Evidence map›Paper›PMID 32511492›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Extending A Chronological and Geographical Analysis of Personal Reports of COVID-19 on Twitter to England, UK.

S Golder, Ari Z Klein, Arjun Magge, Karen O'Connor, Haitao Cai, Davy Weissenbacher, Graciela Gonzalez-Hernandez

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

S GolderDepartment of Health Sciences, University of York, York YO10 5DD, UK.
Ari Z KleinDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Arjun MaggeDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Karen O'ConnorDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Haitao CaiDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Davy WeissenbacherDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Graciela Gonzalez-HernandezDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.

Funding

Social Media Mining for PharmacovigilanceR01LM011176 · NLM · UNIVERSITY OF PENNSYLVANIA · PI GONZALEZ HERNANDEZ, GRACIELA, SHEN, LI · 2012 to 2021
$4.5M
Tracking Evolution and Spread of Viral Genomes by Geospatial Observation ErrorR01AI117011 · NIAID · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI GONZALEZ HERNANDEZ, GRACIELA, SCOTCH, MATTHEW · 2016 to 2019
$1.9M
NIAID NIH HHS R01 AI117011NLM NIH HHS R01 LM011176
6 · The paper itself

Abstract

The rapidly evolving COVID-19 pandemic presents challenges for actively monitoring its transmission. In this study, we extend a social media mining approach used in the US to automatically identify personal reports of COVID-19 on Twitter in England, UK. The findings indicate that natural language processing and machine learning framework could help provide an early indication of the chronological and geographical distribution of COVID-19 in England.

Identifiers

PMID32511492
PMCPMC7273260

What OpenQuestion holds

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LicenceCC BY-ND
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Registered trials

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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.