Assessing the Intensity of the Population Affected by a Complex Natural Disaster Using Social Media Data

Cheng, Changxiu; Zhang, Ting; Su, Kuo-Lan; Gao, Peichao; Shen, Shi

doi:10.3390/ijgi8080358

Cited by 19 publications

(10 citation statements)

References 42 publications

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“…The elimination of natural hazard consequences is usually difficult due to their huge extent [1] in spatial and temporal scale, field recognition [2], and effective management [3]. Although, using some methods, such as data fusion [4] can solve some problems to some extent, issues, such as monitoring, resource management, services, financing [5], ensuring effectiveness of actions taken, reducing reacting time and delivering services, resilience [6], and creating widespread coverage with minimal resources are among the challenges that require a more robust solution.…”

Section: Introductionmentioning

confidence: 99%

Flood Management in Aqala through an Agent-Based Solution and Crowdsourcing Services in an Enterprise Geospatial Information System

Eivazy

Malek

2019

IJGI

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Propagating crowdsourcing services via a wireless network can be an appropriate solution to using the potential of crowds in crisis management processes. The present study aimed to deploy crowdsourcing services properly to spatial urgent requests. Composing such atomic services can conquer sophisticated crisis management. In addition, the conducted propagated services guide people through crisis fields and allow managers to use crowd potential appropriately. The use of such services requires a suitable automated allocation method, along with a proper approach to arranging the sequence of propagating services. The solution uses a mathematical framework in the context of a GIS (Geospatial Information System) in order to construct an allocation approach. Solution elements are set out in a multi-agent environment structure, which simulate disaster field objects. Agents which are dynamically linked to objects in a crisis field, interact with each other in a competitive environment, and the results in forming crowdsourcing services are used to guide crowds in the crisis field via the crowdsourcing services. The present solution was implemented through a proper data schema in a powerful geodatabase, along with various users with specialized interfaces. Finally, a solution and crowdsourcing service was tested in the context of a GIS in the 2019 Aqala flood disaster in Iran and other complement scenarios. The allocating performance and operation of other system elements were acceptable and reduced indicators, such as rescuer fatigue and delay time. Crowdsourcing service was positioned well in the solution and provided good performance among the elements of the Geospatial Information System.

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Section: Introductionmentioning

confidence: 99%

Flood Management in Aqala through an Agent-Based Solution and Crowdsourcing Services in an Enterprise Geospatial Information System

Eivazy

Malek

2019

IJGI

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“…Unfortunately, the cross-sectional nature of this study did not allow us to evaluate the evolution of these impacts over time or to establish a causal link. Survey data are relatively static, hindering the possibility of observing the evolution of the impacts of floods [ 40 ]. This research project does, however, contain a second phase, thanks to participants who agreed to be recontacted for another survey a few months after this study.…”

Section: Discussionmentioning

confidence: 99%

Respiratory and Otolaryngology Symptoms Following the 2019 Spring Floods in Quebec

Landaverde

Généreux

Maltais

et al. 2022

IJERPH

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Background: Although floods may have important respiratory health impacts, few studies have examined this issue. This study aims to document the long-term impacts of the spring floods of 2019 in Quebec by (1) describing the population affected by the floods; (2) assessing the impacts on the respiratory system according to levels of exposure; and (3) determining the association between stressors and respiratory health. Methods: A population health survey was carried out across the six most affected regions 8–10 months post-floods. Data were collected on self-reported otolaryngology (ENT) and respiratory symptoms, along with primary and secondary stressors. Three levels of exposure were examined: flooded, disrupted and unaffected. Results: One in ten respondents declared being flooded and 31.4% being disrupted by the floods. Flooded and disrupted participants reported significantly more ENT symptoms (adjusted odds ratio (aOR): 3.18; 95% CI: 2.45–4.14; aOR: 1.76; 95% CI: 1.45–2.14) and respiratory symptoms (aOR: 3.41; 95% CI: 2.45–4.75; aOR: 1.45; 95% CI: 1.10–1.91) than the unaffected participants. All primary stressors and certain secondary stressors assessed were significantly associated with both ENT and respiratory symptoms, but no “dose–response” gradient could be observed. Conclusion: This study highlights the long-term adverse effects of flood exposure on respiratory health.

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“…In most cases, the sub-events referred in the tweet have a corresponding hashtag associated with it. The hashtag intensity (HI) for a particular sub-event s on a given day x is given by Equation (10).…”

Section: Sub-event Intensity By Normalized Averaging Of Intensity Com...mentioning

confidence: 99%

Temporal intensity modeling of sub‐events in microblogs

Vijayakumar

2022

Concurrency and Computation

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Summary Social media has evolved into a conventional source of obtaining and tracking news events in the digital world. Most news events constitute a flow of sub‐events, that are distinct and independent events, related to the same base news event. These sub‐events have the potential to alter the course of the news event and also the emotional responses toward the news event entirely. Discovering the intensity of user attention toward sub‐events at set points of time, aids in modeling the evolution of sub‐events and consecutively, the news event as a whole. This work proposes two methodologies for day‐to‐day temporal analysis of sub‐events: a top‐down approach based on the significance of hashtags and a bottom‐up approach based on the combined intensity of components such as hashtags and tweet content. In comparison, the approach based on the combined intensity of components proves very promising in representing the temporal intensity of sub‐events.

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Assessing the Intensity of the Population Affected by a Complex Natural Disaster Using Social Media Data

Cited by 19 publications

References 42 publications

Flood Management in Aqala through an Agent-Based Solution and Crowdsourcing Services in an Enterprise Geospatial Information System

Flood Management in Aqala through an Agent-Based Solution and Crowdsourcing Services in an Enterprise Geospatial Information System

Respiratory and Otolaryngology Symptoms Following the 2019 Spring Floods in Quebec

Temporal intensity modeling of sub‐events in microblogs

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