ArticlePLoS currents2015
Twitter as a Potential Disaster Risk Reduction Tool. Part I: Introduction, Terminology, Research and Operational Applications.
Article in PLoS currents, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Assessment of the Public Health Risks and Impact of a Tornado in Funing, China, 23 June 2016: A Retrospective Analysis.International journal of environmental research and public health · 2017Article
- Twitter as a Potential Disaster Risk Reduction Tool. Part II: Descriptive Analysis of Identified Twitter Activity during the 2013 Hattiesburg F4 Tornado.PLoS currents · 2015Article
- Twitter as a Potential Disaster Risk Reduction Tool. Part IV: Competency-based Education and Training Guidelines to Promote Community Resiliency.PLoS currents · 2015Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Twitter, a popular communications platform, is identified as contributing to improved mortality and morbidity outcomes resulting from the 2013 Hattiesburg, Mississippi EF-4 Tornado. This study describes the methodology by which Twitter was investigated as a potential disaster risk reduction and management tool at the community level and the process by which the at-risk population was identified from the broader Twitter user population. By understanding how various factors contribute to the superspreading of messages, one can better optimize Twitter as an essential communications and risk reduction tool. This study introduces Parts II, III and IV which further define the technological and scientific knowledge base necessary for developing future competency base curriculum and content for Twitter assisted disaster management education and training at the community level.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.