the application domain of disaster and crisis event reporting, key information includes disaster effects, cause, and severity. While some researches regarding information extraction in the disaster domain have focused on keyphrase extraction from short disaster-related texts like tweets, there is hardly any work that attempts abstractive summarization of long disaster-related documents. Following the recent success of Reinforcement Learning (RL) in other domains, we leverage an RL-based state-of-the-art approach in abstractive summarization to summarize disaster-related documents. RL enables an agent to find an optimal policy by maximizing some reward. We design a novel hybrid reward metric for the disaster domain by combining \underline{Vec}tor Similarity and \underline{Lex}icon Matching (\textit{VecLex}) to maximize the relevance of the abstract to the source document while focusing on disaster-related keywords. We evaluate the model on a disaster-related subset of a CNN/Daily Mail dataset consisting of 104,913 documents. The results show that our approach produces more informative summaries and achieves higher \textit{VecLex} scores compared to the baseline.  
  Address Kansas State University; Kansas State University; Kansas State University; Kansas State University; Kansas State University  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-78 ISBN 2411-3464 Medium  
  Track Social Media for Disaster Response and Resilie Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes nnafi@ksu.edu Approved no  
  Call Number Serial 2279  
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Author Keri K. Stephens; Jessica L. Ford; Ashley Barrett; Michael J. Mahometa pdf  isbn
openurl 
  Title (up) Alert networks of ICTs and sources in campus emergencies 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 652-661  
  Keywords Information systems; Mobile devices; Risk management; Emergency alerts; Emergency management; ICTs; Safety communications; Social media; Social networking (online)  
  Abstract This study contributes an understanding of how ICTs and varying information sources work together during emergency alerts. It builds on the prior work on campus active shooter events by examining an organization that used a range of ICTs including mobile devices, social media, organizational tools, and news media, to notify their stakeholders about an emergency. The study design used a survey to capture the responses from a random sample of over 1000 stakeholders-students, faculty, and staff-who were notified of an active shooter emergency. The findings from the first three notifications suggest that messages reaching the most stakeholders were (a) sent by official sources through ICTs like mobile phones; (b) official email communication, and (c) messages that included face-to-face communication. While 11 different ICTs were included in the study, mass media (i.e., television and radio), and social media (Twitter and Facebook) did not function substantially in the emergency alert process.  
  Address University of Texas at Austin, 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 974  
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Author Online Media as a Means to Affect Public Trust in Emergency Responders pdf  isbn
openurl 
  Title (up) Amanda Lee Hughes; Apoorva Chauhan Type Conference Article
  Year 2015 Publication ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2015  
  Volume Issue Pages  
  Keywords computer-mediated communication; crisis informatics; emergency response; social media; trust  
  Abstract This exploratory study examines how fire and police departments used online media during the 2012 Hurricane Sandy and how these media can be used to affect trust with members of the public during such an event. Using trust theory, we describe how online communications provide a means for emergency responders to appear trustworthy through online acts of ability, integrity, and benevolence. We conclude with implications and recommendations for emergency response practice and a trajectory of future work.  
  Address  
  Corporate Author Thesis  
  Publisher University of Agder (UiA) Place of Publication Kristiansand, Norway Editor L. Palen; M. Buscher; T. Comes; A. Hughes  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 9788271177881 Medium  
  Track Social Media Studies Expedition Conference ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management  
  Notes Approved yes  
  Call Number Serial 1226  
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Author Kenneth Joseph; Peter M. Landwehr; Kathleen M. Carley pdf  isbn
openurl 
  Title (up) An approach to selecting keywords to track on twitter during a disaster Type Conference Article
  Year 2014 Publication ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2014  
  Volume Issue Pages 672-676  
  Keywords Data mining; Disasters; Information systems; Keyword searching; Novel methodology; Situational awareness; Social media; Twitter; Social networking (online)  
  Abstract Several studies on Twitter usage during disasters analyze tweets collected using ad-hoc keywords pre-defined by researchers. While recent efforts have worked to improve this methodology, open questions remain about which keywords can be used to uncover tweets contributing to situational awareness (SA) and the quality of tweets returned using different terms. Herein we consider a novel methodology for uncovering relevant keywords one can use to search for tweets containing situational awareness. We provide a description of the methodology and initial results which suggest our approach may lead to better keywords to use for keyword searching during disasters.  
  Address Carnegie Mellon 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 640  
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Author Tasneem, F.; Chakraborty, S.; Chy, A.N. pdf  doi
openurl 
  Title (up) 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 Shivam Sharma; Cody Buntain pdf  openurl
  Title (up) 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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