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Author (up) Adam Flizikowski, Marcin Przybyszewski; Anna Stachowicz; Tomasz Olejniczak; Rafael Renk
Title Text Analysis Tool TWeet lOcator ? TAT2 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 AIDA; Crisis Management; iSAR+; location of Twitter messages; social media
Abstract Information about location and geographical coordinates in particular, may be very important during a crisis event, especially for search and rescue operations ? but currently geo-tagged tweets are extremely rare. Improved capabilities of capturing additional location from Twitter (up to 4 times improvement) are crucial for response efforts given a vast amount of messages exchanged during a crisis event. That is why authors have designed a tool (Text Analysis TWeet lOcator ? TAT2) that relies on existing open source text analysis tools with additional services to provide additional hints about people location. Validation process, complementing experimentation and test results, included involvement of end-users (i.e. Public Protection and Disaster Relief services and citizens during a realistic crisis exercise showcase. In addition, the integration of TAT2 with external tools has also been validated.
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 1227
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Author (up) Ahmed Nagy; Jeannie Stamberger
Title Crowd sentiment detection during disasters and crises Type Conference Article
Year 2012 Publication ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2012
Volume Issue Pages
Keywords Bayesian networks; Emergency services; Information systems; Risk management; Social networking (online); Crisis management; Disaster response; Emergency management; Short message; Twitter; Disasters
Abstract Microblogs are an opportunity for scavenging critical information such as sentiments. This information can be used to detect rapidly the sentiment of the crowd towards crises or disasters. It can be used as an effective tool to inform humanitarian efforts, and improve the ways in which informative messages are crafted for the crowd regarding an event. Unique characteristics of microblogs (lack of context, use of jargon etc) in Tweets expressed by a message-sharing social network during a disaster response require special handling to identify sentiment. We present a systematic evaluation of approaches to accurately and precisely identify sentiment in these Tweets. This paper describes sentiment detection expressed in 3698 Tweets, collected during the September 2010, San Bruno, California gas explosion and resulting fires. The data collected was manually coded to benchmark our techniques. We start by using a library of words with annotated sentiment, SentiWordNet 3.0, to detect the basic sentiment of each Tweet. We complemented that technique by adding a comprehensive list of emoticons, a sentiment based dictionary and a list of out-of-vocabulary words that are popular in brief, online text communications such as lol, wow, etc. Our technique performed 27% better than Bayesian Networks alone, and the combination of Bayesian networks with annotated lists provided marginal improvements in sentiment detection than various combinations of lists. © 2012 ISCRAM.
Address Carnegie Mellon Silicon Valley, IMT Lucca Institute of Advanced Studies, United States; Disaster Management Initiative, Carnegie Mellon Silicon Valley, United States
Corporate Author Thesis
Publisher Simon Fraser University Place of Publication Vancouver, BC Editor L. Rothkrantz, J. Ristvej, Z.Franco
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9780864913326 Medium
Track Social Media and Collaborative Systems Expedition Conference 9th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 173
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Author (up) Amanda L. Hughes; Leysia Palen
Title Twitter adoption and use in mass convergence and emergency events Type Conference Article
Year 2009 Publication ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives Abbreviated Journal ISCRAM 2009
Volume Issue Pages
Keywords Information systems; Crisis informatics; Emergency; Micro-blogging; Social media; Twitter; Social networking (online)
Abstract This paper offers a descriptive account of Twitter (a micro-blogging service) across four high profile, mass convergence events-two emergency and two national security. We statistically examine how Twitter is being used surrounding these events, and compare and contrast how that behavior is different from more general Twitter use. Our findings suggest that Twitter messages sent during these types of events contain more displays of information broadcasting and brokerage, and we observe that general Twitter use seems to have evolved over time to offer more of an information-sharing purpose. We also provide preliminary evidence that Twitter users who join during and in apparent relation to a mass convergence or emergency event are more likely to become long-term adopters of the technology.
Address University of Colorado, Boulder, United States
Corporate Author Thesis
Publisher Information Systems for Crisis Response and Management, ISCRAM Place of Publication Gothenburg Editor J. Landgren, S. Jul
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9789163347153 Medium
Track Collaboration and Social Networking Expedition Conference 6th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 604
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Author (up) 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 (up) Andrea H. Tapia; Kartikeya Bajpai; Bernard J. Jansen; John Yen
Title Seeking the trustworthy tweet: Can microblogged data fit the information needs of disaster response and humanitarian relief organizations 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 Disasters; Information systems; Public relations; Humanitarian; Microblogging; Ngo; Relief; Trust; Twitter; Emergency services
Abstract Message data has, as yet, not been adopted by large-scale, international humanitarian relief organizations in an instrumental fashion. While the largest of these organizations have adopted messaging as part of their Public Relations functions, few have used any form of message data originating in the field, at the time of disaster. The message data being contributed by bystanders and those affected by a disaster, as it is happening, has largely been deemed as unverifiable and untrustworthy, and thus construed as unsuitable for incorporation into established mechanisms for organizational decision-making. In this paper, we describe the discursive barriers to the use of microblogged data by Humanitarian NGOs during times of disaster. We present data and findings from a study involving representatives from thirteen humanitarian organizations. Our analysis suggests that the organizational barriers, both in terms of function and structure, and the data itself, form barriers to organizational use of microblogged data. We propose three socio-technical solutions to surpassing adoption bottlenecks, namely bounded microblogging, microblogged data as contextual data, and/or use of computational solutions.
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 Humanitarian Challenges Expedition Conference 8th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 991
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Author (up) Andrea H. Tapia; Kathleen A. Moore; Nichloas J. Johnson
Title Beyond the trustworthy tweet: A deeper understanding of microblogged data use by disaster response and humanitarian relief organizations 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 770-779
Keywords Disasters; Information management; Information systems; Societies and institutions; Humanitarian; Microblogging; Ngo; Relief; Trust; Twitter; Emergency services
Abstract In this paper we present findings from interviews conducted with representatives from large international disaster response organizations concerning their use of social media data in crisis response. We present findings in which the barriers to use by responding organizations have gone beyond simple discussions of trustworthiness to that of more operational issues rather than mere data quality. We argue that the landscape of the use of microblogged data in crisis response is varied, with pockets of use and acceptance among organizations. We found that microblogged data is useful to responders in situations where information is limited, such as at the beginning of an emergency response effort, and when the risks of ignoring an accurate response outweigh the risks of acting on an incorrect one. In some situations, such as search and rescue operations, microblogged data may never meet the standards of quality required. In others, such as resource and supply management, microblogging data could be useful as long as it is appropriately verified and classified.
Address College of Information Sciences and Technology, Penn State University, 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 993
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Author (up) Andrea H. Tapia; Nicolas LaLone; Elizabeth MacDonald; Reid Priedhorsky; Hall Hall
Title Crowdsourcing rare events: Using curiosity to draw participants into science and early warning systems Type Conference Article
Year 2014 Publication ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2014
Volume Issue Pages 135-144
Keywords Information systems; Observatories; Satellite observatories; Aurora; Citizen science; Early Warning System; Space weather; Twitter; Alarm systems
Abstract This research presents a centralized boundary object website and mobile app focused on allowing participants to participate in developing an early warning system through space weather and the beauty of the aurora borealis. Because of the beauty and majesty of auroral activity, people will seek information about when and where these unpredictable events occur. This activity, commonly referred to as nowcasting, can be combined with scientific data collected from observatories and satellites and serve as an early warning system with potentially far greater accuracy and timeliness than the current state of the art. We believe that long-term engagement with a citizen science tool will help bridge the many social worlds surrounding the aurora borealis and lead to the development of an early warning system that may correlate the visibility of the northern lights to violent space weather. We hope this will lead to other real time crowdsourced early warning systems in the future.
Address Penn State University, United States; NASA, GSFC, United States; LANL, United States; Science Education Solutions, 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 Community Engagement in Crisis Informatics Research Expedition Conference 11th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 994
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Author (up) Andrea H. Tapia; Nicolas LaLone; Hyun-Woo Kim
Title Run amok: Group crowd participation in identifying the bomb and bomber from the Boston marathon bombing 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 265-274
Keywords Information systems; Social networking (online); Crowdsourcing; Ethical participation; First responders; Social responsibilities; Twitter; Emergency services
Abstract In this paper we tell a version of the story of the bombing of the Boston Marathon. At first, two online groups gathered images, video and textual information concerning the bombing of the Boston Marathon and shared these with the FBI and amongst themselves. Secondly, these groups then created mechanisms to conduct their own investigation into the identities of the perpetrators. Finally, the larger national media followed the results of these online group investigations and reported these as fact to a national audience. We choose Twitter as our data repository and conducted quantitative analyses of tweets sent during the Boston Bombing. The implications for not incorporating public crowd participation within the standard operating procedures of emergency services may result in either a loss of public confidence in the slow-moving nature of official response to uncontrollable, dangerous and irresponsible public and media participation that exacerbates the negative effects of any disaster.
Address Penn 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 Ethical, Legal and Social Issues of IT Supported Emergency Response Expedition Conference 11th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 992
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Author (up) Andrea Zielinski; Ulrich Bügel
Title Multilingual analysis of twitter news in support of mass emergency events Type Conference Article
Year 2012 Publication ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2012
Volume Issue Pages
Keywords Disasters; Earthquakes; Information retrieval systems; Information systems; Sensor networks; Cross-lingual information; Early Warning System; Earthquake events; Event detection; Multilingual analysis; Social sensors; Support crisis management; Twitter; Social networking (online)
Abstract Social media are increasingly becoming a source for event-based early warning systems in the sense that they can help to detect natural disasters and support crisis management during or after disasters. In this work-in-progress paper we study the problems of analyzing multilingual twitter feeds for emergency events. The present work focuses on English as “lingua franca” and on under-resourced Mediterranean languages in endangered zones, particularly Turkey, Greece, and Romania Generally, as local civil protection authorities and the population are likely to respond in their native language. We investigated ten earthquake events and defined four language-specific classifiers that can be used to detect earthquakes by filtering out irrelevant messages that do not relate to the event. The final goal is to extend this work to more Mediterranean languages and to classify and extract relevant information from tweets, translating the main keywords into English. Preliminary results indicate that such a filter has the potential to confirm forecast parameters of tsunami affecting coastal areas where no tide gauges exist and could be integrated into seismographic sensor networks. © 2012 ISCRAM.
Address Fraunhofer IOSB, Germany
Corporate Author Thesis
Publisher Simon Fraser University Place of Publication Vancouver, BC Editor L. Rothkrantz, J. Ristvej, Z.Franco
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9780864913326 Medium
Track Command and Control Studies Expedition Conference 9th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 245
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Author (up) Anna Kruspe; Jens Kersten; Friederike Klan
Title Detecting event-related tweets by example using few-shot models 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, Relevance, Keywords, Hashtags, Few-shot models, One-class classification
Abstract Social media sources can be helpful in crisis situations, but discovering relevant messages is not trivial. Methods

have so far focused on universal detection models for all kinds of crises or for certain crisis types (e.g. floods).

Event-specific models could implement a more focused search area, but collecting data and training new models for

a crisis that is already in progress is costly and may take too much time for a prompt response. As a compromise,

manually collecting a small amount of example messages is feasible. Few-shot models can generalize to unseen

classes with such a small handful of examples, and do not need be trained anew for each event. We show how

these models can be used to detect crisis-relevant tweets during new events with just 10 to 100 examples and

counterexamples. We also propose a new type of few-shot model that does not require counterexamples.
Address German Aerospace Center (DLR), Germany
Corporate Author Thesis
Publisher Iscram Place of Publication Valencia, Spain Editor Franco, Z.; González, J.J.; Canós, J.H.
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 978-84-09-10498-7 Medium
Track T8- Social Media in Crises and Conflicts Expedition Conference 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019)
Notes Approved no
Call Number Serial 1911
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Author (up) Antone Evans Jr.; Yingyuan Yang; Sunshin Lee
Title Towards Predicting COVID-19 Trends: Feature Engineering on Social Media Responses 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 792-807
Keywords Big Data Analysis, Machine Learning, COVID-19, Twitter
Abstract During the course of this pandemic, the use of social media and virtual networks has been at an all-time high. Individuals have used social media to express their thoughts on matters related to this pandemic. It is difficult to predict current trends based on historic case data because trends are more connected to social activities which can lead to the spread of coronavirus. So, it's important for us to derive meaningful information from social media as it is widely used. Therefore, we grouped tweets by common keywords, found correlations between keywords and daily COVID-19 statistics and built predictive modeling. The features correlation analysis was very effective, so trends were predicted very well. A RMSE score of 0.0425504, MAE of 0.03295105 and RSQ of 0.5237014 in relation to daily deaths. In addition, we found a RMSE score of 0.07346836, MAE of 0.0491152 and RSQ 0.374529 in relation to daily cases.
Address University of Illinois Springfield; University of Illinois Springfield; University of Illinois Springfield
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 aevan7@uis.edu Approved no
Call Number ISCRAM @ idladmin @ Serial 2374
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Author (up) Antonin Segault; Federico Tajariol; Ioan Roxin
Title #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 (up) Antonin Segault; Federico Tajariol; Yang Ishigaki; Ioan Roxin
Title #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 (up) Apoorva Chauhan; Amanda Hughes
Title COVID-19 Named Resources on Facebook, Twitter, and Reddit 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 679-690
Keywords Crisis Named Resources, Facebook, Twitter, Reddit, COVID-19
Abstract Crisis Named Resources (CNRs) are social media accounts and pages named after a crisis event. They are created soon after an event occurs. CNRs share a lot of information around an event and are followed by many. In this study, we identify CNRs created around COVID-19 on Facebook, Twitter, and Reddit. We analyze when these resources were created, why they were created, how they were received by members of the public, and who created them. We conclude by comparing CNRs created around COVID-19 with past crisis events and discuss how CNR owners attempt to manage content and combat misinformation.
Address University of Waterloo; Brigham Young University
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 apoorva.chauhan@aggiemail.usu.edu Approved no
Call Number ISCRAM @ idladmin @ Serial 2364
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Author (up) Axel Schulz; Tung Dang Thanh; Heiko Paulheim; Immanuel Schweizer
Title 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 (up) Benjamin Herfort; João Porto De Albuquerque; Svend-Jonas Schelhorn; Alexander Zipf
Title Does the spatiotemporal distribution of tweets match the spatiotemporal distribution of flood phenomena? A study about the River Elbe Flood in June 2013 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 747-751
Keywords Catchments; Data mining; Information systems; Social networking (online); Spatial distribution; Water levels; Crisis management; Digital elevation model; Geographical features; Situational awareness; Social media; Social media platforms; Spatiotemporal distributions; Twitter; Floods
Abstract In this paper we present a new approach to enhance information extraction from social media that relies upon the geographical relations between twitter data and flood phenomena. We use specific geographical features like hydrological data and digital elevation models to analyze the spatiotemporal distribution of georeferenced twitter messages. This approach is applied to examine the River Elbe Flood in Germany in June 2013. Although recent research has shown that social media platforms like Twitter can be complementary information sources for achieving situation awareness, previous work is mostly concentrated on the classification and analysis of tweets without resorting to existing data related to the disaster, e.g. catchment borders or sensor data about river levels. Our results show that our approach based on geographical relations can help to manage the high volume and velocity of social media messages and thus can be valuable for both crisis response and preventive flood monitoring.
Address GIScience Department, Heidelberg University, Germany; Dept. of Computer Systems/ICMC, University of Sao Paulo, Brazil
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 572
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Author (up) Cody Buntain; Richard Mccreadie; Ian Soboroff
Title Incident Streams 2020: TRECIS in the Time of COVID-19 Type Conference Article
Year 2021 Publication ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2021
Volume Issue Pages 621-639
Keywords Emergency Management, Crisis Informatics, Twitter, Categorization, Prioritization, COVID-19
Abstract Between 2018 and 2019, the Incident Streams track (TREC-IS) has developed standard approaches for classifying the types and criticality of information shared in online social spaces during crises, but the introduction of SARS-CoV-2 has shifted the landscape of online crises substantially. While prior editions of TREC-IS have lacked data on large-scale public-health emergencies as these events are exceedingly rare, COVID-19 has introduced an over-abundance of potential data, and significant open questions remain about how existing approaches to crisis informatics and datasets built on other emergencies adapt to this new context. This paper describes how the 2020 edition of TREC-IS has addressed these dual issues by introducing a new COVID-19-specific task for evaluating generalization of existing COVID-19 annotation and system performance to this new context, applied to 11 regions across the globe. TREC-IS has also continued expanding its set of target crises, adding 29 new events and expanding the collection of event types to include explosions, fires, and general storms, making for a total of 9 event types in addition to the new COVID-19 events. Across these events, TREC-IS has made available 478,110 COVID-related messages and 282,444 crisis-related messages for participant systems to analyze, of which 14,835 COVID-related and 19,784 crisis-related messages have been manually annotated. Analyses of these new datasets and participant systems demonstrate first that both the distributions of information type and priority of information vary between general crises and COVID-19-related discussion. Secondly, despite these differences, results suggest leveraging general crisis data in the COVID-19 context improves performance over baselines. Using these results, we provide guidance on which information types appear most consistent between general crises and COVID-19.
Address New Jersey Institute of Technology; University of Glasgow; National Institute of Standards and Technology
Corporate Author Thesis
Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 978-1-949373-61-5 ISBN Medium
Track Social Media for Disaster Response and Resilience Expedition Conference 18th International Conference on Information Systems for Crisis Response and Management
Notes cbuntain@njit.edu Approved no
Call Number ISCRAM @ idladmin @ Serial 2360
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Author (up) Daniel Link; Bernd Hellingrath; Tom De Groeve
Title Twitter integration and content moderation in GDACSmobile 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 67-71
Keywords Disaster prevention; Disasters; Mobile devices; Social networking (online); Content moderation; Coordination; Gdacs; GDACSmobile; Needs Assessment; Social media; Twitter; Information management
Abstract Recent years have shown that mobile devices and Twitter can play a significant role in providing real-time data from disaster-affected areas to disaster managers. Against this background we present a workflow for Twitter integration into a disaster management information system, and a concept for content moderation that can increase the quality of disseminated information.
Address Dept. of Information Systems and Logistics, European Research Center for Information Systems (ERCIS), University of Münster, Germany; Joint Research Centre of European Commission, Italy
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 Coordination and Collaboration Expedition Conference 10th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 709
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Author (up) David F. Merrick; Tom Duffy
Title Utilizing community volunteered information to enhance disaster situational awareness 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 858-862
Keywords Civil defense; Disasters; Information systems; Risk management; Social networking (online); Community volunteered information; Crowd sourcing; Facebook; Situational awareness; Social media; Twitter; Emergency services
Abstract Social media allows the public to engage in the disaster response and recovery process in new and exciting ways. Many emergency management agencies in the United States are embracing social media as a new channel for alerts, warnings, and public outreach, but very few are mining the massive amounts of data available for use in disaster response. The research reflected in this paper strives to help emergency management practitioners harness the power of community volunteered information in a way that is still novel in most parts of the country. Field verification and research combined with survey results attempts to identify and solve many of the barriers to adoption that currently exist. By helping practitioners understand the virtues and limitations of this type of data and information, this research will encourage the use of community volunteered information in the emergency operations center.
Address Florida State University, 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 767
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Author (up) Diana Fischer; Carsten Schwemmer; Kai Fischbach
Title Terror Management and Twitter: The Case of the 2016 Berlin Terrorist Attack Type Conference Article
Year 2018 Publication ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2018
Volume Issue Pages 459-468
Keywords Terrorist attacks, social networking sites, social media, Twitter, topic modeling, terror management, sense-making
Abstract There is evidence that people increasingly use social networking sites like Twitter in the aftermath of terrorist attacks to make sense of the events at the collective level. This work-in-progress paper focuses on the content of Twitter messages related to the 2016 terrorist attack on the Berlin Christmas market. We chose topic modeling to investigate the Twitter data and the terror management theory perspective to understand why people used Twitter in the aftermath of the attack. In particular, by connecting people and providing a real-time communication channel, Twitter helps its users collectively negotiate their worldviews and re-establish self-esteem. We provide first results and discuss next steps.
Address
Corporate Author Thesis
Publisher Rochester Institute of Technology Place of Publication Rochester, NY (USA) Editor Kees Boersma; Brian Tomaszeski
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 978-0-692-12760-5 Medium
Track Social Media Studies Expedition Conference ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 2123
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Author (up) Elodie Fichet; John Robinson; Dharma Dailey; Kate Starbird
Title Eyes on the Ground: Emerging Practices in Periscope Use during Crisis Events Type Conference Article
Year 2016 Publication ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2016
Volume Issue Pages
Keywords Social Media; Periscope; Twitter; Crisis Informatics; Emergency Management
Abstract This empirical analysis examines the use of the live-streaming application Periscope in three crises that occurred in 2015. Qualitative analyses of tweets relating to the Amtrak derailment in Philadelphia, Baltimore protests after Freddie Grey?s death, and Hurricane Joaquin flooding in South Carolina reveal that this recently deployed application is being used by both citizens and journalists for information sharing, crisis coverage and commentary. The accessibility and immediacy of live video directly from crisis situations, and the embedded chats which overlay on top of a video feed, extend the possibilities of real-time interaction between remote crowds and those on the ground in a crisis. These empirical findings suggest several potential challenges and opportunities for responders.
Address
Corporate Author Thesis
Publisher Federal University of Rio de Janeiro Place of Publication Rio de Janeiro, Brasil Editor A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3388 ISBN 978-84-608-7984-9 Medium
Track Social Media Studies Expedition Conference 13th International Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number ISCRAM @ idladmin @ Serial 1391
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Author (up) Evan A. Sultanik; Clayton Fink
Title Rapid geotagging and disambiguation of social media text via an indexed gazetteer Type Conference Article
Year 2012 Publication ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2012
Volume Issue Pages
Keywords Information systems; Contextual information; Disambiguation; Gazetteer; Geolocations; Micro-blogging services; Twitter; Unsupervised approaches; Unsupervised techniques; Social networking (online)
Abstract Microblogging services like Twitter afford opportunities for real time determination of situation awareness during crises as people report, via their statuses, information about events on the ground. An important component of the information included in a tweet are mentions of place names that may be sites of damage, injuries, or relief efforts. Methods for extracting these place names and determining the actual location being referenced are an essential part of the suite of tools required for automated extraction of situation awareness from tweets. Extracting and disambiguating place name mentions from text have been areas of extensive research. Twitter, however, presents challenges given the 140 character restriction on status and the informal, abbreviated language that are a norm in this communication channel. Named entity recognizers, which are dependent on labeled training data, may not be useful in this medium for extracting location mentions because the typical training domains for these taggers are absent the noise found in Twitter statuses. Additionally, the contextual information that is necessary for disambiguating place names is not always present. In this paper, we demonstrate a new technique, RapidGeo, for extracting and disambiguating place names from a location specific Twitter feed using an unsupervised technique for tagging location mentions and relying on the known geographic context of the feed for disambiguation. Our location tagging technique performs much better than an off-the-shelf named entity recognizer and we achieve reasonable precision in disambiguating extracted place names. We argue that such fast, high precision, unsupervised approaches are needed when important, actionable information is required from noisy data sources such as Twitter. © 2012 ISCRAM.
Address Johns Hopkins University, APL, United States
Corporate Author Thesis
Publisher Simon Fraser University Place of Publication Vancouver, BC Editor L. Rothkrantz, J. Ristvej, Z.Franco
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9780864913326 Medium
Track Intelligent Systems Expedition Conference 9th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 212
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Author (up) Federico Angaramo; Claudio Rossi
Title Online clustering and classification for real-time event detection in Twitter 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 1098-1107
Keywords Event detection, Social Media, Clustering, Machine Learning, Twitter
Abstract Event detection from social media is a challenging task due to the volume, the velocity and the variety of user-generated data requiring real-time processing. Despite recent works on this subject, a generalized and scalable approach that could be applied across languages and topics has not been consolidated, yet. In this paper, we propose a methodology for real-time event detection from Twitter data that allows users to select a topic of interest by defining a simple set of keywords and a matching rule. We implement the proposed methodology and evaluate it with real data to detect different types of events.
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 1st International Workshop on Intelligent Crisis Management Technologies for Climate Events (ICMT) Expedition Conference ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 2182
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Author (up) Fedor Vitiugin; Carlos Castillo
Title Comparison of Social Media in English and Russian During Emergencies and Mass Convergence 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 Social Media, Crisis Informatics, Twitter, Information Extraction.
Abstract Twitter is used for spreading information during crisis events. In this paper, we first retrieve event-related information

posted in English and Russian during six disasters and sports events that received wide media coverage in both

languages, using an adaptive information filtering method for automating the collection of about 100 000 messages.

We then compare the contents of these messages in terms of 17 informational and linguistic features using a

difference in differences approach. Our results suggest that posts in each language are focused on different types

of information. For instance, almost 50% of the popular people mentioned in these messages appear exclusively

in either the English messages or the Russian messages, but not both. Our results also suggest differences in the

adoption of platform mechanics during crises between Russian-speaking and English-speaking users. This has

important implications for data collection during crises, which is almost always focused on a single language.
Address Independent;Universitat Pompeu Fabra
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 ISCRAM @ idladmin @ Serial 1916
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Author (up) Francesca Comunello; Simone Mulargia; Piero Polidoro; Emanuele Casarotti; Valentino Lauciani
Title No Misunderstandings During Earthquakes: Elaborating and Testing a Standardized Tweet Structure for Automatic Earthquake Detection Information 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 Automatic detection; earthquakes; tweet comprehension; tweet syntax; Twitter
Abstract Social media have proven to be useful resources for spreading verified information during natural disasters. Nevertheless, little attention has hitherto been devoted to the peculiarities of constructing effective tweets (and tweet formats), or to common users? comprehension of tweets conveying scientific information. In this paper, social scientists and seismologists collaborated in order to elaborate and test a standardized tweet structure to be used during earthquakes, expanding on the results of a quali-quantitative research project. The tweet format is specifically designed to launch an innovative information service by Istituto Nazionale di Geofisica e Vulcanologia (INGV): tweeting the automatic detection of earthquakes with a magnitude greater than 3. This paper illustrates the steps of the research process that led to elaborating a tweet format that will be used in the next few months by the official Twitter account @INGVterremoti.
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 1232
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