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Author | Adam Flizikowski, Marcin Przybyszewski; Anna Stachowicz; Tomasz Olejniczak; Rafael Renk | ||||
Title | Text Analysis Tool TWeet lOcator ? TAT2 | Type | Conference Article | ||
Year | 2015 | Publication | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2015 |
Volume | Issue | Pages | |||
Keywords | AIDA; Crisis Management; iSAR+; location of Twitter messages; social media | ||||
Abstract | Information about location and geographical coordinates in particular, may be very important during a crisis event, especially for search and rescue operations ? but currently geo-tagged tweets are extremely rare. Improved capabilities of capturing additional location from Twitter (up to 4 times improvement) are crucial for response efforts given a vast amount of messages exchanged during a crisis event. That is why authors have designed a tool (Text Analysis TWeet lOcator ? TAT2) that relies on existing open source text analysis tools with additional services to provide additional hints about people location. Validation process, complementing experimentation and test results, included involvement of end-users (i.e. Public Protection and Disaster Relief services and citizens during a realistic crisis exercise showcase. In addition, the integration of TAT2 with external tools has also been validated. | ||||
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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 | |
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Series Volume | Series Issue | Edition | |||
ISSN | 2411-3387 | ISBN | 9788271177881 | Medium | |
Track | Social Media Studies | Expedition | Conference | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | |
Notes | Approved | yes | |||
Call Number | Serial | 1227 | |||
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Author | Irina Temnikova; Carlos Castillo; Sarah Vieweg | ||||
Title | EMTerms 1.0: A Terminological Resource for Crisis Tweets | 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 | crises; Terminological resource; Twitter | ||||
Abstract | We present the first release of EMTerms (Emergency Management Terms), the largest crisis-related terminological resource to date, containing over 7,000 terms used in Twitter to describe various crises. This resource can be used by practitioners to search for relevant messages in Twitter during crises, and by computer scientists to develop new automatic methods for crises in Twitter. The terms have been collected from a seed set of terms manually annotated by a linguist and an emergency manager from tweets broadcast during 4 crisis events. A Conditional Random Fields (CRF) method was then applied to tweets from 35 crisis events, in order to expand the set of terms while overcoming the difficulty of getting more emergency managers? annotations. The terms are classified into 23 information-specific categories, by using a combination of expert annotations and crowdsourcing. This article presents the detailed terminology extraction methodology, as well as final results. |
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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 | 1229 | |||
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Author | Holger Fritze; Christian Kray | ||||
Title | Community and Governmental Responses to an Urban Flash Flood | 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 | community response; Facebook; information flow; social media; Twitter; urban flash flood | ||||
Abstract | In summer of 2014 the city of Münster experienced an urban flash flood not seen before with such intensity in Germany. This paper investigates the subsequent governmental and ad-hoc community response actions with a focus on the chronologies of Facebook and Twitter usage. Interviews identified drawbacks of coordinating volunteers in social media ecosystems. Possible solutions to overcome issues related to the interaction of community and official relief activities are identified. | ||||
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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 | 1231 | |||
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Author | Francesca Comunello; Simone Mulargia; Piero Polidoro; Emanuele Casarotti; Valentino Lauciani | ||||
Title | No Misunderstandings During Earthquakes: Elaborating and Testing a Standardized Tweet Structure for Automatic Earthquake Detection Information | Type | Conference Article | ||
Year | 2015 | Publication | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2015 |
Volume | Issue | Pages | |||
Keywords | Automatic detection; earthquakes; tweet comprehension; tweet syntax; Twitter | ||||
Abstract | Social media have proven to be useful resources for spreading verified information during natural disasters. Nevertheless, little attention has hitherto been devoted to the peculiarities of constructing effective tweets (and tweet formats), or to common users? comprehension of tweets conveying scientific information. In this paper, social scientists and seismologists collaborated in order to elaborate and test a standardized tweet structure to be used during earthquakes, expanding on the results of a quali-quantitative research project. The tweet format is specifically designed to launch an innovative information service by Istituto Nazionale di Geofisica e Vulcanologia (INGV): tweeting the automatic detection of earthquakes with a magnitude greater than 3. This paper illustrates the steps of the research process that led to elaborating a tweet format that will be used in the next few months by the official Twitter account @INGVterremoti. | ||||
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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 | |
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Series Volume | Series Issue | Edition | |||
ISSN | 2411-3387 | ISBN | 9788271177881 | Medium | |
Track | Social Media Studies | Expedition | Conference | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | |
Notes | Approved | yes | |||
Call Number | Serial | 1232 | |||
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Author | Yang Zhang; William Drake; Yuhong Li; Christopher Zobel; Margaret Cowell | ||||
Title | Fostering Community Resilience through Adaptive Learning in a Social Media Age: Municipal Twitter Use in New Jersey following Hurricane Sandy | 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 | Adaptive learning; disaster resilience; Hurricane Sandy; social media; Twitter | ||||
Abstract | Adaptive learning capacity is a critical component of community resilience that describes the ability of a community to effectively gauge its vulnerability to the external environment and to make appropriate changes to its coping strategies. Traditionally, the relationship between government and community learning was framed within a deterministic paradigm. Learning outcomes were understood to result from the activities of central actors (i.e., government) and flow passively into the community. The emergence of social media is fundamentally changing the ways organizations and individuals collect and share information. Despite its growing acceptance, it remains to be determined how this shift in communication will ultimately affect community adaptive learning, and therefore, community resilience. This paper presents the initial results of a mixed-methods research effort that examined the use of Twitter in local municipalities from Monmouth County, NJ after Hurricane Sandy. Using a conceptual model of organizational learning, we examine the learning outcomes following the Hurricane Sandy experience. | ||||
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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 | |
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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 | 1236 | |||
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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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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 | 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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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 | Antonin Segault; Federico Tajariol; Ioan Roxin | ||||
Title | #geiger : Radiation Monitoring Twitter Bots for Nuclear Post-Accident Situations | Type | Conference Article | ||
Year | 2015 | Publication | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2015 |
Volume | Issue | Pages | |||
Keywords | bots; long-term period; nuclear post-accident; radiations; Twitter | ||||
Abstract | In the last decade, people have increasingly relied on social media platforms such as Twitter to share information on the response to a natural or a man-made disaster. This paper focuses on the aftermath of the Fukushima Daiichi nuclear disaster. Since the disaster, victims and volunteers have been sharing relevant information about radiation measurements by means of social media. The aim of this research is to explore the diffusion of information produced and shared by Twitter bots, to understand the degree of popularity of these sources and to check if these bots deliver original radiation measurements. | ||||
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Publisher | University of Agder (UiA) | Place of Publication | Kristiansand, Norway | Editor | L. Palen; M. Buscher; T. Comes; A. Hughes |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 2411-3387 | ISBN | 9788271177881 | Medium | |
Track | Social Media Studies | Expedition | Conference | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | |
Notes | Approved | yes | |||
Call Number | Serial | 1239 | |||
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Author | 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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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 | Jennings Anderson; Marina Kogan; Melissa Bica; Leysia Palen; Kenneth Anderson; Rebecca Morss; Julie Demuth; Heather Lazrus; Olga Wilhelmi | ||||
Title | Far Far Away in Far Rockaway: Responses to Risks and Impacts during Hurricane Sandy through First-Person Social Media Narratives | 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 | Crisis Informatics; Hurricane Sandy; Protective Decision Making; Risk Perception; Social Media; Twitter | ||||
Abstract | When Hurricane Sandy swept over the US eastern seaboard in October 2012, it was the most tweeted about event at the time. However, some of the most affected areas were underrepresented in the social media conversation about Sandy. Here, we examine the hurricane-related experiences and behaviors shared on Twitter by residents of Far Rockaway, a New York City neighborhood that is geographically and socioeconomically vulnerable to disasters, which was significantly affected by the storm. By carefully filtering the vast Twitter data, we focus on 41 Far Rockaway residents who offer rich personal accounts of their experience with Sandy. Analyzing their first-person narratives, we see risk perception and protective decision-making behavior in their data. We also find themes of invisibility and neglect when residents expressed feeling abandoned by the media, the city government, and the overall relief efforts in the aftermath of Sandy. | ||||
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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 | Social Media Studies | Expedition | Conference | 13th International Conference on Information Systems for Crisis Response and Management | |
Notes | Approved | no | |||
Call Number | ISCRAM @ idladmin @ | Serial | 1388 | ||
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Author | Venkata Kishore Neppalli; Murilo Cerqueira Medeiros; Cornelia Caragea; Doina Caragea; Andrea Tapia; Shane Halse | ||||
Title | Retweetability Analysis and Prediction during Hurricane Sandy | 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; Retweetability Analysis; Retweetability Prediction; Hurricane Sandy; Disaster Events | ||||
Abstract | Twitter is a very important source for obtaining information, especially during events such as natural disasters. Users can spread information in Twitter either by crafting new posts, which are called ?tweets,? or by using retweet mechanism to re-post the previously created tweets. During natural disasters, identifying how likely a tweet is to be highly retweeted is very important since it can help promote the spread of good information in a network such as Twitter, as well as it can help stop the spread of misinformation, when corroborated with approaches that identify trustworthy information or misinformation, respectively. In this paper, we present an analysis on retweeted tweets to determine several aspects affecting retweetability. We then extract features from tweets? content and user account information and perform experiments to develop models that automatically predict the retweetability of a tweet in the context of the Hurricane Sandy. | ||||
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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 | Social Media Studies | Expedition | Conference | 13th International Conference on Information Systems for Crisis Response and Management | |
Notes | Approved | no | |||
Call Number | Serial | 1389 | |||
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Author | Elodie Fichet; John Robinson; Dharma Dailey; Kate Starbird | ||||
Title | Eyes on the Ground: Emerging Practices in Periscope Use during Crisis Events | Type | Conference Article | ||
Year | 2016 | Publication | ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2016 |
Volume | Issue | Pages | |||
Keywords | Social Media; Periscope; Twitter; Crisis Informatics; Emergency Management | ||||
Abstract | This empirical analysis examines the use of the live-streaming application Periscope in three crises that occurred in 2015. Qualitative analyses of tweets relating to the Amtrak derailment in Philadelphia, Baltimore protests after Freddie Grey?s death, and Hurricane Joaquin flooding in South Carolina reveal that this recently deployed application is being used by both citizens and journalists for information sharing, crisis coverage and commentary. The accessibility and immediacy of live video directly from crisis situations, and the embedded chats which overlay on top of a video feed, extend the possibilities of real-time interaction between remote crowds and those on the ground in a crisis. These empirical findings suggest several potential challenges and opportunities for responders. | ||||
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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 | Social Media Studies | Expedition | Conference | 13th International Conference on Information Systems for Crisis Response and Management | |
Notes | Approved | no | |||
Call Number | ISCRAM @ idladmin @ | Serial | 1391 | ||
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Author | Antonin Segault; Federico Tajariol; Yang Ishigaki; Ioan Roxin | ||||
Title | #geiger 2: Developing Guidelines for Radiation Measurements Sharing on Social Media | Type | Conference Article | ||
Year | 2016 | Publication | ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2016 |
Volume | Issue | Pages | |||
Keywords | Twitter; Nuclear Post-Accident; Radiation; Robots; Syntax | ||||
Abstract | Radiation measurements are key information in post-nuclear accident situations. Automated Twitter accounts have been used to share the readings, but often in an incomplete way from the perspective of data sharing and risk communication between citizen and radiation experts. In this paper, we investigate the requirements for radiation measurements completeness, by analyzing the perceived usefulness of several metadata items that may go along the measurement itself. We carried out a benchmark of existing uses, and conducted a survey with both experts and lay citizens. We thus produced a set of guidelines regarding the metadata that should be used, and the way to publish it. | ||||
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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 | Social Media Studies | Expedition | Conference | 13th International Conference on Information Systems for Crisis Response and Management | |
Notes | Approved | no | |||
Call Number | Serial | 1394 | |||
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Author | 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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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 | |
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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 | Federico Angaramo; Claudio Rossi | ||||
Title | Online clustering and classification for real-time event detection in Twitter | Type | Conference Article | ||
Year | 2018 | Publication | ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2018 |
Volume | Issue | Pages | 1098-1107 | ||
Keywords | Event detection, Social Media, Clustering, Machine Learning, Twitter | ||||
Abstract | Event detection from social media is a challenging task due to the volume, the velocity and the variety of user-generated data requiring real-time processing. Despite recent works on this subject, a generalized and scalable approach that could be applied across languages and topics has not been consolidated, yet. In this paper, we propose a methodology for real-time event detection from Twitter data that allows users to select a topic of interest by defining a simple set of keywords and a matching rule. We implement the proposed methodology and evaluate it with real data to detect different types of events. | ||||
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Publisher | Rochester Institute of Technology | Place of Publication | Rochester, NY (USA) | Editor | Kees Boersma; Brian Tomaszeski |
Language | English | Summary Language | English | Original Title | |
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Series Volume | Series Issue | Edition | |||
ISSN | 2411-3387 | ISBN | 978-0-692-12760-5 | Medium | |
Track | 1st International Workshop on Intelligent Crisis Management Technologies for Climate Events (ICMT) | Expedition | Conference | ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management | |
Notes | Approved | no | |||
Call Number | Serial | 2182 | |||
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Author | 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. | ||||
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Publisher | Rochester Institute of Technology | Place of Publication | Rochester, NY (USA) | Editor | Kees Boersma; Brian Tomaszeski |
Language | English | Summary Language | English | Original Title | |
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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 | Diana Fischer; Carsten Schwemmer; Kai Fischbach | ||||
Title | Terror Management and Twitter: The Case of the 2016 Berlin Terrorist Attack | Type | Conference Article | ||
Year | 2018 | Publication | ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2018 |
Volume | Issue | Pages | 459-468 | ||
Keywords | Terrorist attacks, social networking sites, social media, Twitter, topic modeling, terror management, sense-making | ||||
Abstract | There is evidence that people increasingly use social networking sites like Twitter in the aftermath of terrorist attacks to make sense of the events at the collective level. This work-in-progress paper focuses on the content of Twitter messages related to the 2016 terrorist attack on the Berlin Christmas market. We chose topic modeling to investigate the Twitter data and the terror management theory perspective to understand why people used Twitter in the aftermath of the attack. In particular, by connecting people and providing a real-time communication channel, Twitter helps its users collectively negotiate their worldviews and re-establish self-esteem. We provide first results and discuss next steps. | ||||
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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 | 2123 | |||
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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 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. | ||||
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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 | 2128 | |||
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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. | ||||
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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 | 2133 | |||
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Author | Leon Derczynski; Kenny Meesters; Kalina Bontcheva; Diana Maynard | ||||
Title | Helping Crisis Responders Find the Informative Needle in the Tweet Haystack | 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 | 649-662 | ||
Keywords | informativeness, twitter, social media, actionability, information filtering | ||||
Abstract | Crisis responders are increasingly using social media, data and other digital sources of information to build a situational understanding of a crisis situation in order to design an effective response. However with the increased availability of such data, the challenge of identifying relevant information from it also increases. This paper presents a successful automatic approach to handling this problem. Messages are filtered for informativeness based on a definition of the concept drawn from prior research and crisis response experts. Informative messages are tagged for actionable data – for example, people in need, threats to rescue efforts, changes in environment, and so on. In all, eight categories of actionability are identified. The two components – informativeness and actionability classification – are packaged together as an openly-available tool called Emina (Emergent Informativeness and Actionability). | ||||
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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 | 2139 | |||
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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. | ||||
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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 | 2145 | |||
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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 | 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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