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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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Murray Turoff. (2015). The Paradox of Emergency Management. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: The role of Emergency Management is to respond effectively to a major emergency that cannot be handled by the day to day independent services such as fire fighters, police, and medical response facilities. However, normal evolutionary processes typically make the ability to respond to disasters more difficult. This leads to long term decision and policy conflicts and incompatibilities about desirable goals, with implications for practitioners and system designers.
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Shane Errol Halse, Andrea Tapia, Anna Squicciarini, & Cornelia Caragea. (2016). An Emotional Step Towards Automated Trust Detection in Crisis 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: 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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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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Shane Halse, Jess Kropczynski, & Andrea Tapia. (2018). Using Metrics of Stability to Identify Points of Failure and Support in Online Information Distribution during a Disaster. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (p. 1121). Rochester, NY (USA): Rochester Institute of Technology.
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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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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Yang Zhang, William Drake, Yuhong Li, Christopher Zobel, & Margaret Cowell. (2015). Fostering Community Resilience through Adaptive Learning in a Social Media Age: Municipal Twitter Use in New Jersey following Hurricane Sandy. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
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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