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Linda Plotnick, Starr Roxanne Hiltz, Jane A. Kushma, & Andrea Tapia. (2015). Red Tape: Attitudes and Issues Related to Use of Social Media by U.S. County-Level Emergency Managers. 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: Social media are ubiquitous in modern society. Among their uses are to provide real-time information during crisis. One might expect that emergency management agencies in the U.S. make use of social media extensively to disseminate and collect crisis information as that is where the information flows most freely and quickly; yet, these agencies are not fully exploiting the capabilities of social media. A survey of 241 U.S. emergency managers at the county level shows that only about half of these agencies use social media in any way as of 2014. Most do not have any formal policies to guide their use. Of those that do have formal policies, about one quarter actually forbid the use of social media. This study describes the barriers that impede use of social media by these emergency managers, and the ways in which they are currently used, and recommends steps to improve this use.
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Linda Plotnick, Starr Roxanne Hiltz, Sukeshini Grandhi, & Julie Dugdale. (2018). Real or Fake? User Behavior and Attitudes Related to Determining the Veracity of Social Media Posts. 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. 439–449). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: Citizens and Emergency Managers need to be able to distinguish “fake” (untrue) news posts from real news posts on social media during disasters. This paper is based on an online survey conducted in 2018 that produced 341 responses from invitations distributed via email and through Facebook. It explores to what extent and how citizens generally assess whether postings are “true” or “fake,” and describes indicators of the trustworthiness of content that users would like. The mean response on a semantic differential scale measuring how frequently users attempt to verify the news trustworthiness (a scale from 1-never to 5-always) was 3.37. The most frequent message characteristics citizens' use are grammar and the trustworthiness of the sender. Most respondents would find an indicator of trustworthiness helpful, with the most popular choice being a colored graphic. Limitations and implications for assessments of trustworthiness during disasters are discussed.
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Lise Ann St. Denis, Amanda L. Hughes, & Leysia Palen. (2012). Trial by fire: The deployment of trusted digital volunteers in the 2011 shadow lake fire. 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: We report on the use of a team of trusted digital volunteers during the 2011 Shadow Lake Fire that occurred in the US Pacific Northwest to extend the social media capacity of a Type I incident management team. In this case study, we outline the tools and processes used by this virtual team to coordinate their activities, monitor social media communication and to establish communications with the public around the event. Finally, we discuss the potential merits and limitations of implementing a team of trusted volunteers and explore how this idea could be incorporated into emergency management organizations. © 2012 ISCRAM.
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Lise Ann St. Denis, Amanda Lee Hughes, Jeremy Diaz, Kylen Solvik, Maxwell B. Joseph, & Jennifer K. Balch. (2020). 'What I Need to Know is What I Don't Know!': Filtering Disaster Twitter Data for Information from Local Individuals. 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. 730–743). Blacksburg, VA (USA): Virginia Tech.
Abstract: We report on the design, development, and evaluation of a user labeling framework for social media monitoring by emergency responders. By labeling Twitter user accounts based on behavior and content, this novel approach identifies tweets from accounts belonging to Individuals generating Personalized content and captures information that might otherwise be missed. We evaluate the framework using training data from the 2018 Camp, Woolsey, and Hill fires. Approximately 30% of the Individual-Personalized tweets contain first-hand information, providing a rich stream of content for social media monitoring. Because it can quickly eliminate most redundant tweets, this framework could be a critical first step in an end-to-end information extraction pipeline. It may also generalize more easily for new disaster events since it relies on general user account attributes rather than tweet content. We conclude with next steps for refining and evaluating our framework in near real-time during a disaster response.
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Lise Ann St. Denis, Leysia Palen, & Kenneth M. Anderson. (2014). Mastering social media: An analysis of Jefferson County's communications during the 2013 Colorado floods. 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. 737–746). University Park, PA: The Pennsylvania State University.
Abstract: We report on the social media communications and work practices of the Jefferson County Type III Incident Management Team during the September 2013 Colorado Floods. In this case study, we examine flood-related communications across three platforms: Facebook, Twitter, and the team's blog for insight into how this innovative team coordinated their communications to meet the information needs of a community outside of the media spotlight. Using a mixed method approach of interviews and social media content analysis, we describe their online behaviors in relation to the needs of the emergency response as a whole. We report on adaptations to their work practice that allowed them to extend traditional communications with social media to create an integrated communication plan. Finally, we look to the team's experiences for direction in how to use social media in emergencies generally.
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Lixiong Chen, Monika Buscher, & Yang Hu. (2019). On Liquid Ground: Contesting the facts around Shouguang Flood on Weibo. 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: As one of the most well-known social media platforms in China, Weibo provides an online public sphere. During the 2018 Shouguang flood, many people who were affected converged on the platform to discuss the disaster. The government ? the highest emergency management authority ? was accused of using censorship and other measures to suppress the coverage of the disaster. Based on an analysis of 34 qualitative interviews with Weibo users, of which nine directly address the Shouguang floods, this paper examines how three major actors contested facts and responsibilities during the disaster. Focusing on the state-censored, market-moderated social media context in China, our ongoing study provides new insights into a universal challenge of managing diverging interpretations and expectations in risk communication. We show that the establishing and framing of facts is inherently ethical and political. Time, time-space compression, liability and scales of risk responsibility emerge as critical points of friction. We draw on theories of risk governance, public discourse, computer supported collaborative work, and media studies for analysis and to articulate avenues for design.
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Long, Z., McCreadiem, R., & Imran, M. (2023). CrisisViT: A Robust Vision Transformer for Crisis Image Classification. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 309–319). Omaha, USA: University of Nebraska at Omaha.
Abstract: In times of emergency, crisis response agencies need to quickly and accurately assess the situation on the ground in order to deploy relevant services and resources. However, authorities often have to make decisions based on limited information, as data on affected regions can be scarce until local response services can provide first-hand reports. Fortunately, the widespread availability of smartphones with high-quality cameras has made citizen journalism through social media a valuable source of information for crisis responders. However, analyzing the large volume of images posted by citizens requires more time and effort than is typically available. To address this issue, this paper proposes the use of state-of-the-art deep neural models for automatic image classification/tagging, specifically by adapting transformer-based architectures for crisis image classification (CrisisViT). We leverage the new Incidents1M crisis image dataset to develop a range of new transformer-based image classification models. Through experimentation over the standard Crisis image benchmark dataset, we demonstrate that the CrisisViT models significantly outperform previous approaches in emergency type, image relevance, humanitarian category, and damage severity classification. Additionally, we show that the new Incidents1M dataset can further augment the CrisisViT models resulting in an additional 1.25% absolute accuracy gain.
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Louis Ngamassi, Abish Malik, Jiawei Zhang, & David Edbert. (2017). Social Media Visual Analytic Toolkits for Disaster Management: A Review of the Literature. 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. 785–797). Albi, France: Iscram.
Abstract: The past decade has seen a significant increase in the use of social media for disaster management. This is due especially to the widespread usage of mobile devices and also to the different data types and data formats that social media supports. In recent years, research in the area of social media visual analytics has also gained interest in the scientific community. Research in this area however, lacks a comprehensive overview on social media visual analytics for disaster management. Hence, this paper presents a synthesis of extant research on social media visual analytic and visualization toolkits for disaster management. We survey available literature on these tools with the goal to outline the major characteristics and features, and to examine the extent to which they cover the full cycle of disaster management. Our main purpose is to provide a foundation based on the current literature that can help to shape future research directions to enhance social media visual analytic tools for full cycle disaster management.
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Louis Ngamassi, Thiagarajan Ramakrishnan, & Shahedur Rahman. (2020). Investigating the Use of Social Media by Underserved Communities for Disaster Management. 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. 490–496). Blacksburg, VA (USA): Virginia Tech.
Abstract: Social media is emerging as a communication tool for successfully managing disasters. However, studies have shown that not all individuals are equally predisposed towards effectively using social media for disaster management. There still exists a big digital divide when it comes to using social media for disaster management. Drawing on situational theory of problem solving, we develop a conceptual model that examines the motivating factors for the underserved communities to use social media for disaster management. We further develop and cross-validate a questionnaire instrument to acilitate empirical research. We thus offer an empirical context for motivating individuals from underserved communities to use social media effectively during disasters.
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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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Lucia Castro Herrera. (2021). Configuring Social Media Listening Practices in Crisis Management. 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. 640–654). Blacksburg, VA (USA): Virginia Tech.
Abstract: Social media listening practices are increasingly adopted in crisis management and have become an object of interest for researchers and practitioners alike. This article analyzes how these enactments have been studied in the academic literature. Through a systematic review of the available body of knowledge, features from studies involving depictions of practice were extracted, analyzed, and turned into a narrative using an inductive approach. Strategies of improvisation, overreliance on personal and professional networks, manual work, spontaneous coordination, and re-assigning tasks represent the main findings in the multidisciplinary literature. This article is a consolidated overview of experiences from social media listening in practice beyond listing the benefits of social media as a source of information. Moreover, the paper sets the basis for future studies on the range of possible configurations and institutionalization of disruptive crisis management practices.
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Lucia Castro Herrera, & Terje Gjøsæter. (2022). Community Segmentation and Inclusive Social Media Listening. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 1012–1023). Tarbes, France.
Abstract: Social media analytics provide a generalized picture of situational awareness from the conversations happening among communities present in social media channels that are that are, or risk being affected by crises. The generalized nature of results from these analytics leaves underrepresented communities in the background. When considering social media analytics, concerns, sentiment, and needs are perceived as homogenous. However, offline, the community is diverse, often segmented by age group, occupation, or language, to name a few. Through our analysis of interviews from professionals using social media as a source of information in public service organizations, we argue that practitioners might not be perceiving this segmentation from the social media conversation. In addition, practitioners who are aware of this limitation, agree that there is room for improvement and resort to alternative mechanisms to understand, reach, and provide services to these communities in need. Thus, we analyze current perceptions and activities around segmentation and provide suggestions that could inform the design of social media analytics tools that support inclusive public services for all, including persons with disabilities and from other disadvantaged groups.
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Ma Ma, H. Zhang, & Yi Liu. (2014). Development of a joint official microblog platform to improve interactive communication with the public under a centralized system. 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. 782–786). University Park, PA: The Pennsylvania State University.
Abstract: Social media bring both challenges and opportunities to crisis management. This paper summarizes the difficulties in crisis communication under a centralized jurisdiction system by looking into online collective behaviors in mainland China. The paper then introduces the development of an official microblog and proposes a joint official microblog platform to improve interactive communication in a centralized system. The functional design of this platform is introduced in detail and the future improvement of the platform is discussed.
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Mahshid Marbouti, Craig Anslow, & Frank Maurer. (2018). Evaluation results for a Social Media Analyst Responding Tool. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 480–492). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: We take a human-centered design approach to develop a fully functional prototype, SMART (“Social Media Analyst Responding Tool”), informed by emergency practitioners. The prototype incorporates machine learning techniques to identify relevant information during emergencies. In this paper, we report the result of a user study to gather qualitative feedback on SMART. The evaluation results offer recommendations into the design of Social Media analysis tools for emergencies. The evaluation findings show the interest of emergency practitioners into designing such solutions; it reflects their need to not only identify relevant information but also to further perceive the outcome of their actions in social media. We found out there is a notable emphasis on the sentiment from these practitioners and social media analysis tools need to do a better job of handling negative sentiment within the emergency concept.
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Mahshid Marbouti, Irene Mayor, Dianna Yim, & Frank Maurer. (2017). Social Media Analyst Responding Tool: A Visual Analytics Prototype to Identify Relevant Tweets in Emergency Events. 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. 572–582). Albi, France: Iscram.
Abstract: Public and humanitarian organizations monitor social media to extract useful information during emergencies. In this paper, we propose a new method for identifying situation awareness (SA) tweets for emergencies. We take a human centered design approach to developing a visual analytics prototype, SMA-RT (“Social Media Analyst Responding Tool”), informed by social media analysts and emergency practitioners. Our design offers insights into the main requirements of social media monitoring tools used for emergency purposes. It also highlights the role that human and technology can play together in such solutions. We embed a machine learning classifier to identify SA tweets in a visual interactive tool. Our classifier aggregates textual, social, location, and tone based features to increase precision and recall of SA tweets.
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Marc-André Kaufhold, & Christian Reuter. (2017). The Impact of Social Media for Emergency Services: A Case Study with the Fire Department Frankfurt. 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. 603–612). Albi, France: Iscram.
Abstract: The use of social media is not only part of everyday life but also of crises and emergencies. Many studies focus on the concrete use of social media during a specific emergency, but the prevalence of social media, data access and published research studies allows the examination in a broader and more integrated manner. This work-in-progress paper presents the results of a case study with the Fire Department Frankfurt, which is one of the biggest and most modern fire departments in Germany. The findings relate to social media technologies, organizational structure and roles, information validation, staff skills and resources, and the importance of volunteer communities. In the next step, the results will be integrated into the frame of a comparative case study with the overall aim of examining the impact of social media on how emergency services respond and react in an emergency.
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Marion Lara Tan, Sara Harrison, Julia S. Becker, Emma E.H. Doyle, & Raj Prasanna. (2020). Research Themes on Warnings in Information Systems Crisis Management Literature. 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. 1085–1099). Blacksburg, VA (USA): Virginia Tech.
Abstract: Early Warning Systems (EWS) are crucial to mitigating and reducing disaster impacts. Furthermore, technology and information systems (IS) are key to the success of EWSs. This systematic literature review investigates the research topics and themes from the past six years of Information Systems for Crisis Response and Management (ISCRAM) conference proceedings and seeks to identify the research developments and directions for EWSs to steer a discourse to advance the research in this field. Findings from a sample size of 60 papers show that there are technical, social, and topical considerations to using and advancing technology for EWSs. While technology has advanced EWSs to new levels, it is important to consider the influence of technology in the successful operation of EWSs. The results are based on the ISCRAM proceedings literature and may be broader or have different prioritization if a wider disciplinary body of literature was explored. This will be considered in the future.
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Mark Latonero, & Irina Shklovski. (2010). Respectfully yours in safety and service: Emergency management & social media evangelism. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: In this paper we consider how emergency response organizations utilize available social media technologies to communicate with the public in emergencies and to potentially collect valuable information using the public as sources of information on the ground. We discuss the use of public social media tools from the emergency management professionals. viewpoint with a particular focus on the use of Twitter. Little research has investigated Twitter usage in crisis situations from an organizational perspective. This paper contributes to our understanding of organizational innovation, risk communication, and technology adoption by emergency management. An in-depth case study of Public Information Officers of the Los Angeles Fire Department highlights the importance of the information evangelist within emergency management organizations and details the challenges those organizations face with an engagement with social media and Twitter. This article provides insights into practices and challenges of new media implementation for crisis and risk management organizations.
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Marta Poblet Balcell, Stan Karanasios, & Vanessa Cooper. (2018). Look after Your Neighbours: Social Media and Vulnerable Groups during Extreme Weather Events. 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. 408–415). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: Emergency management organisations across the world routinely use social media to reach out populations for preparedness and response to extreme weather events. In this paper we present a preliminary analysis of social media strategies towards vulnerable populations in the State of Victoria (Australia). Using the notion of vulnerability in an emergency management context (e.g. older persons, socially/geographically isolated persons, people with disabilities, refugee/recent migrant communities) we explore whether and how organisations address vulnerable groups with targeted messages. Our initial findings suggest that organisations do not tend to interact directly with these groups. Rather, reliance on 'information brokers' (intermediary organisations and individuals with an expected duty of care) seems to be a preferred strategy.
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Maryam Shahbazi, Christian Ehnis, Majid Shahbazi, & Deborah Bunker. (2018). Tweeting from the Shadows: Social Media Convergence Behaviour During the 2017 Iran-Iraq Earthquake. 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. 416–427). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: Official policies, socioeconomic and demographic factors influence how individuals cope with, and respond to natural disasters. Understanding the impact of these factors in social media crisis communications studies is difficult. This paper focuses on convergence behaviour during social media crisis communication in an environment where the access to commercial social media platforms is highly restricted. This study is designed as a case which analyses 41,745 Tweets communicated during an earthquake event and for the two weeks after. This research aims to understand how different communities use social media services for communication during extreme events. The content of the Tweets shows users' attitudes toward government policies as well as the social difficulties of ethnic groups reflecting on the use of social media in crises communication. The results indicate a “political effect” on this online crisis communication. This behaviour was not expected and has been underreported in the current body of knowledge.
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Maximilian Walther, Sven Schaust, & Michael Kaisser. (2013). Social media-based event detection for crisis management in the al za'atari refugee camp. 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. 927–928). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Social Media data allows for profound analyses of user-generated content in order to predict or manage disasters and crisis situations. In this paper, we present an analysis of tweets from and about Al Za'atari, a refugee camp in Jordan close to the Syrian border. Our results are based on the analysis of location-tagged tweets by our “Avalanche” system in order to support an accurate situational awareness picture for on-site and off-site operators from relief organizations on evolving events and challenges.
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Michael Aupetit, & Muhammad Imran. (2017). Interactive Monitoring of Critical Situational Information on Social Media. 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. 673–683). Albi, France: Iscram.
Abstract: According to many existing studies, the data available on social media platforms such as Twitter at the onset of a crisis situation could be useful for disaster response and management. However, making sense of this huge data coming at high-rate is still a challenging task for crisis managers. In this work, we present an interactive social media monitoring tool that uses a supervised classification engine and natural language processing techniques to provide a detailed view of an on-going situation. The tool allows users to apply various filtering options using interactive timelines, critical entities, and other logical operators to get quick access to situational information. The evaluation of the tool conducted with crisis managers shows its significance for situational awareness and other crisis management related tasks.
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Muhammad Imran, Firoj Alam, Umair Qazi, Steve Peterson, & Ferda Ofli. (2020). Rapid Damage Assessment Using Social Media Images by Combining Human and Machine Intelligence. 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. 761–773). Blacksburg, VA (USA): Virginia Tech.
Abstract: Rapid damage assessment is one of the core tasks that response organizations perform at the onset of a disaster to understand the scale of damage to infrastructures such as roads, bridges, and buildings. This work analyzes the usefulness of social media imagery content to perform rapid damage assessment during a real-world disaster. An automatic image processing system, which was activated in collaboration with a volunteer response organization, processed ~280K images to understand the extent of damage caused by the disaster. The system achieved an accuracy of 76% computed based on the feedback received from the domain experts who analyzed ~29K system-processed images during the disaster. An extensive error analysis reveals several insights and challenges faced by the system, which are vital for the research community to advance this line of research.
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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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Muhammad Imran, Shady Elbassuoni, Carlos Castillo, Fernando Díaz, & Patrick Meier. (2013). Extracting information nuggets from disaster- Related messages in social media. 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. 791–801). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Microblogging sites such as Twitter can play a vital role in spreading information during “natural” or man-made disasters. But the volume and velocity of tweets posted during crises today tend to be extremely high, making it hard for disaster-affected communities and professional emergency responders to process the information in a timely manner. Furthermore, posts tend to vary highly in terms of their subjects and usefulness; from messages that are entirely off-topic or personal in nature, to messages containing critical information that augments situational awareness. Finding actionable information can accelerate disaster response and alleviate both property and human losses. In this paper, we describe automatic methods for extracting information from microblog posts. Specifically, we focus on extracting valuable “information nuggets”, brief, self-contained information items relevant to disaster response. Our methods leverage machine learning methods for classifying posts and information extraction. Our results, validated over one large disaster-related dataset, reveal that a careful design can yield an effective system, paving the way for more sophisticated data analysis and visualization systems.
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