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| Author | Muhammad Imran; Prasenjit Mitra; Jaideep Srivastava | ||||
| Title | Cross-Language Domain Adaptation for Classifying Crisis-Related Short Messages | 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  |
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| Keywords | Social Media; Tweets Classification; Domain Adaptation | ||||
| Abstract | Rapid crisis response requires real-time analysis of messages. After a disaster happens, volunteers attempt to classify tweets to determine needs, e.g., supplies, infrastructure damage, etc. Given labeled data, supervised machine learning can help classify these messages. Scarcity of labeled data causes poor performance in machine training. Can we reuse old tweets to train classifiers? How can we choose labeled tweets for training? Specifically, we study the usefulness of labeled data of past events. Do labeled tweets in different language help? We observe the performance of our classifiers trained using different combinations of training sets obtained from past disasters. We perform extensive experimentation on real crisis datasets and show that the past labels are useful when both source and target events are of the same type (e.g. both earthquakes). For similar languages (e.g., Italian and Spanish), cross-language domain adaptation was useful, however, when for different languages (e.g., Italian and English), the performance decreased. | ||||
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| Corporate Author | Thesis | ||||
| Publisher | Federal University of Rio de Janeiro | Place of Publication | Rio de Janeiro, Brasil | Editor | A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3388 | ISBN | 978-84-608-7984-9 | Medium | |
| Track | Social Media Studies | Expedition | Conference | 13th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 1396 | |||
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| Author | Cornelia Caragea; Adrian Silvescu; Andrea Tapia | ||||
| Title | Identifying Informative Messages in Disasters using Convolutional Neural Networks | 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 |
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| Keywords | Informative Tweets Classification; Disaster Events; Convolutional Neural Networks | ||||
| Abstract | Social media is a vital source of information during any major event, especially natural disasters. Data produced through social networking sites is seen as ubiquitous, rapid and accessible, and it is believed to empower average citizens to become more situationally aware during disasters and coordinate to help themselves. However, with the exponential increase in the volume of social media data, so comes the increase in data that are irrelevant to a disaster, thus, diminishing peoples? ability to find the information that they need in order to organize relief efforts, find help, and potentially save lives. In this paper, we present an approach to identifying informative messages in social media streams during disaster events. Our approach is based on Convolutional Neural Networks and shows significant improvement in performance over models that use the ?bag of words? and n-grams as features on several datasets of messages from flooding events. | ||||
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| Corporate Author | Thesis | ||||
| Publisher | Federal University of Rio de Janeiro | Place of Publication | Rio de Janeiro, Brasil | Editor | A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3388 | ISBN | 978-84-608-7984-9 | Medium | |
| Track | Social Media Studies | Expedition | Conference | 13th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 1397 | |||
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| Author | Emma Potter | ||||
| Title | Balancing conflicting operational and communications priorities: social media use in an emergency management organization | 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 |
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| Keywords | Emergency Management; Social Media; Internal Communication; Disasters; Ethnography | ||||
| Abstract | Social media are now widely used by affected members of the public during an emergency. As these platforms have become mainstream, governments have responded to the public?s expectation that information is available online, particularly during disasters. Emergency management organizations (EMOs) now widely use social media to communicate with the public alongside occasional intelligence gathering. While EMOs increasingly use social media, breakdowns in internal communication can inhibit the dissemination of timely information to their online followers. Drawing on a two-year ethnography at the Queensland Fire and Emergency Services (QFES), an Australian EMO, this paper outlines how the organization uses social media to disseminate information during emergencies and identifies the internal tensions around its use. These tensions include the prioritization of operational duties over public information responsibilities, and the difficulties around requesting and receiving information from operational personnel located on the ground. | ||||
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| Corporate Author | Thesis | ||||
| Publisher | Federal University of Rio de Janeiro | Place of Publication | Rio de Janeiro, Brasil | Editor | A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3388 | ISBN | 978-84-608-7984-9 | Medium | |
| Track | Social Media Studies | Expedition | Conference | 13th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 1398 | |||
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| Author | Louis Ngamassi; Thiagarajan Ramakrishnan; Shahedur Rahman | ||||
| Title | Examining the Role of Social Media in Disaster Management from an Attribution Theory Perspective | 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 |
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| Keywords | Attribution Theory; Social Media; Disaster Management; Disaster Management Phases | ||||
| Abstract | This paper is related to the use of social media for disaster management by humanitarian organizations. The past decade has seen a significant increase in the use of social media to manage humanitarian disasters. It seems, however, that it has still not been used to its full potential. In this paper, we examine the use of social media in disaster management through the lens of Attribution Theory. Attribution Theory posits that people look for the causes of events, especially unexpected and negative events. The two major characteristics of disasters are that they are unexpected and have negative outcomes/impacts. Thus, Attribution Theory may be a good fit for explaining social media adoption patterns by emergency managers. We propose a model, based on Attribution Theory, which is designed to understand the use of social media during the mitigation and preparedness phases of disaster management. We also discuss the theoretical contributions and some practical implications. This study is still in its nascent stage and is research in progress. | ||||
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| Corporate Author | Thesis | ||||
| Publisher | Federal University of Rio de Janeiro | Place of Publication | Rio de Janeiro, Brasil | Editor | A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3388 | ISBN | 978-84-608-7984-9 | Medium | |
| Track | Social Media Studies | Expedition | Conference | 13th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 1399 | |||
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| Author | Briony Jennifer Gray | ||||
| Title | Social Media and Disasters: A New Conceptual Framework | 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 |
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| Keywords | Social Media; Conceptual Framework; Disaster Management; Web Accessibility; Information Reliability | ||||
| Abstract | Conceptual frameworks which seek to integrate social media uses into disaster management strategies are employed in a range of events. With continued variations to social media practices, developments in technology, and changes in online behaviors, it is imperative to provide conceptual frameworks which are relevant, current and insightful. This paper conceptualizes a range of recent literature through an inductive methodology, and presents the themes of Web accessibility and online information reliability as broad and emerging considerations for the identification of social media uses during disasters. It presents a new conceptual framework of current social media uses which may be used to supplement existing frameworks. The framework has been applied to a dataset of Tweets from the 2015 Nepal earthquake to demonstrate its validity. Suggestions for future applications are discussed. | ||||
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| Corporate Author | Thesis | ||||
| Publisher | Federal University of Rio de Janeiro | Place of Publication | Rio de Janeiro, Brasil | Editor | A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3388 | ISBN | 978-84-608-7984-9 | Medium | |
| Track | Social Media Studies | Expedition | Conference | 13th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 1400 | |||
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| Author | Daniel Link; Bernd Hellingrath; Jie Ling | ||||
| Title | A Human-is-the-Loop Approach for Semi-Automated Content Moderation | Type | Conference Article | ||
| Year | 2016 | Publication | ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2016 |
| Volume | Issue | Pages |
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| Keywords | Disaster Management; Social Media Analysis; Human-Is-The-Loop; Content Moderation; Supervised Machine Learning | ||||
| Abstract | Online social media has been recognized as a valuable information source for disaster management whose volume, velocity and variety exceed manual processing capacity. Current machine learning systems that support the processing of such data generally follow a human-in-the-loop approach, which has several inherent limitations. This work applies the human-is-the-loop concept from visual analytics to semi-automate a manual content moderation workflow, wherein human moderators take the dominant role. The workflow is instantiated with a supervised machine learning system that supports moderators with suggestions regarding the relevance and categorization of content. The instantiated workflow has been evaluated using in-depth interviews with practitioners and serious games. which suggest that it offers good compatibility with work practices in humanitarian assessment as well as improved moderation quality and higher flexibility than common approaches. | ||||
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| Corporate Author | Thesis | ||||
| Publisher | Federal University of Rio de Janeiro | Place of Publication | Rio de Janeiro, Brasil | Editor | A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3388 | ISBN | 978-84-608-7984-9 | Medium | |
| Track | Social Media Studies | Expedition | Conference | 13th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 1401 | |||
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| Author | Jidi Zhao; Linlin Wang | ||||
| Title | Research on Public Opinion Propagation in Micro-Blogging Based on Epidemic Models | 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 |
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| Keywords | Mb-RP Model; Micro-Blogging; Public Opinion; Propagation Rules | ||||
| Abstract | Micro-blogging has become an important communication channel for public opinion topics with its own characteristics such as openness, timeliness and interactive and so on. Studying the propagation rules for public opinion topics in micro-blogging is important to monitor and understand Micro-blogging public opinion. In this paper, we study the spreading process of public opinion in micro-blogging, identify key elements in the process and propose an Mb-RP (Micro-blogging Read-Post) propagation model based on the traditional SIR (Susceptible- Infective-Recovered) epidemic model. Through statistical analysis of a case on Sina Weibo, we assign values to parameters in the model and conduct simulations. Simulation results show that the model established in this paper can well fit real data. Further study of the model indicates that, compared with the attention cycle and the average amount of readings per post, the forwarding rate has the most influence on Micro-blogging information propagation. | ||||
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| Corporate Author | Thesis | ||||
| Publisher | Federal University of Rio de Janeiro | Place of Publication | Rio de Janeiro, Brasil | Editor | A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3388 | ISBN | 978-84-608-7984-9 | Medium | |
| Track | Social Media Studies | Expedition | Conference | 13th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 1402 | |||
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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 |
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| Keywords | Twitter; Sandy; Hurricane; Boston Bombing; Trust; Usefulness | ||||
| Abstract | To this date, research on crisis informatics has focused on the detection of trust in Twitter data through the use of message structure, sentiment, propagation and author. Little research has examined the usefulness of these messages in the crisis response domain. Toward detecting useful messages in case of crisis, in this paper, we characterize tweets, which are perceived useful or trustworthy, and determine their main features. Our analysis is carried out on two datasets (one natural and one man made) gathered from Twitter concerning hurricane Sandy in 2012 and the Boston Bombing 2013. The results indicate that there is a high correlation and similar factors (support for the victims, informational data, use of humor and type of emotion used) influencing trustworthiness and usefulness for both disaster types. This could have impacts on how messages from social media data are analyzed for use in crisis response. | ||||
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| Corporate Author | Thesis | ||||
| Publisher | Federal University of Rio de Janeiro | Place of Publication | Rio de Janeiro, Brasil | Editor | A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3388 | ISBN | 978-84-608-7984-9 | Medium | |
| Track | Social Media Studies | Expedition | Conference | 13th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 1403 | |||
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| Author | Guoqin Ma; Chittayong Surakitbanharn | ||||
| Title | Predicting Hurricane Damage Using Social Media Posts Coupled with Physical and Socio-Economic Variables | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages |
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| Keywords | Social media, disaster management, damage prediction | ||||
| Abstract | During a natural disaster or emergency event, individual social media posts or hot spots may not necessarily correlate to the most devastated areas. To better understand the correlation between social media and physical damage, we compare Tweets, data about the physical environment, and socio-economic factors with insurance claim information (as a proxy for physical damage) from 2017 Hurricane Irma in the state of Florida. We use machine learning to identify relevant Tweets, sensitivity analyses to identify socio-economic factors, and statistical regression to determine the predictive capability of insurance claims as a proxy for damage. We find that Tweets alone result in a poorly fitted regression model of insurance claims, but the inclusion of physical features (e.g., power outages, wind level) and socio-economic factors (e.g., population density, education, Internet access) improves the model?s fit. Such models contribute to the knowledge base that may allow social media to predict damage in real-time. |
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| Address | Stanford University, United States of America | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1955 | |||
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| Author | Marion Lara Tan; Raj Prasanna; Kristin Stock; Emma Hudson-Doyle; Graham Leonard; David Johnston | ||||
| Title | Enhancing the usability of a disaster app: exploring the perspective of the public as users | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages |
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| Keywords | usability inquiry, mobile application, disasters, alerts, public perspective | ||||
| Abstract | Limited research has studied how citizens? perspectives as end-users can contribute to improving the usability of disaster apps. This study addresses this gap by exploring end-user insights with the use of a conceptual disaster app in the New Zealand (NZ) context. NZ has multiple public alerting authorities that have various technological options in delivering information to the population?s mobile devices; including social media platforms, apps, as well as the Emergency Mobile Alert system. However, during critical events, the multiplicity of information may become overwhelming. A disaster app, conceptualised in the NZ context, aims to aggregate, organise, and deliver information from official sources to the public. After the initial conceptual design, a usability inquiry was administered by interviewing members of the public. Partial results of the inquiry show that the public?s perspective has value; in the process of understanding the new user?s viewpoint, usability highlights and issues are identified. | ||||
| Address | Massey University, New Zealand;GNS Science, New Zealand | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | ISCRAM @ idladmin @ | Serial | 1946 | ||
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| Author | Thomas Spielhofer; Anna Sophie Hahne; Christian Reuter; Marc-André Kaufhold; Stefka Schmid | ||||
| Title | Social Media Use in Emergencies of Citizens in the United Kingdom | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages |
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| Keywords | Emergencies; social media; Twitter; Facebook; representative study | ||||
| Abstract | People use social media in various ways including looking for or sharing information during crises or emergencies (e.g. floods, storms, terrorist attacks). Few studies have focused on European citizens? perceptions, and just one has deployed a representative sample to examine this. This article presents the results of one of the first representative studies on this topic conducted in the United Kingdom. The study shows that around a third (34%) have used social media during an emergency and that such use is more widespread among younger people. In contrast, the main reasons for not using social media in an emergency include technological concerns and that the trustworthiness of social media content is doubtful. However, there is a growing trend towards increased use. The article deduces and explores implications of these findings, including problems potentially arising with more citizens sharing information on social media during emergencies and expecting a response. |
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| Address | Technische Universität Darmstadt, Science and Technology for Peace and Security (PEASEC), Germany;The Tavistock Institute of Human Relations (TIHR) | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1849 | |||
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| Author | Xukun Li; Doina Caragea; Cornelia Caragea; Muhammad Imran; Ferda Ofli | ||||
| Title | Identifying Disaster Damage Images Using a Domain Adaptation Approach | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages |
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| Keywords | image classification, disaster damage, domain adaptation, domain adversarial neural networks. | ||||
| Abstract | Approaches for effectively filtering useful situational awareness information posted by eyewitnesses of disasters, in real time, are greatly needed. While many studies have focused on filtering textual information, the research on filtering disaster images is more limited. In particular, there are no studies on the applicability of domain adaptation to filter images from an emergent target disaster, when no labeled data is available for the target disaster. To fill in this gap, we propose to apply a domain adaptation approach, called domain adversarial neural networks (DANN), to the task of identifying images that show damage. The DANN approach has VGG-19 as its backbone, and uses the adversarial training to find a transformation that makes the source and target data indistinguishable. Experimental results on several pairs of disasters suggest that the DANN model generally gives similar or better results as compared to the VGG-19 model fine-tuned on the source labeled data. |
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| Address | Department of Computer Science, Kansas State University, United States of America;Department of Computer Science, University of Illinois at Chicago, United States of America;Qatar Computing Research Institute, Hamad Bin Khalifa University, Qatar | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1853 | |||
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| Author | Valerio Lorini; Carlos Castillo; Francesco Dottori; Milan Kalas; Domenico Nappo; Peter Salamon | ||||
| Title | Integrating Social Media into a Pan-European Flood Awareness System: A Multilingual Approach | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
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| Keywords | Social Media, Disaster Risk Management, Flood Risk | ||||
| Abstract | This paper describes a prototype system that integrates social media analysis into the European Flood Awareness System (EFAS). This integration allows the collection of social media data to be automatically triggered by flood risk warnings determined by a hydro-meteorological model. Then, we adopt a multi-lingual approach to find flood-related messages by employing two state-of-the-art methodologies: language-agnostic word embeddings and language-aligned word embeddings. Both approaches can be used to bootstrap a classifier of social media messages for a new language with little or no labeled data. Finally, we describe a method for selecting relevant and representative messages and displaying them back in the interface of EFAS. |
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| Address | European Commission, Joint Research Centre (JRC), Ispra, Italy;Universitat Pompeu Fabra, Barcelona, Spain;KAJO, Slovakia | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1854 | |||
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| Author | Sooji Han; Fabio Ciravegna | ||||
| Title | Rumour Detection on Social Media for Crisis Management | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages |
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| Keywords | Rumours, large-scale data, event summarisation, sub-event detection, social media analysis | ||||
| Abstract | We address the problem of making sense of rumour evolution during crises and emergencies. We study how understanding and capturing emerging rumours can benefit decision makers during such event. To this end, we propose a two-step framework for detecting rumours during crises. In the first step, we introduce an algorithm to identify noteworthy sub-events in real time. In the second step, we introduce a graph-based text ranking method for summarising newsworthy sub-events while events unfold. We use temporal and content-based features to achieve the effective and real-time response and management of crises situations. These features can improve efficiency in the detection of key rumours in the context of a real-world application. The effectiveness of our method is evaluated over large-scale Twitter data related to real-world crises. The results show that our framework can efficiently and effectively capture key rumours circulated during natural and human-made disasters. |
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| Address | The University of Sheffield, United Kingdom | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1860 | |||
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| Author | Amanda Langer; Marc-André Kaufhold; Elena Maria Runft; Christian Reuter; Margarita Grinko; Volkmar Pipek | ||||
| Title | Counter Narratives in Social Media: An Empirical Study on Combat and Prevention of Terrorism | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
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| Keywords | Counter Narratives, Online Campaign, Social Media, Terrorism, Radicalisation | ||||
| Abstract | With the increase of terrorist attacks and spreading extremism worldwide, countermeasures advance as well. Often social media is used for recruitment and radicalization of susceptible target groups. Counter narratives are trying to disclose the illusion created by radical and extremist groups through a purposive and educational counter statement, and to initiate a rethinking in the affected individuals via thought-provoking impulses and advice. This exploratory study investigates counter narrative campaigns with regard to their fight and prevention against terrorism in social media. Posts with strong emotions and a personal reference to affected individuals achieved the highest impact and most reactions from the target group. Furthermore, our results illustrate that the impact of a counter narrative campaign cannot be measured solely according to the reaction rate to their postings and that further analysis steps are therefore necessary for the final evaluation of the campaigns. |
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| Address | University of Siegen, Institute for Information Systems, Germany;Technische Universität Darmstadt, Science and Technology for Peace and Security (PEASEC), Germany | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1861 | |||
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| Author | Steven Sheetz; Andrea Kavanaugh; Edward Fox; Riham Hassan; Seungwon Yang; Mohamed Magdy; Shoemaker Donald | ||||
| Title | Information Uses and Gratifications Related to Crisis: Student Perceptions since the Egyptian Uprising | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages |
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| Keywords | Uses and gratifications theory; information sources; Internet; social media; structural equation modeling | ||||
| Abstract | People use diverse sources of information, e.g., newspapers, TV, Internet news, social media, and face-to-face conversations, to make sense of crises. We apply uses and gratifications theory (UGT) and structural equation modeling to illustrate how using internet-based information sources since the political uprisings in Egypt influence perceptions of information satisfaction. Consistent with expectations we find that content and process gratifications constructs combine to explain information satisfaction, while social gratifications do not significantly influence satisfaction in the context of a crisis. This suggests that UGT is useful for evaluating the use of information technology in a context where information is limited in quantity and reliability. |
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| Address | Virginia Tech, United States of America;Microsoft;Louisiana State University;Arab Academy of Science and Technology | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1862 | |||
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| Author | Liuqing Li; Edward A. Fox | ||||
| Title | Understanding patterns and mood changes through tweets about disasters | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages |
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| Keywords | Disaster, Pattern, User Classification, Mood Detection, Twitter | ||||
| Abstract | We analyzed a sample of large tweet collections gathered since 2011, to expand understanding about tweeting patterns and emotional responses of different types of tweeters regarding disasters. We selected three examples for each of four disaster types: school shooting, bombing, earthquake, and hurricane. For each collection, we deployed our novel model TwiRole for user classification, and an existing deep learning model for mood detection. We found differences in the daily tweet count patterns, between the different types of events. Likewise, there were different average scores and patterns of moods (fear, sadness, surprise), both between types of events, and between events of the same type. Further, regarding surprise and fear, there were differences among roles of tweeters. These results suggest the value of further exploration as well as hypothesis testing with our hundreds of event and trend related tweet collections, considering indications in those that reflect emotional responses to disasters. |
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| Address | Virginia Tech, United States of America | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1863 | |||
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| Author | Richard McCreadie; Cody Buntain; Ian Soboroff | ||||
| Title | TREC Incident Streams: Finding Actionable Information on Social Media | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages |
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| Keywords | Emergency Management, Crisis Informatics, Real-time, Twitter, Categorization | ||||
| Abstract | The Text Retrieval Conference (TREC) Incident Streams track is a new initiative that aims to mature social media-based emergency response technology. This initiative advances the state of the art in this area through an evaluation challenge, which attracts researchers and developers from across the globe. The 2018 edition of the track provides a standardized evaluation methodology, an ontology of emergency-relevant social media information types, proposes a scale for information criticality, and releases a dataset containing fifteen test events and approximately 20,000 labeled tweets. Analysis of this dataset reveals a significant amount of actionable information on social media during emergencies (> 10%). While this data is valuable for emergency response efforts, analysis of the 39 state-of-the-art systems demonstrate a performance gap in identifying this data. We therefore find the current state-of-the-art is insufficient for emergency responders? requirements, particularly for rare actionable information for which there is little prior training data available. |
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| Address | University of Glasgow, United Kingdom;New York University, USA;National Institute of Standards and Technology, USA | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1867 | |||
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| Author | Sara Barozzi; Jose Luis Fernandez Marquez; Amudha Ravi Shankar; Barbara Pernici | ||||
| Title | Filtering images extracted from social media in the response phase of emergency events | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages |
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| Keywords | rapid mapping, floods, information extraction, filtering, crowdsourcing | ||||
| Abstract | The use of social media to support emergency operators in the first hours of the response phases can improve the quality of the information available and awareness on ongoing emergency events. Social media contain both textual and visual information, in the form of pictures and videos. The problem related to the use of social media posts as a source of information during emergencies lies in the difficulty of selecting the relevant information among a very large amount of irrelevant information. In particular, we focus on the extraction of images relevant to an event for rapid mapping purpose. In this paper, a set of possible filters is proposed and analyzed with the goal of selecting useful images from posts and of evaluating how precision and recall are impacted. Filtering techniques, which include both automated and crowdsourced steps, have the goal of providing better quality posts and easy manageable data volumes both to emergency responders and rapid mapping operators. The impact of the filters on precision and recall in extracting relevant images is discussed in the paper in two different case studies. |
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| Address | Politecnico di Milano;University of Geneva | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1881 | |||
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| Author | Yuya Shibuya; Hideyuki Tanaka | ||||
| Title | Detecting Disaster Recovery Activities via Social Media Communication Topics | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages |
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| Keywords | Social Media, Topic modeling, Socio-economic recovery, Used-car demand, Housing demand. | ||||
| Abstract | Enhancing situational awareness by mining social media has been widely studied, but little work has been done focusing on recovery phases. To provide evidence to support the possibility of harnessing social media as a sensor of recovery activities, we examine the correlations between topic frequencies on Twitter and people?s socioeconomic recovery activities as reflected in the excess demand for used cars and housing, after the Great East Japan Earthquake and Tsunami of 2011. Our research suggests that people in the disaster-stricken area communicated more about recovery and disaster damages when they needed to purchase used cars, while the nonlocal population communicated more about going to and supporting the disaster-stricken area. On the other hand, regarding the excess demand for housing, when the local population of the disaster-stricken area started to resettle, they communicated their opinions more than in other periods about disaster-related situations. |
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| Address | The University of Tokyo, Japan | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1889 | |||
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| Author | Firoj Alam; Ferda Ofli; Muhammad Imran | ||||
| Title | CrisisDPS: Crisis Data Processing Services | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages |
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| Keywords | Social media, humanitarian data processing, text classification, application programming interfaces, data processing services | ||||
| Abstract | Over the last few years, extensive research has been conducted to develop technologies to support humanitarian aid tasks. However, many technologies are still limited as they require both manual and automatic approaches, and more importantly, are not ready to be integrated into the disaster response workflows. To tackle this limitation, we develop automatic data processing services that are freely and publicly available, and made to be simple, efficient, and accessible to non-experts. Our services take textual messages (e.g., tweets, Facebook posts, SMS) as input to determine (i) which disaster type the message belongs to, (ii) whether it is informative or not, and (iii) what type of humanitarian information it conveys. We built our services upon machine learning classifiers that are obtained from large-scale comparative experiments utilizing both classical and deep learning algorithms. Our services outperform state-of-the-art publicly available tools in terms of classification accuracy. |
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| Address | Qatar Computing Research Institute, Qatar | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1891 | |||
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| Author | Rob Grace; Shane Halse; Jess Kropczynski; Andrea Tapia; Fred Fonseca | ||||
| Title | Integrating Social Media in Emergency Dispatch via Distributed Sensemaking | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages |
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| Keywords | sensemaking, emergency dispatch, social media, role play | ||||
| Abstract | Emergency dispatchers typically answer 911 calls and relay information to first responders; however, new workflows arise when social media analysts are included in emergency dispatch work. In this study we examine emergency dispatch workflows as distributed sensemaking processes performed among 911 call takers, dispatchers, and social media analysts during simulated emergency dispatch operations. In active shooter and water rescue scenarios, emergency dispatch teams including call takers, dispatchers, and social media analysts make sense of unfolding events by analyzing, aggregating, and synthesizing information provided by 911 callers and social media users during each scenario. Findings from the simulations inform design requirements for social media analysis tools that can help analysts detect, seek, and analyze information posted on social media during a crisis, and protocols for coordinating analysts? sensemaking activities with those of 911 call takers and dispatchers in reconfigured emergency dispatch workflows. | ||||
| Address | Pennsylvania State University, United States of America;University of Cincinnati, United States of America | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1897 | |||
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| Author | Shane Errol Halse; Rob Grace; Jess Kropczynski; Andrea Tapia | ||||
| Title | Simulating real-time Twitter data from historical datasets | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages |
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| Keywords | Twitter, Simulation, Crisis Response, Social Media | ||||
| Abstract | In this paper, we will discuss a system design for simulating social media data based on historical datasets. While many datasets containing data collected from social media during crisis have become publicly available, there is a lack of tools or systems can present this data on the same timeline as it was originally posted. Through the design and use of the tool discussed in this paper, we show how historical datasets can be used for algorithm testing, such as those used in machine learning, to improve the quality of the data. In addition, the use of simulated data also has its benefits in training scenarios, which would allow participants to see real, non-fabricated social media messages in the same temporal manner as found on a social media platform. Lastly, we will discuss the positive reception and future improvements suggested by 911 Public Service Answering Point (PSAP) professionals. | ||||
| Address | PSU, United States of America;University of Cincinnati | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1898 | |||
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| Author | Yingjie Li; Seoyeon Park; Cornelia Caragea; Doina Caragea; Andrea Tapia | ||||
| Title | Sympathy Detection in Disaster Twitter Data | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages |
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| Keywords | Word Embedding, Deep Learning, Machine Learning, Sympathy Tweets Detection | ||||
| Abstract | Nowadays, micro-blogging sites such as Twitter have become powerful tools for communicating with others in various situations. Especially in disaster events, these sites can be the best platforms for seeking or providing social support, of which informational support and emotional support are the most important types. Sympathy, a sub-type of emotional support, is an expression of one?s compassion or sorrow for a difficult situation that another person is facing. Providing sympathy to people affected by a disaster can help change people?s emotional states from negative to positive emotions, and hence, help them feel better. Moreover, detecting sympathy contents in Twitter can potentially be used for finding candidate donors since the emotion ?sympathy? is closely related to people who may be willing to donate. Thus, in this paper, as a starting point, we focus on detecting sympathy-related tweets. We address this task using Convolutional Neural Networks (CNNs) with refined word embeddings. Specifically, we propose a refined word embedding technique in terms of various pre-trained word vector models and show great performance of CNNs that use these refined embeddings in the sympathy tweet classification task. We also report experimental results showing that the CNNs with the refined word embeddings outperform not only traditional machine learning techniques, such as Naïve Bayes, Support Vector Machines and AdaBoost with conventional feature sets as bags of words, but also Long Short-Term Memory Networks. |
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| Address | University of Illinois at Chicago, United States of America;Kansas State University, United States of America;Pennsylvania State University, United States of America | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1899 | |||
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| Author | Starr Roxanne Hiltz; Amanda Hughes; Muhammad Imran; Linda Plotnick; Robert Power; Murray Turoff | ||||
| Title | Requirements for Software to Support the use of Social Media in Emergency Management: A Delphi Study | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages |
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| Keywords | Social media, emergency management, crisis informatics, software requirements, Delphi method | ||||
| Abstract | Social Media contain a wealth of information that could improve the situational awareness of Emergency Managers during a crisis, but many barriers stand in the way. These include information overload, making it impossible to deal with the flood of raw posts, and lack of trust in unverified crowdsourced data. The purpose of this project is to build a communications bridge between emergency responders and technologists who can provide the advances needed to realize social media?s full potential. We are employing a Delphi study survey design, which is a technique for exploring and developing consensus among a group of experts around a particular topic. Participants include emergency managers and technologists with experience in software to support the use of social media in crisis response, from many countries. The topics of the study are described and preliminary, partial results presented for Round 1 of the study, based on 33 responses. | ||||
| Address | NJIT, United States of America;Brigham Young U.;Qatar Computing Research Inst.;Commonwealth Scientific and Industrial Research Organisation, Australia | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1906 | |||
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