Evidence map›Paper›PMID 36001556›Full record

ArticlePloS one2022

Analyzing preventive precautions to limit spread of COVID-19.

Ayaz Ahmad, Furqan Rustam, Eysha Saad, Muhammad Abubakar Siddique, Ernesto Lee, Arturo Ortega Mansilla, Isabel de la Torre Díez, Imran Ashraf

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

8 authors.

Ayaz AhmadDepartment of Computer Science, Khawaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan.
Furqan RustamDepartment of Software Engineering, School of Systems and Technology, University of Management and Technology Lahore, Lahore, Pakistan.
Eysha SaadDepartment of Computer Science, Khawaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan.ORCID 0000-0003-3034-961X
Muhammad Abubakar SiddiqueDepartment of Computer Science, Khawaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan.
Ernesto LeeDepartment of Computer Science, Broward College, Broward County, Florida, United States of America.
Arturo Ortega MansillaEuropean University of The Atlantic, Santander, Spain.
Isabel de la Torre DíezDepartment of Signal Theory and Communications and Telematic Engineering, Unviersity of Valladolid, Valladolid, Spain.
Imran AshrafInformation and Communication Engineering, Yeungnam University, Gyeongsan, Korea.ORCID 0000-0002-8271-6496

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the global spread of COVID-19, the governments advised the public for adopting safety precautions to limit its spread. The virus spreads from people, contaminated places, and nozzle droplets that necessitate strict precautionary measures. Consequently, different safety precautions have been implemented to fight COVID-19 such as wearing a facemask, restriction of social gatherings, keeping 6 feet distance, etc. Despite the warnings, highlighted need for such measures, and the increasing severity of the pandemic situation, the expected number of people adopting these precautions is low. This study aims at assessing and understanding the public perception of COVID-19 safety precautions, especially the use of facemask. A unified framework of sentiment lexicon with the proposed ensemble EB-DT is devised to analyze sentiments regarding safety precautions. Extensive experiments are performed with a large dataset collected from Twitter. In addition, the factors leading to a negative perception of safety precautions are analyzed by performing topic analysis using the Latent Dirichlet allocation algorithm. The experimental results reveal that 12% of the tweets correspond to negative sentiments towards facemask precaution mainly by its discomfort. Analysis of change in peoples' sentiment over time indicates a gradual increase in the positive sentiments regarding COVID-19 restrictions.

Indexed as

COVID-19Social MediaHumansPandemics

Identifiers

PMID36001556
PMCPMC9401132

What OpenQuestion holds

Textmetadata
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.