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	Author	Dario Salza; Edoardo Arnaudo; Giacomo Blanco; Claudio Rossi
	Title	A 'Glocal' Approach for Real-time Emergency Event Detection in Twitter			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	570-583
	Keywords	Emergency; Event Detection; Social Media; Twitter; Incremental Clustering
	Abstract	Social media like Twitter offer not only an unprecedented amount of user-generated content covering developing emergencies but also act as a collector of news produced by heterogeneous sources, including big and small media companies as well as public authorities. However, this volume, velocity, and variety of data constitute the main value and, at the same time, the key challenge to implement and automatic detection and tracking of independent emergency events from the real-time stream of tweets. Leveraging online clustering and considering both textual and geographical features, we propose, implement, and evaluate an algorithm to automatically detect emergency events applying a ‘glocal’ approach, i.e., offering a global coverage while detecting events at local (municipality level) scale.
	Address	LINKS Foundation; LINKS Foundation; LINKS Foundation; LINKS Foundation
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Social Media for Crisis Management	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2440
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	Author	Cody Buntain; Richard Mccreadie; Ian Soboroff
	Title	Incident Streams 2021 Off the Deep End: Deeper Annotations and Evaluations in Twitter			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	584-604
	Keywords	Emergency Management; Crisis Informatics; Twitter; Categorization; Priorization; Multi-Modal; Public Safety; PSCR; TREC
	Abstract	This paper summarizes the final year of the four-year Text REtrieval Conference Incident Streams track (TREC-IS), which has produced a large dataset comprising 136,263 annotated tweets, spanning 98 crisis events. Goals of this final year were twofold: 1) to add new categories for assessing messages, with a focus on characterizing the audience, author, and images associated with these messages, and 2) to enlarge the TREC-IS dataset with new events, with an emphasis of deeper pools for sampling. Beyond these two goals, TREC-IS has nearly doubled the number of annotated messages per event for the 26 crises introduced in 2021 and has released a new parallel dataset of 312,546 images associated with crisis content – with 7,297 tweets having annotations about their embedded images. Our analyses of this new crisis data yields new insights about the context of a tweet; e.g., messages intended for a local audience and those that contain images of weather forecasts and infographics have higher than average assessments of priority but are relatively rare. Tweets containing images, however, have higher perceived priorities than tweets without images. Moving to deeper pools, while tending to lower classification performance, also does not generally impact performance rankings or alter distributions of information-types. We end this paper with a discussion of these datasets, analyses, their implications, and how they contribute both new data and insights to the broader crisis informatics community.
	Address	University of Maryland, College Park (UMD); University of Glasgow; National Institute of Standards and Technology (NIST)
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Social Media for Crisis Management	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2441
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	Author	Gaëtan Caillaut; Cécile Gracianne; Nathalie Abadie; Guillaume Touya; Samuel Auclair
	Title	Automated Construction of a French Entity Linking Dataset to Geolocate Social Network Posts in the Context of Natural Disasters			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	654-663
	Keywords	Automated geotagging; French Entity Linking; Wikipedia; Twitter; Crisis Management; Natural Disaster
	Abstract	During natural disasters, automatic information extraction from Twitter posts is a valuable way to get a better overview of the field situation. This information has to be geolocated to support effective actions, but for the vast majority of tweets, spatial information has to be extracted from texts content. Despite the remarkable advances of the Natural Language Processing field, this task is still challenging for current state-of-the-art models because they are not necessarily trained on Twitter data and because high quality annotated data are still lacking for low resources languages. This research in progress address this gap describing an analytic pipeline able to automatically extract geolocatable entities from texts and to annotate them by aligning them with the entities present in Wikipedia/Wikidata resources. We present a new dataset for Entity Linking on French texts as preliminary results, and discuss research perspectives for enhancements over current state-of-the-art modeling for this task.
	Address	BRGM; BRGM; LASTIG, Univ Gustave Eiffel, IGN-ENSG; LASTIG, Univ Gustave Eiffel, IGN-ENSG; BRGM
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Social Media for Crisis Management	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2445
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	Author	Jens Kersten; Jan Bongard; Friederike Klan
	Title	Gaussian Processes for One-class and Binary Classification of Crisis-related Tweets			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	664-673
	Keywords	Gaussian Process; One-class Classification; Twitter; Overload Reduction; Crisis Informatics
	Abstract	Overload reduction is essential to exploit Twitter text data for crisis management. Often used pre-trained machine learning models require training data for both, crisis-related and off-topic content. However, this task can also be formulated as a one-class classification problem in which labeled off-topic samples are not required. Gaussian processes (GPs) have great potential in both, binary and one-class settings and are therefore investigated in this work. Deep kernel learning combines the representative power of text embeddings with the Bayesian formalism of GPs. Motivated by this, we investigate the potential of deep kernel models for the task of classifying crisis-related tweet texts with special emphasis on cross-event applications. Compared to standard binary neural networks, first experiments with one-class GP models reveal a great potential for realistic scenarios, offering a fast and flexible approach for interactive model training without requiring off-topic training samples and comprehensive expert knowledge (only two model parameters involved).
	Address	German Aerospace Center– Jena, Germany; German Aerospace Center– Jena, Germany; German Aerospace Center– Jena, Germany
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Social Media for Crisis Management	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2446
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	Author	Ahmed Alnuhayt; Suvodeep Mazumdar; Vitaveska Lanfranchi; Frank Hopfgartner
	Title	Understanding Reactions to Misinformation – A Covid-19 Perspective			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	687-700
	Keywords	Misinformation; social reactions; twitter; people; COVID-19
	Abstract	The increasing use of social media as an information source brings further challenges – social media platforms can be an excellent medium for disseminating public awareness and critical information, that can be shared across large populations. However, misinformation in social media can have immense implications on public health, risking the effectiveness of health interventions as well as lives. This has been particularly true in the case of COVID-19 pandemic, with a range of misinformation, conspiracy theories and propaganda being spread across social channels. In our study, through a questionnaire survey, we set out to understand how members of the public interact with different sources when looking for information on COVID-19. We explored how participants react when they encounter information they believe to be misinformation. Through a set of three behaviour tasks, synthetic misinformation posts were provided to the participants who chose how they would react to them. In this work in progress study, we present initial findings and insights into our analysis of the data collected. We highlight what are the most common reactions to misinformation and also how these reactions are different based on the type of misinformation.
	Address	Information School University of Sheffield; Information School University of Sheffield; Computer Science University of Sheffield; Information School University of Sheffield
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Social Media for Crisis Management	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2448
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	Author	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	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	Chauhan, A.
	Title	Humor-Based COVID-19 Twitter Accounts			Type	Conference Article
	Year	2023	Publication	Proceedings of the 20th International ISCRAM Conference	Abbreviated Journal	Iscram 2023
	Volume		Issue		Pages	417-427
	Keywords	COVID-19; Twitter; Humor; Crisis Named Resources
	Abstract	Crisis Named Resources (or CNRs) are social media pages and accounts named after a crisis event. Using the COVID-19 Pandemic as a case study, we identified and examined the role of CNRs that shared humor on Twitter. Our analyses showed that humor-based CNRs shared virus-related rumors, stigma, safety measures, opinions, sarcasm, and news updates. These resources also shared the overall anger and frustration over the year 2020. We conclude by discussing the critical role of humor based CNRs in crisis response.
	Address	Concordia University of Edmonton
	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/YHDI4576			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2536
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	Author	Anjum, U.; Zadorozhny, V.; Krishnamurthy, P.
	Title	Localization of Events Using Neural Networks in Twitter Data			Type	Conference Article
	Year	2023	Publication	Proceedings of the 20th International ISCRAM Conference	Abbreviated Journal	Iscram 2023
	Volume		Issue		Pages	909-919
	Keywords	Social Networking; Event Localization; Twitter; Neural Networks; GAN, BiLSTM
	Abstract	In this paper, we develop a model with neural networks to localize events using microblogging data. Localization is the task of finding the location of an event and can be done by discovering event signatures in microblogging data. We use the deep learning methodology of Bi-directional Long Short-Term Memory (Bi-LSTM) to learn event signatures. We propose a methodology for labeling the Twitter date for use in Bi-LSTM However, there might not be enough data available to train the Bi-LSTM and learn the event signatures. Hence, the data is augmented using generative adversarial networks (GAN). Finally, we combine event signatures at different temporal and spatial granularity to improve the accuracy of event localization. We use microblogging data collected from Twitter to evaluate our model and compare it with other baseline methods.
	Address	Tokyo Institute of Technology
	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	AI for Crisis Management	Expedition		Conference
	Notes	http://dx.doi.org/10.59297/UVZV1884			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2575
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	Author	Kartikeya Bajpai; Anuj Jaiswal
	Title	A framework for analyzing collective action events on Twitter			Type	Conference Article
	Year	2011	Publication	8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011	Abbreviated Journal	ISCRAM 2011
	Volume		Issue		Pages
	Keywords	Information systems; Collective action; Content and structure; Government censorships; Micro-blogging platforms; Research goals; Social movements; Thailand; Twitter; Social networking (online)
	Abstract	Recent years have witnessed multiple international protest movements which have purportedly been greatly affected by the use of Twitter, a micro-blogging platform. Social movement actors in Iran, Moldova, Kyrgyzstan and Thailand are thought to have utilized Twitter to spread information, co-ordinate protest activities, evade government censorship and, in some cases, to spread misinformation. We propose a framework for conceptualizing and analyzing Twitter data related to contentious collective action crises. Our primary research goal is to delineate a framework informed with a social movements lens and to demonstrate the framework by means of Twitter usage data related to the Thailand protests of 2010. Our proposed framework concerns itself with two aspects of protest activities and Twitter usage, namely, analyzing the content and structure of messages and our construct of Twitter protest waves.
	Address	Pennsylvania State University, United States
	Corporate Author				Thesis
	Publisher	Information Systems for Crisis Response and Management, ISCRAM	Place of Publication	Lisbon	Editor	M.A. Santos, L. Sousa, E. Portela
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	9789724922478	Medium
	Track	Social Media and Collaborative Systems	Expedition		Conference	8th International ISCRAM Conference on Information Systems for Crisis Response and Management
	Notes				Approved	no
	Call Number				Serial	283
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	Author	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. Â© 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	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. Â© 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	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. Â© 2012 ISCRAM.
	Address	HKV Consultants, Netherlands; Twitcident, Netherlands; TNO, Netherlands
	Corporate Author				Thesis
	Publisher	Simon Fraser University	Place of Publication	Vancouver, BC	Editor	L. Rothkrantz, J. Ristvej, Z.Franco
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	9780864913326	Medium
	Track	Social Media and Collaborative Systems	Expedition		Conference	9th International ISCRAM Conference on Information Systems for Crisis Response and Management
	Notes				Approved	no
	Call Number				Serial	215
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	Author	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. Â© 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	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. Â© 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	Justine I. Blanford; Jase Bernhardt; Alexander Savelyev; Gabrielle Wong-Parodi; Andrew M. Carleton; David W. Titley; Alan M. MacEachren
	Title	Tweeting and tornadoes			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	319-323
	Keywords	Geographic information systems; Information systems; Social networking (online); Tornadoes; Emergency response; Message warnings and alerts; Risk communication; Situational awareness; Twitter; Emergency services
	Abstract	Social Media and micro-blogging is being used during crisis events to provide live up-to-date information as events evolve (before, during and after). Messages are posted by citizens or public officials. To understand the effectiveness of these messages, we examined the content of geo-located Twitter messages (“tweets”) sent during the Moore, Oklahoma tornado of May 20th, 2013 (+/-1day) to explore the spatial and temporal relationships of real-time reactions of the general public. We found a clear transition of topics during each stage of the tornado event. Twitter was useful for posting and retrieving updates, reconstructing the sequence of events as well as capturing people's reactions leading up to, during and after the tornado. A long-term goal for the research reported here is to provide insights to forecasters and emergency response personnel concerning the impact of warnings and other advisory messages.
	Address	GeoVISTA Center, Pennsylvania State University, United States; Geography Dept, Pennsylvania State University, United States; Dept of Engineering and Public Policy, Carnegie-Mellon University, United States; Center for Solutions to Weather and Climate Risk, Pennsylvania State University, United States
	Corporate Author				Thesis
	Publisher	The Pennsylvania State University	Place of Publication	University Park, PA	Editor	S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih.
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	9780692211946	Medium
	Track	Geographic Information Science	Expedition		Conference	11th International ISCRAM Conference on Information Systems for Crisis Response and Management
	Notes				Approved	no
	Call Number				Serial	328
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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	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	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	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	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	Kenneth Joseph; Peter M. Landwehr; Kathleen M. Carley
	Title	An approach to selecting keywords to track on twitter during a disaster			Type	Conference Article
	Year	2014	Publication	ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	ISCRAM 2014
	Volume		Issue		Pages	672-676
	Keywords	Data mining; Disasters; Information systems; Keyword searching; Novel methodology; Situational awareness; Social media; Twitter; Social networking (online)
	Abstract	Several studies on Twitter usage during disasters analyze tweets collected using ad-hoc keywords pre-defined by researchers. While recent efforts have worked to improve this methodology, open questions remain about which keywords can be used to uncover tweets contributing to situational awareness (SA) and the quality of tweets returned using different terms. Herein we consider a novel methodology for uncovering relevant keywords one can use to search for tweets containing situational awareness. We provide a description of the methodology and initial results which suggest our approach may lead to better keywords to use for keyword searching during disasters.
	Address	Carnegie Mellon University, United States
	Corporate Author				Thesis
	Publisher	The Pennsylvania State University	Place of Publication	University Park, PA	Editor	S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih.
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	9780692211946	Medium
	Track	Social Media in Crisis Response and Management	Expedition		Conference	11th International ISCRAM Conference on Information Systems for Crisis Response and Management
	Notes				Approved	no
	Call Number				Serial	640
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	Author	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	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	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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