Evidence map›Paper›PMID 36531142›Full record

ArticleSN social sciences2022

Lessons for science and technology policy? Probing the Linkedin network of an RDI organisation.

Evi Sachini, Konstantinos Sioumalas-Christodoulou, Nikias Bouras, Nikolaos Karampekios

Abstract read
In one paragraph

Article in SN social sciences, 2022. 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

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.

Evi SachiniNational Documentation Centre, 48 Vas. Konstantinou Str., 11635 Athens, Greece.
Konstantinos Sioumalas-ChristodoulouNational Documentation Centre, 48 Vas. Konstantinou Str., 11635 Athens, Greece.
Nikias BourasNational Documentation Centre, 48 Vas. Konstantinou Str., 11635 Athens, Greece.
Nikolaos KarampekiosNational Documentation Centre, 48 Vas. Konstantinou Str., 11635 Athens, Greece.ORCID 0000-0002-4906-9557

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we seek to examine the network of the Greek National Documentation Centre (EKT) as formed by its LinkedIn followers. By applying specific data collection and processing techniques, we explore the network of all the individuals that follow EKT's LinkedIn page. Significant manual and automatic approaches have been implemented with regard to data extraction, data curation and data homogenization. The aim is to identify the network's advancement over time, the institutions involved and the countries. The timeframe of the study spans from when the relevant LinkedIn page was constructed in 2015 to 2020. Findings indicate that there is a steady increase in the number of new followers, peaking in 2020. On an international scale, the evolution of the network of followers is imprinted and distributed in worldwide maps. In total, 68 countries have followed EKT over the examined time period. Also, in terms of followers' institutional sector the Business Sector (BES) stands out (46.5%). Higher Education (HES) and Government Sector (GOV) are associated with 26.4 and 22.2% of the followers, respectively. Lastly, this paper provides a first institutional and country-level mapping of who constitutes the organisation's interlocutors in the national and global RDI ecosystem.

Indexed as

Data scienceGreeceLinkedInNetworkRDI systemSocial media

Identifiers

PMID36531142
PMCPMC9734916

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.