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Author  |
Mark Latonero; Irina Shklovski | ||||
| Title | Respectfully yours in safety and service: Emergency management & social media evangelism | Type | Conference Article | ||
| Year | 2010 | Publication | ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings | Abbreviated Journal | ISCRAM 2010 |
| Volume | Issue | Pages | |||
| Keywords | Civil defense; Disasters; Information systems; Social networking (online); Societies and institutions; Emergency management; Evangelism; Lafd; Risk communication; Social media; Twitter; Risk management | ||||
| Abstract | In this paper we consider how emergency response organizations utilize available social media technologies to communicate with the public in emergencies and to potentially collect valuable information using the public as sources of information on the ground. We discuss the use of public social media tools from the emergency management professionals. viewpoint with a particular focus on the use of Twitter. Little research has investigated Twitter usage in crisis situations from an organizational perspective. This paper contributes to our understanding of organizational innovation, risk communication, and technology adoption by emergency management. An in-depth case study of Public Information Officers of the Los Angeles Fire Department highlights the importance of the information evangelist within emergency management organizations and details the challenges those organizations face with an engagement with social media and Twitter. This article provides insights into practices and challenges of new media implementation for crisis and risk management organizations. | ||||
| Address | California State University Fullerton, USC Annenberg Center on Communication Leadership and Policy, Netherlands; Digital Culture and Mobile Communication Research Group, IT University of Copenhagen, Netherlands | ||||
| Corporate Author | Thesis | ||||
| Publisher | Information Systems for Crisis Response and Management, ISCRAM | Place of Publication | Seattle, WA | Editor | S. French, B. Tomaszewski, C. Zobel |
| 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 | Collaboration and Social Networking | Expedition | Conference | 7th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 681 | |||
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| Author |
McCreadie, R.; Buntain, C. | ||||
| Title | CrisisFACTS: Buidling and Evaluating Crisis Timelines | Type | Conference Article | ||
| Year | 2023 | Publication | Proceedings of the 20th International ISCRAM Conference | Abbreviated Journal | Iscram 2023 |
| Volume | Issue | Pages | 320-339 | ||
| Keywords | Emergency Management; Crisis Informatics News; Twitter; Facebook; Reddit; Wikipedia; Summarization | ||||
| Abstract | Between 2018 and 2021, the Incident Streams track (TREC-IS) developed standard approaches for classifying information types and criticality of tweets during crises. While successful in producing substantial collections of labeled data, TREC-IS as a data challenge had several limitations: It only evaluated information at type-level rather than what was reported; it only used Twitter data; and it lacked measures of redundancy in system output. This paper introduces Crisis Facts and Cross-Stream Temporal Summarization (CrisisFACTS), a new data challenge piloted in 2022 and developed to address these limitations. The CrisisFACTS framework recasts TREC-IS into an event-summarization task using multiple disaster-relevant data streams and a new fact-based evaluation scheme, allowing the community to assess state-of-the-art methods for summarizing disaster events Results from CrisisFACTS in 2022 include a new test-collection comprising human-generated disaster summaries along with multi-platform datasets of social media, crisis reports and news coverage for major crisis events. | ||||
| Address | University of Glasgow; University of Maryland, College Park (UMD) | ||||
| 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/JVQZ9405 | Approved | no | ||
| Call Number | ISCRAM @ idladmin @ | Serial | 2529 | ||
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| Author |
Muhammad Imran; Shady Elbassuoni; Carlos Castillo; Fernando Díaz; Patrick Meier | ||||
| Title | Extracting information nuggets from disaster- Related messages in social media | Type | Conference Article | ||
| Year | 2013 | Publication | ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2013 |
| Volume | Issue | Pages | 791-801 | ||
| Keywords | Artificial intelligence; Data visualization; Disasters; Information retrieval; Information systems; Learning systems; Social networking (online); Emergency responders; Extracting information; Machine learning methods; Situational awareness; Social media; Supervised classification; Twitter; Visualization system; Emergency services | ||||
| Abstract | Microblogging sites such as Twitter can play a vital role in spreading information during “natural” or man-made disasters. But the volume and velocity of tweets posted during crises today tend to be extremely high, making it hard for disaster-affected communities and professional emergency responders to process the information in a timely manner. Furthermore, posts tend to vary highly in terms of their subjects and usefulness; from messages that are entirely off-topic or personal in nature, to messages containing critical information that augments situational awareness. Finding actionable information can accelerate disaster response and alleviate both property and human losses. In this paper, we describe automatic methods for extracting information from microblog posts. Specifically, we focus on extracting valuable “information nuggets”, brief, self-contained information items relevant to disaster response. Our methods leverage machine learning methods for classifying posts and information extraction. Our results, validated over one large disaster-related dataset, reveal that a careful design can yield an effective system, paving the way for more sophisticated data analysis and visualization systems. | ||||
| Address | University of Trento, Italy; American Univ. of Beirut, Lebanon; QCRI, Qatar; Microsoft Research, Qatar | ||||
| Corporate Author | Thesis | ||||
| Publisher | Karlsruher Institut fur Technologie | Place of Publication | KIT; Baden-Baden | Editor | T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9783923704804 | Medium | |
| Track | Social Media | Expedition | Conference | 10th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 613 | |||
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| Author |
Nick LaLone; Andrea H. Tapia; Nathan A. Case; Elizabeth MacDonald; Michelle Hall; Matt Heavner | ||||
| Title | HYBRID COMMUNITY PARTICIPATION IN CROWDSOURCED EARLY WARNING SYSTEMS | 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 | Aurorasaurus; citizen science; crowdsourcing; Early Warning System; Twitter | ||||
| Abstract | In this paper we present Aurorasaurus: a website, a mobile application, and a citizen science initiative that allows a community of users to report and verify sightings of the Aurora Borealis. Through ad-hoc data indirectly offered through social media, a community of citizen scientists verify sightings of the Aurora Borealis. These verified data are tested against currently existing aurora-forecasting models. The insights these data provide are transformed into map and text-based forms. In addition, notifications are sent to interested participants in a timely manner. This is a design test-bed for an early warning system (EWS) that is capable of detecting and communicating the earliest signs of disaster to community members in near real time. Most importantly, this system incorporates community participation in improving the quality of data mined from Twitter and direct community contributions. | ||||
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| 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 | Community Engagement | Expedition | Conference | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | yes | |||
| Call Number | Serial | 1270 | |||
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| Author |
Ntalla Athanasia; Ponis T. Stavros | ||||
| Title | Twitter as an instrument for crisis response: The Typhoon Haiyan case study | Type | Conference Article | ||
| Year | 2015 | Publication | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2015 |
| Volume | Issue | Pages | |||
| Keywords | Crisis Management; emergency response; Haiyan; social media; Twitter | ||||
| Abstract | The research presented in this paper attempts an initial evaluation of Twitter as an instrument for emergency response in the context of a recent crisis event. The case of the 2013 disaster, when typhoon Haiyan hit Philippines is examined by analyzing nine consecutive days of Twitter messages and comparing them to the actual events. The results indicate that during disasters, Twitter users tend to post messages to enhance situation awareness and to motivate people to act. Furthermore, tweets were found reliable and provided valuable information content, supporting the argument that Twitter presents a very good potential to become a useful tool in situations where rapid emergency response is essential. | ||||
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| Corporate Author | Thesis | ||||
| Publisher | University of Agder (UiA) | Place of Publication | Kristiansand, Norway | Editor | L. Palen; M. Buscher; T. Comes; A. Hughes |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9788271177881 | Medium | |
| Track | Social Media Studies | Expedition | Conference | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | yes | |||
| Call Number | Serial | 1238 | |||
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| Author |
Richard McCreadie; Cody Buntain; Ian Soboroff | ||||
| Title | TREC Incident Streams: Finding Actionable Information on Social Media | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages | |||
| Keywords | Emergency Management, Crisis Informatics, Real-time, Twitter, Categorization | ||||
| Abstract | The Text Retrieval Conference (TREC) Incident Streams track is a new initiative that aims to mature social media-based emergency response technology. This initiative advances the state of the art in this area through an evaluation challenge, which attracts researchers and developers from across the globe. The 2018 edition of the track provides a standardized evaluation methodology, an ontology of emergency-relevant social media information types, proposes a scale for information criticality, and releases a dataset containing fifteen test events and approximately 20,000 labeled tweets. Analysis of this dataset reveals a significant amount of actionable information on social media during emergencies (> 10%). While this data is valuable for emergency response efforts, analysis of the 39 state-of-the-art systems demonstrate a performance gap in identifying this data. We therefore find the current state-of-the-art is insufficient for emergency responders? requirements, particularly for rare actionable information for which there is little prior training data available. |
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| Address | University of Glasgow, United Kingdom;New York University, USA;National Institute of Standards and Technology, USA | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1867 | |||
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| Author |
Richard McCreadie; Cody Buntain; Ian Soboroff | ||||
| Title | Incident Streams 2019: Actionable Insights and How to Find Them | Type | Conference Article | ||
| Year | 2020 | Publication | ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2020 |
| Volume | Issue | Pages | 744-760 | ||
| Keywords | Emergency Management, Crisis Informatics, Real-time, Twitter, Categorization. | ||||
| Abstract | The ubiquity of mobile internet-enabled devices combined with wide-spread social media use during emergencies is posing new challenges for response personnel. In particular, service operators are now expected to monitor these online channels to extract actionable insights and answer questions from the public. A lack of adequate tools makes this monitoring impractical at the scale of many emergencies. The TREC Incident Streams (TREC-IS) track drives research into solving this technology gap by bringing together academia and industry to develop techniques for extracting actionable insights from social media streams during emergencies. This paper covers the second year of TREC-IS, hosted in 2019 with two editions, 2019-A and 2019-B, contributing 12 new events and approximately 20,000 new tweets across 25 information categories, with 15 research groups participating across the world. This paper provides an overview of these new editions, actionable insights from data labelling, and the automated techniques employed by participant systems that appear most effective. | ||||
| Address | University of Glasgow; InfEco Lab, New Jersey Institute of Technology (NJIT); National Institute of Standards and Technology (NIST) | ||||
| Corporate Author | Thesis | ||||
| Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 978-1-949373-27-67 | ISBN | 2411-3453 | Medium | |
| Track | Social Media for Disaster Response and Resilie | Expedition | Conference | 17th International Conference on Information Systems for Crisis Response and Management | |
| Notes | richard.mccreadie@glasgow.ac.uk | Approved | no | ||
| Call Number | Serial | 2268 | |||
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| Author |
Rob Grace | ||||
| Title | Hyperlocal Toponym Usage in Storm-Related Social Media | 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 | 849-859 | ||
| Keywords | Volunteered Geographic Information, Twitter, Information Behavior, Crisis Informatics, Emergency Management. | ||||
| Abstract | Crisis responders need to locate events reported in social media messages that typically lack geographic metadata such as geotags. Toponyms, places names referenced in messages, provide another source of geographic information, however, the availability and granularity of toponyms in crisis social media remain poorly understood. This study examines toponym usage and granularity across six categories of crisis-related information posted on Twitter during a severe storm. Findings show users often include geographic information in messages describing local and remote storm events but do so rarely when discussing other topics, more often use toponyms than geotags when describing local events, and tend to include fine-grained toponyms in reports of infrastructure damage and service disruption and course-grained toponyms in other kinds of storm-related messages. These findings present requirements for hyperlocal geoparsing techniques and suggest that social media monitoring presents more immediate affordances for course-grained damage assessment than fine-grained situational awareness during a crisis. | ||||
| Address | Texas Tech 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 | 978-1-949373-27-75 | ISBN | 2411-3461 | Medium | |
| Track | Social Media for Disaster Response and Resilie | Expedition | Conference | 17th International Conference on Information Systems for Crisis Response and Management | |
| Notes | rob.grace@ttu.edu | Approved | no | ||
| Call Number | Serial | 2276 | |||
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| Author |
Robert Power; Bella Robinson; John Colton; Mark Cameron | ||||
| Title | 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. |
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| 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 |
Robert Power; Bella Robinson; Mark Cameron | ||||
| Title | Insights from a Decade of Twitter Monitoring for Emergency Management | Type | Conference Article | ||
| Year | 2023 | Publication | Proceedings of the ISCRAM Asia Pacific Conference 2022 | Abbreviated Journal | Proc. ISCRAM AP 2022 |
| Volume | Issue | Pages | 247-257 | ||
| Keywords | Crisis Coordination; Disaster Management; Situation Awareness; Social Media; System Architecture; Twitter | ||||
| Abstract | The Emergency Situation Awareness (ESA) tool began as a research study into automated web text mining to support emergency management use cases. It started in late 2009 by investigating how people respond on Twitter to specific emergency events and we quickly realized that every emergency situation is different and preemptively defining keywords to search for content on Twitter beforehand would likely miss important information. So, in late September 2011 we established location-based searches with the aim of collecting all the tweets published in Australia and New Zealand. This was the beginning of over a decade of collecting and processing tweets to help emergency response agencies and crisis coordination centres use social media content as a new channel of information to support their work practices and to engage with the community impacted by emergency events. This journey has seen numerous challenges overcome to continuously maintain a tweet stream for an operational system. This experience allows us to derive insights into the changing use of Twitter over this time. In this paper we present some of the lessons we’ve learned from maintaining a Twitter monitoring system for emergency management use cases and we provide some insights into the changing nature of Twitter usage by users over this period. | ||||
| Address | CSIRO Data61; CSIRO Data61; CSIRO Data61 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Massey Unversity | Place of Publication | Palmerston North, New Zealand | Editor | Thomas J. Huggins, V.L. |
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-0-473-66845-7 | Medium | |
| Track | Social Media for Disaster Response | Expedition | Conference | ||
| Notes | Approved | no | |||
| Call Number | ISCRAM @ idladmin @ | Serial | 2498 | ||
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| Author |
Robert Thomson; Naoya Ito; Hinako Suda; Fangyu Lin; Yafei Liu.; Ryo Hayasaka; Ryuzo Isochi; Zhou Wang | ||||
| Title | Trusting tweets: The Fukushima disaster and information source credibility on Twitter | 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 | Cell culture; Information systems; Nuclear power plants; Social networking (online); Anonymity; Credibility; Crisis communications; Deindividuation; Fukushima; Social media; Trust; Twitter; Disasters | ||||
| Abstract | This paper focuses on the micro-blogging service Twitter, looking at source credibility for information shared in relation to the Fukushima Daiichi nuclear power plant disaster in Japan. We look at the sources, credibility, and between-language differences in information shared in the month following the disaster. Messages were categorized by user, location, language, type, and credibility of information source. Tweets with reference to third-party information made up the bulk of messages sent, and it was also found that a majority of those sources were highly credible, including established institutions, traditional media outlets, and highly credible individuals. In general, profile anonymity proved to be correlated with a higher propensity to share information from low credibility sources. However, Japanese-language tweeters, while more likely to have anonymous profiles, referenced low-credibility sources less often than non-Japanese tweeters, suggesting proximity to the disaster mediating the degree of credibility of shared content. © 2012 ISCRAM. | ||||
| Address | Graduate School of International Media, Communication and Tourism Studies, Japan; Research Faculty of Media Communication, Hokkaido University, Japan | ||||
| 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 | 216 | |||
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| Author |
Seungwon Yang; Haeyong Chung; Xiao Lin; Sunshin Lee; Liangzhe Chen; Andrew Wood; Andrea Kavanaugh; Steven D. Sheetz; Donald J. Shoemaker; Edward A. Fox | ||||
| Title | PhaseVis1: What, when, where, and who in visualizing the four phases of emergency management through the lens of social media | Type | Conference Article | ||
| Year | 2013 | Publication | ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2013 |
| Volume | Issue | Pages | 912-917 | ||
| Keywords | Civil defense; Classification (of information); Data visualization; Information systems; Risk management; 10-fold cross-validation; Classification algorithm; Classification evaluation; Emergency management; Potential utility; ThemeRiver; Through the lens; Twitter; Disasters | ||||
| Abstract | The Four Phase Model of Emergency Management has been widely used in developing emergency/disaster response plans. However, the model has received criticism contrasting the clear phase distinctions in the model with the complex and overlapping nature of phases indicated by empirical evidence. To investigate how phases actually occur, we designed PhaseVis based on visualization principles, and applied it to Hurricane Isaac tweet data. We trained three classification algorithms using the four phases as categories. The 10-fold cross-validation showed that Multi-class SVM performed the best in Precision (0.8) and Naïve Bayes Multinomial performed the best in F-1 score (0.782). The tweet volume in each category was visualized as a ThemeRiver[TM], which shows the 'What' aspect. Other aspects – 'When', 'Where', and 'Who' – Are also integrated. The classification evaluation and a sample use case indicate that PhaseVis has potential utility in disasters, aiding those investigating a large disaster tweet dataset. | ||||
| Address | Department of Computer Science, Virginia Tech, Blacksburg, VA 24061, United States; Department of Accounting and Information Systems, Virginia Tech, Blacksburg, VA 24061, United States; Department of Sociology, Virginia Tech, Blacksburg, VA 24061, United States | ||||
| Corporate Author | Thesis | ||||
| Publisher | Karlsruher Institut fur Technologie | Place of Publication | KIT; Baden-Baden | Editor | T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9783923704804 | Medium | |
| Track | Social Media | Expedition | Conference | 10th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 1122 | |||
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| Author |
Shane Errol Halse; Andrea Tapia; Anna Squicciarini; Cornelia Caragea | ||||
| Title | Tweet Factors Influencing Trust and Usefulness During Both Man-Made and Natural Disasters | 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; Sandy; Hurricane; Boston Bombing; Trust; Usefulness | ||||
| Abstract | To this date, research on crisis informatics has focused on the detection of trust in Twitter data through the use of message structure, sentiment, propagation and author. Little research has examined the usefulness of these messages in the crisis response domain. Toward detecting useful messages in case of crisis, in this paper, we characterize tweets, which are perceived useful or trustworthy, and determine their main features. Our analysis is carried out on two datasets (one natural and one man made) gathered from Twitter concerning hurricane Sandy in 2012 and the Boston Bombing 2013. The results indicate that there is a high correlation and similar factors (support for the victims, informational data, use of humor and type of emotion used) influencing trustworthiness and usefulness for both disaster types. This could have impacts on how messages from social media data are analyzed for use in crisis response. | ||||
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| 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 | 1403 | |||
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| Author |
Shane Errol Halse; Andrea Tapia; Anna Squicciarini; Cornelia Caragea | ||||
| Title | An Emotional Step Towards Automated Trust Detection in Crisis 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; Sandy; Hurricane; Boston; Bombing; Trust; Usefulness; Sentiment. Emotion | ||||
| Abstract | To this date, research on crisis informatics has focused on the detection of trust in Twitter data through the use of message structure, sentiment, propagation and author. Little research has examined the effects of perceived emotion of these messages in the crisis response domain. Toward detecting useful messages in case of crisis, we examine perceived emotions of these messages and how the different emotions affect the perceived usefulness and trustworthiness. Our analysis is carried out on two datasets gathered from Twitter concerning hurricane Sandy in 2012 and the Boston Bombing 2013. The results indicate that there is a significant difference in the perceived emotions that contribute towards the perceived trustworthiness and usefulness. This could have impacts on how messages from social media data are analyzed for use in crisis response. | ||||
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| Publisher | Federal University of Rio de Janeiro | Place of Publication | Rio de Janeiro, Brasil | Editor | A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
| 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 | Emerging Topics | Expedition | Conference | 13th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 1414 | |||
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| Author |
Shane Errol Halse; Aurélie Montarnal; Andrea Tapia; Frederick Benaben | ||||
| Title | Bad Weather Coming: Linking social media and weather sensor data | 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 | 507-515 | ||
| Keywords | Twitter; weather; sensor data; social media | ||||
| Abstract | In this paper we leverage the power of citizen supplied data. We examined how both physical weather sensor data (obtained from the weather underground API) and social media data (obtained from Twitter) can serve to improve local community awareness during a severe weather event. A local tornado warning was selected due to its small scale and isolated geographic area, and only Twitter data found from within this geo-locational area was used. Our results indicate that during a severe weather event, an increase in weather activity obtained from the local weather sensors does correlate with an increase in local social media usage. The data found on social media also contains additional information from, and about the community of interest during the event. While this study focuses on a small scale event, it provides the groundwork for use during a much larger weather event. | ||||
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| 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 | 2127 | |||
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| Author |
Shane Errol Halse; Rob Grace; Jess Kropczynski; Andrea Tapia | ||||
| Title | Simulating real-time Twitter data from historical datasets | 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 | Twitter, Simulation, Crisis Response, Social Media | ||||
| Abstract | In this paper, we will discuss a system design for simulating social media data based on historical datasets. While many datasets containing data collected from social media during crisis have become publicly available, there is a lack of tools or systems can present this data on the same timeline as it was originally posted. Through the design and use of the tool discussed in this paper, we show how historical datasets can be used for algorithm testing, such as those used in machine learning, to improve the quality of the data. In addition, the use of simulated data also has its benefits in training scenarios, which would allow participants to see real, non-fabricated social media messages in the same temporal manner as found on a social media platform. Lastly, we will discuss the positive reception and future improvements suggested by 911 Public Service Answering Point (PSAP) professionals. | ||||
| Address | PSU, United States of America;University of Cincinnati | ||||
| 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 | 1898 | |||
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| Author |
Shane Halse; Jess Kropczynski; Andrea Tapia | ||||
| Title | Using Metrics of Stability to Identify Points of Failure and Support in Online Information Distribution during a Disaster | 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 | 1121-1121 | ||
| Keywords | Information distribution, Social Media, Stability, Hurricane Sandy, Hurricane, Twitter, Social Network Analysis, Crisis | ||||
| Abstract | We utilize the 2012 Hurricane Sandy dataset to investigate methods to measure network stability during a crisis. While previous research on information distribution has focused on individuals that are most connected, or most willing to share information, we examined this dataset for indicators of network stability. The value of this measure is to identify the points of failure within the network. The findings in this paper provide support for the use of social network analysis within the realm of crisis response to identify the points of failure within the network. | ||||
| 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 | Poster | Expedition | Conference | ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 2184 | |||
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| Author |
Shane Halse; Jomara Binda; Samantha Weirman | ||||
| Title | It's what's outside that counts: Finding credibility metrics through non-message related Twitter features | 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 | 516-528 | ||
| Keywords | Twitter; social media; trust | ||||
| Abstract | Social media data, such as Twitter, enables crisis response personnel and civilians to share information during a crisis situation. However, a lack of information gatekeeping processes also translates into concerns about both content and source credibility. This research aims to identify Twitter metrics which could assist with the latter. A 2 (average number of hashtags used) x 2 (ratio of tweets/retweets posted) x 2 (ratio of follower/followee) between-subjects experiment was conducted to evaluate the level of influence of Twitter broker metrics on behavioral intention and the perception of source credibility. The findings indicate that follower/followee ratio in conjunction with hashtag usage approached a significant effect on perceived source credibility. In addition, both Twitter awareness metrics and dispositional trust played an important role in determining behavioral intentions and perceived source credibility. Implications and limitations are also discussed. | ||||
| 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 | 2128 | |||
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| Author |
Shivam Sharma; Cody Buntain | ||||
| Title | An Evaluation of Twitter Datasets from Non-Pandemic Crises Applied to Regional COVID-19 Contexts | Type | Conference Article | ||
| Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
| Volume | Issue | Pages | 808-815 | ||
| Keywords | covid19, twitter, trecis, cross-validation, machine learning, transfer learning | ||||
| Abstract | In 2020, we have witnessed an unprecedented crisis event, the COVID-19 pandemic. Various questions arise regarding the nature of this crisis data and the impacts it would have on the existing tools. In this paper, we aim to study whether we can include pandemic-type crisis events with general non-pandemic events and hypothesize that including labeled crisis data from a variety of non-pandemic events will improve classification performance over models trained solely on pandemic events. To test our hypothesis we study the model performance for different models by performing a cross validation test on pandemic only held-out sets for two different types of training sets, one containing only pandemic data and the other a combination of pandemic and non-pandemic crisis data, and comparing the results of the two. Our results approve our hypothesis and give evidence of some crucial information propagation upon inclusion of non-pandemic crisis data to pandemic data. | ||||
| Address | New Jersey Institute of Technology; New Jersey Institute of Technology | ||||
| Corporate Author | Thesis | ||||
| Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
| Track | Social Media for Disaster Response and Resilience | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
| Notes | cbuntain@njit.edu | Approved | no | ||
| Call Number | ISCRAM @ idladmin @ | Serial | 2375 | ||
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| Author |
Songhui Yue; Jyothsna Kondari; Aibek Musaev; Songqing Yue; Randy Smith | ||||
| Title | Using Twitter Data to Determine Hurricane Category: An Experiment | Type | Conference Article | ||
| Year | 2018 | Publication | ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2018 |
| Volume | Issue | Pages | 718-726 | ||
| Keywords | Social Media Data, Hurricane Category, Twitter, Prediction | ||||
| Abstract | Social media posts contain an abundant amount of information about public opinion on major events, especially natural disasters such as hurricanes. Posts related to an event, are usually published by the users who live near the place of the event at the time of the event. Special correlation between the social media data and the events can be obtained using data mining approaches. This paper presents research work to find the mappings between social media data and the severity level of a disaster. Specifically, we have investigated the Twitter data posted during hurricanes Harvey and Irma, and attempted to find the correlation between the Twitter data of a specific area and the hurricane level in that area. Our experimental results indicate a positive correlation between them. We also present a method to predict the hurricane category for a specific area using relevant Twitter data. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Rochester Institute of Technology | Place of Publication | Rochester, NY (USA) | Editor | Kees Boersma; Brian Tomaszeski |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-0-692-12760-5 | Medium | |
| Track | Social Media Studies | Expedition | Conference | ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 2145 | |||
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| Author |
Soudip Roy Chowdhury; Muhammad Imran; Muhammad Rizwan Asghar; Amer-Yahia, S.; Carlos Castillo | ||||
| Title | Tweet4act: Using incident-specific profiles for classifying crisis-related messages | Type | Conference Article | ||
| Year | 2013 | Publication | ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2013 |
| Volume | Issue | Pages | 834-839 | ||
| Keywords | Artificial intelligence; Disaster prevention; Classification methods; Crisis informatics; Disaster management; Micro-blogging platforms; Microblogging; Precision and recall; Standard machines; Twitter data-analytics; Information systems | ||||
| Abstract | We present Tweet4act, a system to detect and classify crisis-related messages communicated over a microblogging platform. Our system relies on extracting content features from each message. These features and the use of an incident-specific dictionary allow us to determine the period type of an incident that each message belongs to. The period types are: Pre-incident (messages talking about prevention, mitigation, and preparedness), during-incident (messages sent while the incident is taking place), and post-incident (messages related to the response, recovery, and reconstruction). We show that our detection method can effectively identify incident-related messages with high precision and recall, and that our incident-period classification method outperforms standard machine learning classification methods. | ||||
| Address | University of Trento, Italy; Fehler Textmarke Nicht Definiert, University of Trento, Italy; CNRS, LIG, France; QCRI, Doha, Qatar | ||||
| Corporate Author | Thesis | ||||
| Publisher | Karlsruher Institut fur Technologie | Place of Publication | KIT; Baden-Baden | Editor | T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9783923704804 | Medium | |
| Track | Social Media | Expedition | Conference | 10th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 396 | |||
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| Author |
Starr Roxanne Hiltz; Jane Kushma; Linda Plotnick | ||||
| Title | Use of Social Media by U.S. Public Sector Emergency Managers: Barriers and Wish Lists | Type | Conference Article | ||
| Year | 2014 | Publication | ISCRAM 2014 Conference Proceedings ? 11th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2014 |
| Volume | Issue | Pages | 602-611 | ||
| Keywords | Social media, emergency management, Twitter, Facebook | ||||
| Abstract | Semi-structured interviews were conducted with U.S. public sector emergency managers to probe barriers to use of social media and reactions to possible software enhancements to support such use. The three most frequently described barriers were lack of personnel time to work on use of social media, lack of policies and guidelines for its use, and concern about the trustworthiness of pulled data. The most popular of the possible technological enhancements described for Twitter are filtering by category of user/contributor, and display of posts on a GIS system with a map-based display. | ||||
| Address | NJIT, Newark NJ, United States; Jacksonville State U., AL, United States | ||||
| Corporate Author | Thesis | ||||
| Publisher | The Pennsylvania State University | Place of Publication | University Park, PA | Editor | S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9780692211946 | Medium | |
| Track | Social Media in Crisis Response and Management | Expedition | Conference | 11th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 1171 | |||
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| Author |
Sven Schaust; Maximilian Walther; Michael Kaisser | ||||
| Title | Avalanche: Prepare, manage, and understand crisis situations using social media analytics | Type | Conference Article | ||
| Year | 2013 | Publication | ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2013 |
| Volume | Issue | Pages | 852-857 | ||
| Keywords | Hardware; Crisis management; Event detection; Natural hazard; Social media analytics; Twitter; Information systems | ||||
| Abstract | The recent rise of Social Media services has created huge streams of information which can be very valuable in a variety of scenarios. One specific scenario that has received interest is how Social Media analytics can be beneficial in crisis situations. In this paper, we describe our vision for a Social Media-ready command and control center. As motivation for our work, we present a short analysis of tweets issued in NYC during Hurricane Sandy in late October 2012 and we give an overview of the architecture of our event detection subsystem. | ||||
| Address | AGT Group (R and D) GmbH, Germany | ||||
| Corporate Author | Thesis | ||||
| Publisher | Karlsruher Institut fur Technologie | Place of Publication | KIT; Baden-Baden | Editor | T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9783923704804 | Medium | |
| Track | Social Media | Expedition | Conference | 10th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 919 | |||
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| Author |
Takuya Oki | ||||
| Title | Possibility of Using Tweets to Detect Crowd Congestion: A Case Study Using Tweets just before/after the Great East Japan Earthquake | Type | Conference Article | ||
| Year | 2018 | Publication | ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2018 |
| Volume | Issue | Pages | 584-596 | ||
| Keywords | Twitter, crowd congestion, time-series analysis, linguistic expression, disaster mitigation. | ||||
| Abstract | During large earthquakes, it is critical to safely guide evacuation efforts and to prevent accidents caused by congestion. In this paper, we focus on detecting the degree of crowd congestion following an earthquake based on information posted to Social Networking Services (SNSs). This research uses text data posted to Twitter just before/after the occurrence of the Great East Japan Earthquake (11 March 2011 at 02:46 PM JST). First, we extract co-occurring place names, proper nouns, and time-series information from tweets about congestion in the Tokyo metropolitan area (TMA). Next, using these extracted data, we analyze the frequency and spatiotemporal characteristics of these tweets. Finally, we identify expressions that describe the degree of crowd congestion and discuss methods to quantify these expressions based on a questionnaire survey and tweets that contain a photograph. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Rochester Institute of Technology | Place of Publication | Rochester, NY (USA) | Editor | Kees Boersma; Brian Tomaszeski |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-0-692-12760-5 | Medium | |
| Track | Social Media Studies | Expedition | Conference | ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 2133 | |||
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| Author |
Teun Terpstra; Richard Stronkman; Arnout De Vries; Geerte L. Paradies | ||||
| Title | Towards a realtime Twitter analysis during crises for operational crisis management | Type | Conference Article | ||
| Year | 2012 | Publication | ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2012 |
| Volume | Issue | Pages | |||
| Keywords | Disaster prevention; Information filtering; Information retrieval; Information systems; Monitoring; Storms; Crisis communications; Crisis management; Graphical displays; Information extraction tools; Natural hazard; Self organizations; Social media; Twitter; Social networking (online) | ||||
| Abstract | Today's crises attract great attention on social media, from local and distant citizens as well as from news media. This study investigates the possibilities of real-time and automated analysis of Twitter messages during crises. The analysis was performed through application of an information extraction tool to nearly 97,000 tweets that were published shortly before, during and after a storm hit the Pukkelpop 2011 festival in Belgium. As soon as the storm hit the festival tweet activity increased exponentially, peaking at 576 tweets per minute. The extraction tool enabled analyzing tweets through predefined (geo)graphical displays, message content filters (damage, casualties) and tweet type filters (e.g., retweets). Important topics that emerged were 'early warning tweets', 'rumors' and the 'self-organization of disaster relief' on Twitter. Results indicate that automated filtering of information provides valuable information for operational response and crisis communication. Steps for further research are discussed. © 2012 ISCRAM. | ||||
| Address | HKV Consultants, Netherlands; Twitcident, Netherlands; TNO, Netherlands | ||||
| Corporate Author | Thesis | ||||
| Publisher | Simon Fraser University | Place of Publication | Vancouver, BC | Editor | L. Rothkrantz, J. Ristvej, Z.Franco |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9780864913326 | Medium | |
| Track | Social Media and Collaborative Systems | Expedition | Conference | 9th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 215 | |||
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