Evidence map›Paper›PMID 26203396›Full record

ArticlePLoS currents2015

Twitter as a Potential Disaster Risk Reduction Tool. Part II: Descriptive Analysis of Identified Twitter Activity during the 2013 Hattiesburg F4 Tornado.

Guy Paul Cooper, Violet Yeager, Frederick M Burkle, Italo Subbarao

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Guy Paul CooperCollege of Osteopathic Medicine, William Carey University, Hattiesburg, Mississippi, USA.
Violet YeagerCollege of Osteopathic Medicine, William Carey University, Hattiesburg, Mississippi, USA.
Frederick M BurkleHarvard Humanitarian Initiative, Harvard University, Cambridge, Massachusetts; The Woodrow Wilson International Center for Scholars, Washington, DC, USA.
Italo SubbaraoCollege of Osteopathic Medicine, William Carey University, Hattiesburg, Mississippi, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis article describes a novel triangulation methodological approach for identifying twitter activity of regional active twitter users during the 2013 Hattiesburg EF-4 Tornado. METHODOLOGY: A data extraction and geographically centered filtration approach was utilized to generate Twitter data for 48 hrs pre- and post-Tornado. The data was further validated using six sigma approach utilizing GPS data.

resultsThe regional analysis revealed a total of 81,441 tweets, 10,646 Twitter users, 27,309 retweets and 2637 tweets with GPS coordinates.

conclusionsTwitter tweet activity increased 5 fold during the response to the Hattiesburg Tornado.  Retweeting activity increased 2.2 fold. Tweets with a hashtag increased 1.4 fold. Twitter was an effective disaster risk reduction tool for the Hattiesburg EF-4 Tornado 2013.

Indexed as

CommunicationsDisaster analysisDisaster risk reductionPrevention and preparednessSocial mediaTwitter

Identifiers

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.