Crisis Communication Patterns in Social Media during Hurricane Sandy

Hurricane Sandy was one of the deadliest and costliest of hurricanes over the past few decades. Many states experienced significant power outage, however many people used social media to communicate while having limited or no access to traditional information sources. In this study, we explored the evolution of various communication patterns using machine learning techniques and determined user concerns that emerged over the course of Hurricane Sandy. The original data included ~52M tweets coming from ~13M users between October 14, 2012 and November 12, 2012. We run topic model on ~763K tweets from top 4,029 most frequent users who tweeted about Sandy at least 100 times. We identified 250 well-defined communication patterns based on perplexity. Conversations of most frequent and relevant users indicate the evolution of numerous storm-phase (warning, response, and recovery) specific topics. People were also concerned about storm location and time, media coverage, and activities of political leaders and celebrities. We also present each relevant keyword that contributed to one particular pattern of user concerns. Such keywords would be particularly meaningful in targeted information spreading and effective crisis communication in similar major disasters. Each of these words can also be helpful for efficient hash-tagging to reach target audience as needed via social media. The pattern recognition approach of this study can be used in identifying real time user needs in future crises

Crisis Event Extraction Service (CREES) - Automatic Detection and Classification of Crisis-related Content on Social Media

Social media posts tend to provide valuable reports during crises. However, this information can be hidden in large amounts of unrelated documents. Providing tools that automatically identify relevant posts, event types (e.g., hurricane, floods, etc.) and information categories (e.g., reports on affected individuals, donations and volunteering, etc.) in social media posts is vital for their efficient handling and consumption. We introduce the Crisis Event Extraction Service (CREES), an open-source web API that automatically classifies posts during crisis situations. The API provides annotations for crisis-related documents, event types and information categories through an easily deployable and accessible web API that can be integrated into multiple platform and tools. The annotation service is backed by Convolutional Neural Networks (CNNs) and validated against traditional machine learning models. Results show that the CNN-based API results can be relied upon when dealing with specific crises with the benefits associated with the usage word embeddings

Social Media Analytics in Disaster Response: A Comprehensive Review

Social media has emerged as a valuable resource for disaster management, revolutionizing the way emergency response and recovery efforts are conducted during natural disasters. This review paper aims to provide a comprehensive analysis of social media analytics for disaster management. The abstract begins by highlighting the increasing prevalence of natural disasters and the need for effective strategies to mitigate their impact. It then emphasizes the growing influence of social media in disaster situations, discussing its role in disaster detection, situational awareness, and emergency communication. The abstract explores the challenges and opportunities associated with leveraging social media data for disaster management purposes. It examines methodologies and techniques used in social media analytics, including data collection, preprocessing, and analysis, with a focus on data mining and machine learning approaches. The abstract also presents a thorough examination of case studies and best practices that demonstrate the successful application of social media analytics in disaster response and recovery. Ethical considerations and privacy concerns related to the use of social media data in disaster scenarios are addressed. The abstract concludes by identifying future research directions and potential advancements in social media analytics for disaster management. The review paper aims to provide practitioners and researchers with a comprehensive understanding of the current state of social media analytics in disaster management, while highlighting the need for continued research and innovation in this field.Comment: 11 page

Social Signal Processing for Real-time Situational Understanding: A Vision and Approach

National Research Foundation (NRF) Singapore under International Research Centres in Singapore Funding Initiativ

Exploring Social Media Affordances in Natural Disaster: Case Study of 2015 Myanmar Flood

Consumers’ willingness to disclose and allow electronic storage of their personal health information (PHI) is critical to the successful digitization of healthcare. However, concern about privacy and potentially negative consequences of privacy loss (e.g., loss of jobs) can discourage PHI disclosure by consumers. It is thus imperative to identify and address key roadblocks from the perspective of consumers that may impede the progress of developing countries in digitizing healthcare. Toward this end, this research-in-progress integrates the privacy calculus model with procedural justice to investigate the willingness of individuals in developing countries to disclose PHI in order to receive care in contexts where the disclosed PHI is stored and used electronically. A comprehensive model is proposed to explain the determinants of consumer PHI privacy concerns and willingness to disclose PHI. We will test the proposed model using the survey method. Several theoretical contributions expected from the study are provided

Hajj Pilgrims’ Perceptions of Trust and Internet Use for (Emergency) Information

This empirical study examines the patterns of internet use during Hajj, with the broader aim of providing suggestions on how organisations can improve risk communication at crowded religious venues using traditional and new media. The research team adopted a convenience sampling strategy to conduct in-person surveys of 348 Hajj pilgrims in the vicinity of the Grand Mosque in Madinah, Saudi Arabia during the October 2013 season. Of these, 150 pilgrims used the internet and their responses were analysed using simple descriptive statistics and binary regression analyses. The findings of this study suggest that Hajj pilgrims prefer accessing the internet through their smartphone devices and laptops, and both first timers and repeat pilgrims trusted websites hosted by the Saudi Arabian authorities, and their group leaders. Additionally, findings suggest that the trust in information sources and patterns of social media use differed by demographic characteristics such as age, language and economic characteristics. This underscores the need for diversifying the use of both traditional and new media communication channels to increase the diffusion and penetration of risk information for varied groups. Cross-checking of government efforts with such empirical studies helps demonstrate whether the funds expended to improve risk communication and raise hazard awareness are on point to make the pilgrims safer. The paper concludes by acknowledging that although the internet and social media are revolutionising the kinds of information available to pilgrims, they may lead to a loss in the sanctity, simplicity and equanimity of partaking in a pilgrimage, or bring harm to pilgrims through the misuse of personal data collected through social media sites. Suggestions are made to authorities and event organisers to keep a balance between traditional and modern practices of conducting a pilgrimage and designing information and communication technologies. A call for inspiring pilgrims to not only be consumers of information, but rather, providers of information by being ever vigilant is made. Presently, few pilgrimage destinations are using the power of the internet and social media for garnering pilgrims’ participation in risk communication and crisis preparedness which is a missed opportunity

The Social Media Intelligence Analyst for Emergency Management

The Social Media Intelligence Analyst is a new operational role within a State Control Centre in Victoria, Australia dedicated to obtaining situational awareness from social media to support decision making for emergency management. We outline where this role fits within the structure of a command and control organisation, describe the requirements for such a position and detail the operational activities expected during an emergency event. As evidence of the importance of this role, we provide three real world examples where important information was obtained from social media which led to improved outcomes for the community concerned. \ \ This is the first time a dedicated role has been formally established solely for monitoring social media for emergency management intelligence gathering purposes in Victoria. To the best of our knowledge, it is also the first time such a dedicated position in an operational crisis coordination centre setting has been described in the literature

Kajian terhadap kepadanan Facebook sebagai teknologi untuk berkongsi maklumat semasa banjir

Social media is gaining its popularity as one of the most used ICT platform for information sharing. Recently, social media has been identified as one of the important communication platforms to disseminate information during the event of disaster. Although it has been acknowledged as one of the most useful platforms to disseminate information, there are situations where this platform has been found notsuitable to support this task. Thus, examining the fit between the task and technology can enhance the efficiency of information sharing. The main aim of this study is to identify the factors that influenced task technology fit using social mediaespecially Facebook when sharing information during the flood. Theory of task-technology fit (TTF) has been used as an underlying theory for this study. This study administered web based questionnaire as the data collection technique to obtain data from respondent which is the user of National Security Counsil’s Facebook. Then, the obtained data is analyzed using partial least square (PLS) technique. SmartPLS 2.0 software was used to validate the research model and test the proposed research hypotheses.The findings showed that task characteristic has a strong influenced over technology characteristic to determine the fit between information sharing task and Facebook technology. Theoretically, this study developed a better understanding of what influence task technology fit using Facebook to share information during the event of flood; examined the significant factors that contribute to higher task technology fit during the flood; and proposed a theoretical model that can be used to predict the fit between information sharing task and Facebook during the occurance of flood. Practically, this study contributes by proposing a mechanism to the government agencies on how to improve the fit between Facebook and information sharing task duringflood

@Houstonpolice: an exploratory case of Twitter during Hurricane Harvey

Abstract Purpose The purpose of this paper is to examine the Houston Police Department (HPD)’s public engagement efforts using Twitter during Hurricane Harvey, which was a large-scale urban crisis event. Design/methodology/approach This study harvested a corpus of over 13,000 tweets using Twitter’s streaming API, across three phases of the Hurricane Harvey event: preparedness, response and recovery. Both text and social network analysis (SNA) techniques were employed including word clouds, n-gram analysis and eigenvector centrality to analyze data. Findings Findings indicate that departmental tweets coalesced around topics of protocol, reassurance and community resilience. Twitter accounts of governmental agencies, such as regional police departments, local fire departments, municipal offices, and the personal accounts of city’s police and fire chiefs were the most influential actors during the period under review, and Twitter was leveraged as de facto a 9-1-1 dispatch. Practical implications Emergency management agencies should consider adopting a three-phase strategy to improve communication and narrowcast specific types of information corresponding to relevant periods of a crisis episode. Originality/value Previous studies on police agencies and social media have largely overlooked discrete periods, or phases, in crisis events. To address this gap, the current study leveraged text and SNA to investigate Twitter communications between HPD and the public. This analysis advances understanding of information flows on law enforcement social media networks during crisis and emergency events