Evidence map›Paper›PMID 35308061›Full record

ArticleApplied network science2022

Sustainable development goals: conceptualization, communication and achievement synergies in a complex network framework.

Loredana Bellantuono, Alfonso Monaco, Nicola Amoroso, Vincenzo Aquaro, Angela Lombardi, Sabina Tangaro, Roberto Bellotti

Abstract read
In one paragraph

Article in Applied network science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Loredana BellantuonoDipartimento di Scienze Mediche di Base, Neuroscienze e Organi di Senso, Università degli studi di Bari Aldo Moro, 70126 Bari, Italy.
Alfonso MonacoIstituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125 Bari, Italy.
Nicola AmorosoIstituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125 Bari, Italy.ORCID 0000-0003-0211-0783
Vincenzo AquaroDivision for Public Institutions and Digital Government, United Nations Department of Economic and Social Affairs (DESA), New York, NY 10017 USA.
Angela LombardiIstituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125 Bari, Italy.
Sabina TangaroIstituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125 Bari, Italy.
Roberto BellottiIstituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125 Bari, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this work we use a network-based approach to investigate the complex system of interactions among the 17 Sustainable Development Goals (SDGs), that constitute the structure of the United Nations 2030 Agenda for a sustainable future. We construct a three-layer multiplex, in which SDGs represent nodes, and their connections in each layer are determined by similarity definitions based on conceptualization, communication, and achievement, respectively. In each layer of the multiplex, we investigate the presence of nodes with high centrality, corresponding to strategic SDGs. We then compare the networks to establish whether and to which extent similar patterns emerge. Interestingly, we observe a significant relation between the SDG similarity patterns determined by their achievement and their communication and perception, revealed by social network data. The proposed framework represents an instrument to unveil new and nontrivial aspects of sustainability, laying the foundation of a decision support system to define and implement SDG achievement strategies.

Indexed as

Community detectionComplex networksMultilayer networksNatural language processingSocial networksSustainabilitySustainable development goals

Identifiers

PMID35308061
PMCPMC8919151

What OpenQuestion holds

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LicenceCC BY
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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.