Understanding social media data for disaster management

Xiao, Yu; Huang, Qunying; Kai, Wu

doi:10.1007/s11069-015-1918-0

Cited by 136 publications

(82 citation statements)

References 16 publications

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“…identifying topicality) within unstructured or semi-structured web-harvested data, unknown quality (there may be little or no relevant metadata), and difficulty integrating it with other sources (which may in turn have their own issues of quality and uncertainty). When using social media, biases may also be present, for example, from a lack of digital engagement within certain demographics of the populations of particular areas (Xiao et al 2015). Panteras et al (2014) cross-reference geotagged points of images mined from Flickr and tweets to estimate spatial footprints events.…”

Section: Social Mediamentioning

confidence: 99%

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Rapid flood inundation mapping using social media, remote sensing and topographic data

2017

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Flood events cause substantial damage to urban and rural areas. Monitoring water extent during large-scale flooding is crucial in order to identify the area affected and to evaluate damage. During such events, spatial assessments of floodwater may be derived from satellite or airborne sensing platforms. Meanwhile, an increasing availability of smartphones is leading to documentation of flood events directly by individuals, with information shared in real-time using social media. Topographic data, which can be used to determine where floodwater can accumulate, are now often available from national mapping or governmental repositories. In this work, we present and evaluate a method for rapidly estimating flood inundation extent based on a model that fuses remote sensing, social media and topographic data sources. Using geotagged photographs sourced from social media, optical remote sensing and high-resolution terrain mapping, we develop a Bayesian statistical model to estimate the probability of flood inundation through weights-of-evidence analysis. Our experiments were conducted using data collected during the 2014 UK flood event and focus on the Oxford city and surrounding areas. Using the proposed technique, predictions of inundation were evaluated against ground-truth flood extent. The results report on the quantitative accuracy of the multisource mapping process, which obtained area under receiver operating curve values of 0.95 and 0.93 for model fitting and testing, respectively.

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Section: Social Mediamentioning

confidence: 99%

“…However, despite much interest in using such sources in natural hazard assessment (Goodchild and Glennon 2010), exploiting this information is not trivial. The data usually have no validation or assessment of quality (Goodchild and Li 2012) and may contain deliberate or unintended bias (Xiao et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Rapid flood inundation mapping using social media, remote sensing and topographic data

2017

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“…Social data have proven enormously useful in emergency situations (Xiao et al. ) and results can be filtered by a user‐specified text‐string or hashtag to find images, videos, live camera feeds, hyperlinks, and commentaries for evolving hazards.…”

Section: The Floodhippo Prototypementioning

confidence: 99%

Challenges and Opportunities for Creating Intelligent Hazard Alerts: The “FloodHippo” Prototype

Johnson

Coll

Ruess

et al. 2018

J American Water Resour Assoc

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Disasters evolving from hazards are a persistent and deadly occurrence in the United States. Despite this, hazard alerts have remained spatially vague, temporally imprecise, and lack actionable information. These deficiencies indicate a divide between the status quo and what is possible given modern environmental models, geographic information systems (GIS), and smartphone capabilities. This work describes an alternative, prototype system, “FloodHippo,” which integrates operational model outputs, cloud‐based GIS, and expanded communication channels to provide personal and interactive disaster alerts for floods. The precepts and methods underpinning FloodHippo apply equally to other disasters that evolve over space and time, presenting the opportunity for a more intelligent disaster response system. The development of such a system would not only minimize current shortcomings in disaster alerts but also improve resilience through individual action, along with community, academic, and federal cooperation.

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“…Although social media is frequently effectively used during natural disasters, it must be recognised that it has various limitations, for example, issues relating to data quality. When critical information are submitted by civilians, agencies are required to verify its content in order to limit the dissemination of inaccurate information (Alexander, ; Rizza and Pereira, ; Takahashi et al, ; Xiao et al, ). Due to the volume and speed of information generated, particularly on Twitter (Herfort et al, ), verification procedures can be lengthy, consequently the transmission of critical information is often delayed (Chavez et al, ; Ehnis and Bunker, ; Kavanaugh et al, ; Alexander, ; Fritze and Kray, ).…”

Section: Introductionmentioning

confidence: 99%

The role of Facebook and Twitter as organisational communication platforms in relation to flood events in Northern Ireland

Stephenson¹,

Vaganay²,

Coon³

et al. 2017

J Flood Risk Management

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Social media networks enable flood‐affected individuals to obtain and share credible information; however, their full potential is not recognised by official institutions. This study evaluates flood‐related usage of Facebook and Twitter by organisations in Northern Ireland. Data collection involved extraction of publicly visible flood‐related Facebook and Twitter posts, over a 9‐month period, from official accounts of selected organisations. NVivo was used to conduct a content analysis of the data. The results concluded that flood‐related information are predominantly distributed at the flood response stage, illustrating the present reactive social media presence of organisations. Twitter accounted for a higher proportion of broadcasting information, while Facebook was more likely to encourage specific behaviour. Public preference was associated with information provided by emergency services and information transmitted at the response stage. Policy implications include the need for an established proactive social media presence among organisations with a flood‐related function and community consultation to identify public information needs.

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Understanding social media data for disaster management

Cited by 136 publications

References 16 publications

Rapid flood inundation mapping using social media, remote sensing and topographic data

Rapid flood inundation mapping using social media, remote sensing and topographic data

Challenges and Opportunities for Creating Intelligent Hazard Alerts: The “FloodHippo” Prototype

The role of Facebook and Twitter as organisational communication platforms in relation to flood events in Northern Ireland

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