Evidence map›Paper›PMID 33382727›Full record

ReviewPloS one2020

Rapid detection of fast innovation under the pressure of COVID-19.

Nicola Melluso, Andrea Bonaccorsi, Filippo Chiarello, Gualtiero Fantoni

Abstract readReview
In one paragraph

Review in PloS one, 2020. 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
  2. Article
  3. Managerial Responses to the Onset of the COVID-19 Pandemic in Healthcare Organizations Project Management.International journal of environmental research and public health · 2021
    Article
  4. 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

4 authors.

Nicola MellusoDepartment of Energy, Systems, Territory and Construction Engineering, School of Engineering, University of Pisa, Pisa, Italy.ORCID 0000-0003-4273-1509
Andrea BonaccorsiDepartment of Energy, Systems, Territory and Construction Engineering, School of Engineering, University of Pisa, Pisa, Italy.
Filippo ChiarelloDepartment of Energy, Systems, Territory and Construction Engineering, School of Engineering, University of Pisa, Pisa, Italy.
Gualtiero FantoniDepartment of Civil and Industrial Engineering, School of Engineering, University of Pisa, Pisa, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Covid-19 has rapidly redefined the agenda of technological research and development both for academics and practitioners. If the medical scientific publication system has promptly reacted to this new situation, other domains, particularly in new technologies, struggle to map what is happening in their contexts. The pandemic has created the need for a rapid detection of technological convergence phenomena, but at the same time it has made clear that this task is impossible on the basis of traditional patent and publication indicators. This paper presents a novel methodology to perform a rapid detection of the fast technological convergence phenomenon that is occurring under the pressure of the Covid-19 pandemic. The fast detection has been performed thanks to the use of a novel source: the online blogging platform Medium. We demonstrate that the hybrid structure of this social journalism platform allows a rapid detection of innovation phenomena, unlike other traditional sources. The technological convergence phenomenon has been modelled through a network-based approach, analysing the differences of networks computed during two time periods (pre and post COVID-19). The results led us to discuss the repurposing of technologies regarding "Remote Control", "Remote Working", "Health" and "Remote Learning".

Indexed as

COVID-19COVID-19 TestingPandemicsSARS-CoV-2TeleworkingHumans

Identifiers

PMID33382727
PMCPMC7774967

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.