Processing Social Media Messages in Mass Emergency

Imran, Muhammad; Castillo, Carlos; Dı́az, Fernando; Vieweg, Sarah

doi:10.1145/3184558.3186242

Cited by 206 publications

(279 citation statements)

References 23 publications

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“…Some simple methods mentioned within these different functions included mapping the evolution of tweets over an event or the use of heat maps and building a Twitter listening tool that can be used to dispatch responders to a person in need. The latter tool requires reasonably sophisticated methods for filtering the data, which are described in detail in papers by Barbier et al () and Imran et al (). For example, both papers describe different methods for data preprocessing.…”

Section: Review Of Issues Associated With Crowdsourcing Applicationsmentioning

confidence: 99%

Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions

Zheng

Tao

Maier

et al. 2018

Reviews of Geophysics

113

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Data are essential in all areas of geophysics. They are used to better understand and manage systems, either directly or via models. Given the complexity and spatiotemporal variability of geophysical systems (e.g., precipitation), a lack of sufficient data is a perennial problem, which is exacerbated by various drivers, such as climate change and urbanization. In recent years, crowdsourcing has become increasingly prominent as a means of supplementing data obtained from more traditional sources, particularly due to its relatively low implementation cost and ability to increase the spatial and/or temporal resolution of data significantly. Given the proliferation of different crowdsourcing methods in geophysics and the promise they have shown, it is timely to assess the state of the art in this field, to identify potential issues and map out a way forward. In this paper, crowdsourcing‐based data acquisition methods that have been used in seven domains of geophysics, including weather, precipitation, air pollution, geography, ecology, surface water, and natural hazard management, are discussed based on a review of 162 papers. In addition, a novel framework for categorizing these methods is introduced and applied to the methods used in the seven domains of geophysics considered in this review. This paper also features a review of 93 papers dealing with issues that are common to data acquisition methods in different domains of geophysics, including the management of crowdsourcing projects, data quality, data processing, and data privacy. In each of these areas, the current status is discussed and challenges and future directions are outlined.

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Section: Review Of Issues Associated With Crowdsourcing Applicationsmentioning

confidence: 99%

Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions

Zheng

Tao

Maier

et al. 2018

Reviews of Geophysics

113

View full text Add to dashboard Cite

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“…To alleviate the adverse effects of uninformative words and characters, the filtered data should be preprocessed. The preprocessing approaches that are used commonly in existing studies include lowercase (lower case every letter in the tweet), tokenization (split the tweets as a set of tokens), stop‐words removal (remove some words that commonly appear in other documents), and lemmatization (return the base or dictionary form of a word) (Imran, Castillo, Diaz, & Vieweg, ; Zhang, He, Gao, & Ni, ). In addition, in this study, we not only use these common preprocessing approaches, but also employ regular expressions to remove the punctuation, URLs, and emojis.…”

Section: A Graph‐based Computational Methodsmentioning

confidence: 99%

A graph‐based method for social sensing of infrastructure disruptions in disasters

Fan

Mostafavi

2019

Computer aided Civil Eng

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Damages in critical infrastructure occur abruptly, and disruptions evolve with time dynamically. Understanding the situation of critical infrastructure disruptions is essential to effective disaster response and recovery of communities. Although the potential of social media data for situation awareness during disasters has been investigated in recent studies, the application of social sensing in detecting disruptions and analyzing evolutions of the situation about critical infrastructure is limited. To address this limitation, this study developed a graph‐based method for detecting credible situation information related to infrastructure disruptions in disasters. The proposed method was composed of data filtering, burst time‐frame detection, content similarity calculation, graph analysis, and situation evolution analysis. The application of the proposed method was demonstrated in a case study of Hurricane Harvey in 2017 in Houston. The findings highlighted the capability of the proposed method in detecting credible situational information and capturing the temporal and spatial patterns of critical infrastructure events that occurred in Harvey, including disruptive events and their adverse impacts on communities. The proposed methodology can improve the ability of community members, volunteer responders, and decision makers to detect and respond to infrastructure disruptions in disasters.

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“…However, there are a number of challenges to using social media in risk management, such as the real‐time analysis and monitoring of social media streams. Authors of a study discuss processing and managing social media data concerning emergency events. The paper defines challenges according to 2 main high‐level categories: (1) scalability, recording millions of messages and storing multimedia objects (eg, images and videos); and (2) content, social media and microblogging messages particularly are brief and informal, which may lead to poor results.…”

Section: Social Media Use In Emergenciesmentioning

confidence: 99%

Using Twitter and the mobile cloud for delivering medical help in emergencies

Alshareef

Grigoraş

2017

Concurrency and Computation

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Summary Emergency events require a fast response and decisions based on first‐hand information. This paper presents a mobile cloud service that makes the best use of social media applications, such as Twitter, in emergency and risk management. Here, risk and emergency teams can receive data that can inform their decisions in a matter of seconds when an emergency has affected areas under their management. The proposed service allows users to provide on‐the‐ground information regarding such an event, as well as early notification to people who are in the vicinity of an emergency situation. The service matches users' requests to a set of predefined labels that will help rescuers to understand the situation more clearly. The service was implemented and tested with Android devices and a cloud‐computing instance hosted on an Amazon platform. A cloud‐based tool is also provided for risk and emergency management teams to interact with users' requests. The experimental results show that the proposed mobile cloud service enhanced the early detection of emergencies. This paper also provides a review of research papers on the use of social media in risk and emergency management and the benefits of integrating social media with mobile cloud computing to provide a better healthcare service in emergencies.

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Processing Social Media Messages in Mass Emergency

Cited by 206 publications

References 23 publications

Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions

Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions

A graph‐based method for social sensing of infrastructure disruptions in disasters

Using Twitter and the mobile cloud for delivering medical help in emergencies

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