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Adam Flizikowski, M. P., Anna Stachowicz, Tomasz Olejniczak, & Rafael Renk. (2015). Text Analysis Tool TWeet lOcator ? TAT2. 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: 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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Ahmed Alnuhayt, Suvodeep Mazumdar, Vitaveska Lanfranchi, & Frank Hopfgartner. (2022). Understanding Reactions to Misinformation – A Covid-19 Perspective. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 687–700). Tarbes, France.
Abstract: The increasing use of social media as an information source brings further challenges – social media platforms can be an excellent medium for disseminating public awareness and critical information, that can be shared across large populations. However, misinformation in social media can have immense implications on public health, risking the effectiveness of health interventions as well as lives. This has been particularly true in the case of COVID-19 pandemic, with a range of misinformation, conspiracy theories and propaganda being spread across social channels. In our study, through a questionnaire survey, we set out to understand how members of the public interact with different sources when looking for information on COVID-19. We explored how participants react when they encounter information they believe to be misinformation. Through a set of three behaviour tasks, synthetic misinformation posts were provided to the participants who chose how they would react to them. In this work in progress study, we present initial findings and insights into our analysis of the data collected. We highlight what are the most common reactions to misinformation and also how these reactions are different based on the type of misinformation.
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Aibek Musaev, Kimberly Stowers, & Jonghun Kam. (2018). Harnessing Data to Create an Effective Drought Management System. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 544–552). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Drought is a complex climate phenomenon with slow emergence and quick vanish, which makes it hard for stakeholders to respond to drought timely. To reduce the vulnerability of our society to future drought, a better understanding of how society responds to drought is critical. Here, we propose a pilot study about social response to a recent California drought through social media. In this study, we identify the most important users using an extension of PageRank algorithm. We investigate the key drivers of the public activity in February, 2014 during the California drought. We also create a word cloud visualization from the most retweeted tweets. Lastly, we specify the information sources from those tweets. The findings of this study inform us that big data can help us to improve the current drought response plans through fundamental understanding of social response to drought, which is applicable to other natural hazards.
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Amro Al-Akkad, Christian Raffelsberger, Alexander Boden, Leonardo Ramirez, & Zimmermann, A. (2014). Tweeting 'when online is off'? Opportunistically creating mobile ad-hoc networks in response to disrupted infrastructure. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 662–671). University Park, PA: The Pennsylvania State University.
Abstract: In this paper, we present a system that enables people to post and receive tweets despite disruptions of existing network infrastructure. Our system opportunistically deploys mobile ad hoc networks (MANETs) based on Wi-Fi in which people can communicate with each other in a peer-to-peer fashion. A MANET per se constitutes an isolated island, but as people carry devices around that can join other MANETs, eventually people can transport previously collected data to the online world. Compared to other systems that aim to enable communication in crisis, our system differs in two ways: it does not rely on existing network infrastructure, and it exploits established protocols and standards allowing it to run on off-the-shelf, commercially available smartphones. We evaluated our prototype with a group of students and practitioners. Overall, we received positive feedback on the potential of our technology, but also were pointed to limitations requiring future work.
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Alan Aipe, Asif Ekbal, Mukuntha NS, & Sadao Kurohashi. (2018). Linguistic Feature Assisted Deep Learning Approach towards Multi-label Classification of Crisis Related Tweets. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 705–717). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Micro-blogging site like Twitter, over the last decade, has evolved into a proactive communication channel during mass convergence and emergency events, especially in crisis stricken scenarios. Extracting multiple levels of information associated with the overwhelming amount of social media data generated during such situations remains a great challenge to disaster-affected communities and professional emergency responders. These valuable data, segregated into different informative categories, can be leveraged by the government agencies, humanitarian communities as well as citizens to bring about faster response in areas of necessity. In this paper, we address the above scenario by developing a deep Convolutional Neural Network (CNN) for multi-label classification of crisis related tweets.We augment deep CNN by several linguistic features extracted from Tweet, and investigate their usage in classification. Evaluation on a benchmark dataset show that our proposed approach attains the state-of-the-art performance.
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Amanda Langer, Marc-André Kaufhold, Elena Maria Runft, Christian Reuter, Margarita Grinko, & Volkmar Pipek. (2019). Counter Narratives in Social Media: An Empirical Study on Combat and Prevention of Terrorism. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
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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Andrea Kavanaugh, Steven D. Sheetz, Riham Hassan, Seungwon Yang, Hicham G. Elmongui, Edward A. Fox, et al. (2012). Between a rock and a cell phone: Communication and information technology use during the 2011 Egyptian uprising. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Many observers heralded the use of social media during recent political uprisings in the Middle East even dubbing Iran's post election protests a “Twitter Revolution”. We seek to put into perspective the use of social media in Egypt during the mass political demonstrations in 2011. We draw on innovation diffusion theory to argue that these media could have had an impact beyond their low adoption rates due to other factors related to demographics and social networks. We supplement our social media data analysis with survey data we collected in June 2011 from an opportunity sample of Egyptian youth. We conclude that in addition to the contextual factors noted above, the individuals within Egypt who used Twitter during the uprising have the characteristics of opinion leaders. These findings contribute to knowledge regarding the role of opinion leaders and social media, especially Twitter, during violent political demonstrations. © 2012 ISCRAM.
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Andrés Moreno, Philip Garrison, & Karthik Bhat. (2017). WhatsApp for Monitoring and Response during Critical Events: Aggie in the Ghana 2016 Election. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 645–655). Albi, France: Iscram.
Abstract: Mobile Instant Messaging platforms like WhatsApp are becoming increasingly popular. They have expanded access to digital text, audio, picture, and video messaging. Integrating them into existing crisis monitoring and response platforms and workflows can help reach a wider population. This paper describes a first attempt to integrate WhatsApp into Aggie, a social media aggregating and monitoring platform. We report on the deployment of this integration during Ghana's 2016 election, along with Twitter, Facebook, and RSS. The WhatsApp messages collected by Aggie during the election improved the eectiveness of the monitoring eorts. Thanks to these messages, more incidents were found and escalated to the Electoral Commission and security forces. From interviews with people involved in monitoring and response, we found that the WhatsApp integration helped their coordination and monitoring activities.
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Anna Kruspe. (2020). Detecting Novelty in Social Media Messages During Emerging Crisis Events. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 860–871). Blacksburg, VA (USA): Virginia Tech.
Abstract: Social media can be a highly valuable source of information during disasters. A crisis' development over time is of particular interest here, as social media messages can convey unfolding events in near-real time. Previous approaches for the automatic detection of information in such messages have focused on a static analysis, not taking temporal changes and already-known information into account. In this paper, we present a novel method for detecting new topics in incoming Twitter messages (tweets) conditional upon previously found related tweets. We do this by first extracting latent representations of each tweet using pre-trained sentence embedding models. Then, Infinite Mixture modeling is used to dynamically cluster these embeddings anew with each incoming tweet. Once a cluster reaches a minimum number of members, it is considered to be a new topic. We validate our approach on the TREC Incident Streams 2019A data set.
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Anna Kruspe, Jens Kersten, & Friederike Klan. (2019). Detecting event-related tweets by example using few-shot models. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Social media sources can be helpful in crisis situations, but discovering relevant messages is not trivial. Methods
have so far focused on universal detection models for all kinds of crises or for certain crisis types (e.g. floods).
Event-specific models could implement a more focused search area, but collecting data and training new models for
a crisis that is already in progress is costly and may take too much time for a prompt response. As a compromise,
manually collecting a small amount of example messages is feasible. Few-shot models can generalize to unseen
classes with such a small handful of examples, and do not need be trained anew for each event. We show how
these models can be used to detect crisis-relevant tweets during new events with just 10 to 100 examples and
counterexamples. We also propose a new type of few-shot model that does not require counterexamples.
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Antone Evans Jr., Yingyuan Yang, & Sunshin Lee. (2021). Towards Predicting COVID-19 Trends: Feature Engineering on Social Media Responses. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 792–807). Blacksburg, VA (USA): Virginia Tech.
Abstract: During the course of this pandemic, the use of social media and virtual networks has been at an all-time high. Individuals have used social media to express their thoughts on matters related to this pandemic. It is difficult to predict current trends based on historic case data because trends are more connected to social activities which can lead to the spread of coronavirus. So, it's important for us to derive meaningful information from social media as it is widely used. Therefore, we grouped tweets by common keywords, found correlations between keywords and daily COVID-19 statistics and built predictive modeling. The features correlation analysis was very effective, so trends were predicted very well. A RMSE score of 0.0425504, MAE of 0.03295105 and RSQ of 0.5237014 in relation to daily deaths. In addition, we found a RMSE score of 0.07346836, MAE of 0.0491152 and RSQ 0.374529 in relation to daily cases.
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Antonin Segault, Federico Tajariol, & Ioan Roxin. (2015). #geiger : Radiation Monitoring Twitter Bots for Nuclear Post-Accident Situations. 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: 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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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 Hughes. (2021). COVID-19 Named Resources on Facebook, Twitter, and Reddit. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 679–690). Blacksburg, VA (USA): Virginia Tech.
Abstract: Crisis Named Resources (CNRs) are social media accounts and pages named after a crisis event. They are created soon after an event occurs. CNRs share a lot of information around an event and are followed by many. In this study, we identify CNRs created around COVID-19 on Facebook, Twitter, and Reddit. We analyze when these resources were created, why they were created, how they were received by members of the public, and who created them. We conclude by comparing CNRs created around COVID-19 with past crisis events and discuss how CNR owners attempt to manage content and combat misinformation.
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Apoorva Chauhan, & Amanda Lee Hughes. (2015). Facebook and Twitter Adoption by Hurricane Sandy-affected Police and Fire Departments. 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: We report initial findings around the Facebook and Twitter adoption trends of 840 fire and police departments affected by Hurricane Sandy. The data show that adoption increased during the time period directly surrounding Hurricane Sandy. Despite this increase, the creation of new online accounts since that time has been declining and overall adoption rates seem to be stabilizing. Lastly, the data report Facebook to be significantly more popular than Twitter as a form of online communication for these fire and police departments.
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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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Apoorva Chauhan, & Amanda Lee Hughes. (2018). Social Media Resources Named after a Crisis Event. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 573–583). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Crisis Named Resources (CNRs) are the social media accounts and pages named after a crisis event. CNRs typically appear spontaneously after an event as places for information exchange. They are easy to find when searching for information about the event. Yet in most cases, it is unclear who manages these resources. Thus, it is important to understand what kinds of information they provide and what role they play in a response. This paper describes a study of Facebook and Twitter CNRs around the 2016 Fort McMurray wildfire. We report on CNR lifecycles, and their relevance to the event. Based on the information provided by these resources, we categorize them into 8 categories: donations, fundraisers, prayers, reactions, reports, needs and offers, stories, and unrelated. We also report on the most popular CNR on both Facebook and Twitter. We conclude by discussing the role of CNRs and the need for future investigation.
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Asmelash Teka Hadgu, Sallam Abualhaija, & Claudia Niederée. (2019). Real-time Adaptive Crawler for Tracking Unfolding Events on Twitter. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: When a major event such as a crisis situation occurs, people post messages on social media sites such as Twitter, in
order to exchange information or to share emotions. These posts can provide useful information to raise situation
awareness and support decision making, e.g., by aid organizations. In this paper, we propose a novel method for
social media crawling, which exploits a Bayesian inference framework to keep track of keyword changes over time
and uses a counter-stream to gauge the inclusion of noise and irrelevant information. In addition, we present a
framework to evaluate real-time adaptive social search algorithms in a reproducible manner, which relies on a
semi-automated approach for ground-truth construction. We show that our method outperforms previous methods
for very large scale events.
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Kartikeya Bajpai, & Anuj Jaiswal. (2011). A framework for analyzing collective action events on Twitter. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Recent years have witnessed multiple international protest movements which have purportedly been greatly affected by the use of Twitter, a micro-blogging platform. Social movement actors in Iran, Moldova, Kyrgyzstan and Thailand are thought to have utilized Twitter to spread information, co-ordinate protest activities, evade government censorship and, in some cases, to spread misinformation. We propose a framework for conceptualizing and analyzing Twitter data related to contentious collective action crises. Our primary research goal is to delineate a framework informed with a social movements lens and to demonstrate the framework by means of Twitter usage data related to the Thailand protests of 2010. Our proposed framework concerns itself with two aspects of protest activities and Twitter usage, namely, analyzing the content and structure of messages and our construct of Twitter protest waves.
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Roser Beneito-Montagut, Susan Anson, Duncan Shaw, & Christopher Brewster. (2013). Governmental social media use for emergency communication. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 828–833). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The possibility of crowdsourced information, multi-geographical and multi-organisational information flows during emergencies and crises provided by web 2.0 tools are providing emergency management centres with new communication challenges and opportunities. Building on the existing emergency management and social media literature, this article explores how institutions are using and adopting social media for emergency communication. By examining the drivers and barriers of social media adoption in two European governmental agencies dealing with emergencies, the paper aims to establish a framework to examine whether and how institutional resilience could be improved.
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Jesse Blum, Genovefa Kefalidou, Robert Houghton, Martin Flintham, Unna Arunachalam, & Murray Goulden. (2014). Majority report: Citizen empowerment through collaborative sensemaking. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 767–771). University Park, PA: The Pennsylvania State University.
Abstract: In the past crisis sensemaking activities have primarily been controlled by professional emergency responders and the media. Social media, however, has the potential to see a shift towards more grassroots and ad hoc citizen engagement. This paper sets out our vision and our progress in implementation of a new online platform called 'Majority Report', which aims to empower citizen sensemaking activities around crisis events. The concept is to facilitate citizen volunteers to draw together a range of digital media (photographs, Tweets, videos, etc.) to present stories of crisis events, and thus demarcate arguments about different understandings in terms of the temporal ordering of event narrative components and their relations to each other. Through collaborative usages of the platform, accounts may be improved by others, and variants may be presented and compared to challenge existing assumptions and beliefs.
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Briony Gray, Mark J. Weal, & David Martin. (2017). Social Media during a Sustained Period of Crisis: The Case of the UK Storms. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 633–644). Albi, France: Iscram.
Abstract: This paper analyses the social media communications surrounding the 2015 – 2016 series of winter storms in the UK. Three storms were selected for analysis over a sustained period of time; these were storms Desmond, Eva and Frank which made landfall within quick succession of one another. In this case study we examine communications relating to multiple hazards which include flooding, evacuation and weather warnings using mainstream media content such as news stories, and online content such as Twitter data. Using a mixed method approach of content analysis combined with the application of a conceptual framework, we present (i.) the network of emergency responders managing events, (ii.) an analysis of crisis communications over time, and (iii.) highlight the barriers posed to effective social media communications during multi-hazard disasters. We conclude by assessing how these barriers may be lessened during prolonged periods of crisis.
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Briony Gray, Mark Weal, & David Martin. (2018). Building Resilience in Small Island Developing States: Social Media during the 2017 Atlantic Hurricane Season. In Kristin Stock, & Deborah Bunker (Eds.), Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. (pp. 469–479). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: There are growing concerns that future Atlantic hurricane seasons will be severe and unpredictable due to underlying factors such as climate change. The 2017 season may offer a range of lessons, especially to small island developing states (SIDS), who are looking to build community resilience and heighten community engagement to cope with disaster. While many SIDS utilise a range of media and technology for these purposes, there has been a recent uptake in the use of social media, which may have further potential to support their goals. This paper scopes the use and users of social media in the case of Antigua and Barbuda during the 2017 Atlantic hurricane season. Through a series of qualitative interviews it explains the role that social media currently has, and concludes with suggestions for its improvement in future seasons that are contextualized over the disaster lifecycle phases.
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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, Anna Squicciarini, Sam Stehle, Kishore Neppalli, & Andrea H. Tapia. (2014). Mapping moods: Geo-mapped sentiment analysis during hurricane sandy. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 642–651). University Park, PA: The Pennsylvania State University.
Abstract: Sentiment analysis has been widely researched in the domain of online review sites with the aim of generating summarized opinions of product users about different aspects of the products. However, there has been little work focusing on identifying the polarity of sentiments expressed by users during disaster events. Identifying sentiments expressed by users in an online social networking site can help understand the dynamics of the network, e.g., the main users' concerns, panics, and the emotional impacts of interactions among members. 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. In this work, we perform sentiment classification of user posts in Twitter during the Hurricane Sandy and visualize these sentiments on a geographical map centered around the hurricane. We show how users' sentiments change according not only to users' locations, but also based on the distance from the disaster.
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