Antonin Segault, Federico Tajariol, Yang Ishigaki, & Ioan Roxin. (2016). #geiger 2: Developing Guidelines for Radiation Measurements Sharing on Social Media. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
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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Apoorva Chauhan, & Amanda Lee Hughes. (2016). Online Mentioning Behavior during Hurricane Sandy: References, Recommendations, and Rebroadcasts. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Large-scale crisis events require coordination between the many responding stakeholders to provide timely, relevant, and accurate information to the affected public. In this paper, we examine how social media can support these coordinated public information efforts. This research considers how emergency responders mentioned different organizations, institutions, and individuals by examining the social media communications of police and fire departments during Hurricane Sandy. We find that these departments use mentions to reference other sources of information, recommend credible information and sources, and rebroadcast information. These mentions offer insight into how emergency responders fit within a broader crisis information network and the types of entities that responders trust and recommend to provide information to the public.
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Briony Jennifer Gray. (2016). Social Media and Disasters: A New Conceptual Framework. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
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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Cornelia Caragea, Adrian Silvescu, & Andrea Tapia. (2016). Identifying Informative Messages in Disasters using Convolutional Neural Networks. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
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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Daniel Link, Bernd Hellingrath, & Jie Ling. (2016). A Human-is-the-Loop Approach for Semi-Automated Content Moderation. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
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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Elodie Fichet, John Robinson, Dharma Dailey, & Kate Starbird. (2016). Eyes on the Ground: Emerging Practices in Periscope Use during Crisis Events. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
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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Emma Potter. (2016). Balancing conflicting operational and communications priorities: social media use in an emergency management organization. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
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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Jennings Anderson, Marina Kogan, Melissa Bica, Leysia Palen, Kenneth Anderson, Rebecca Morss, et al. (2016). Far Far Away in Far Rockaway: Responses to Risks and Impacts during Hurricane Sandy through First-Person Social Media Narratives. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
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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Jidi Zhao, & Linlin Wang. (2016). Research on Public Opinion Propagation in Micro-Blogging Based on Epidemic Models. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
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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Louis Ngamassi, Thiagarajan Ramakrishnan, & Shahedur Rahman. (2016). Examining the Role of Social Media in Disaster Management from an Attribution Theory Perspective. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
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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Muhammad Imran, Prasenjit Mitra, & Jaideep Srivastava. (2016). Cross-Language Domain Adaptation for Classifying Crisis-Related Short Messages. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
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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Pragna Debnath, Saniul Haque, Somprakash Bandyopadhyay, & Siuli Roy. (2016). Post-disaster Situational Analysis from WhatsApp Group Chats of Emergency Response Providers. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Use of social media has established itself as one of the important information carriers in the field of disaster management. However, use of Twitter and Facebook by victims, first responders and others generates information that is varied, unstructured and unreliable. On the other hand, NGOs, operating in the disaster area, are often involved in intra-organizational communication using messaging apps like WhatsApp, and their group interactions can help in gathering meaningful data for situational analysis and need assessment. Our focus is to automate the process of filtering relevant information, query-based clustering of pertinent information from a WhatsApp group conversation of a specific volunteer group, so that situation analysis and need assessment can be done more rapidly. We have evaluated our scheme using WhatsApp chat log of a medical volunteer group in two post-disaster scenarios and concluded that it can provide valuable insights about region-specific resource requirements and allocation for effective decision making.
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Shane Errol Halse, Andrea Tapia, Anna Squicciarini, & Cornelia Caragea. (2016). Tweet Factors Influencing Trust and Usefulness During Both Man-Made and Natural Disasters. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
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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Shannon Daly, & James A. Thom. (2016). Mining and Classifying Image Posts on Social Media to Analyse Fires. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: We propose a methodology to study the occurrence of fires through image posts on Flickr; crowd-sourcing information from a noisy social media dataset can estimate the presence of fires. We collect several years worth of photos and associated metadata using fire-related search terms. We use an image classification model to detect geotagged photos that are further analysed to determine if a fire event did occur at a particular time and place. Furthermore, a case study investigates image features and spatio-temporal elements in the metadata, as well as location information contained in camera EXIF data.
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Venkata Kishore Neppalli, Murilo Cerqueira Medeiros, Cornelia Caragea, Doina Caragea, Andrea Tapia, & Shane Halse. (2016). Retweetability Analysis and Prediction during Hurricane Sandy. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
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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Yuhong Li, & Christopher Zobel. (2016). Small Businesses and Social Media Usage in the 2013 Colorado Floods. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: The recovery of small businesses from a disaster is critical to community recovery. Such businesses can be extremely vulnerable to disasters, particularly because they often occupy a single location and have a localized customer base. Although social media is an effective platform for information dissemination, and has been extensively used in a disaster context, the way in which small businesses use social media in this context, and the effectiveness of those efforts, are still not well understood. With this in mind, this paper uses the 2013 floods along the Front Range in Colorado as a case study to help improve our understanding of how small businesses use social media in disaster situations. Characterizing the organizations' behavior involves using both qualitative and quantitative approaches, and the paper focuses on an initial qualitative analysis.
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