Evidence map›Paper›PMID 38322879›Full record

ArticleHeliyon2024

Fake news research trends, linkages to generative artificial intelligence and sustainable development goals.

Raghu Raman, Vinith Kumar Nair, Prema Nedungadi, Aditya Kumar Sahu, Robin Kowalski, Sasangan Ramanathan, Krishnashree Achuthan

Abstract readNews
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

7 authors.

Raghu RamanAmrita School of Business, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, 690525, India.
Vinith Kumar NairAmrita School of Business, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, 690525, India.
Prema NedungadiAmrita School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, 690525, India.
Aditya Kumar SahuAmrita School of Computing, Amrita Vishwa Vidyapeetham, Amaravati, Andhra Pradesh, 522503, India.
Robin KowalskiCollege of Behavioral, Social and Health Sciences, Clemson University, Clemson, SC, 29634, USA.
Sasangan RamanathanAmrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, Tamilnadu, 641112, India.
Krishnashree AchuthanCenter for Cybersecurity Systems and Networks, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, 690525, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the digital age, where information is a cornerstone for decision-making, social media's not-so-regulated environment has intensified the prevalence of fake news, with significant implications for both individuals and societies. This study employs a bibliometric analysis of a large corpus of 9678 publications spanning 2013-2022 to scrutinize the evolution of fake news research, identifying leading authors, institutions, and nations. Three thematic clusters emerge: Disinformation in social media, COVID-19-induced infodemics, and techno-scientific advancements in auto-detection. This work introduces three novel contributions: 1) a pioneering mapping of fake news research to Sustainable Development Goals (SDGs), indicating its influence on areas like health (SDG 3), peace (SDG 16), and industry (SDG 9); 2) the utilization of Prominence percentile metrics to discern critical and economically prioritized research areas, such as misinformation and object detection in deep learning; and 3) an evaluation of generative AI's role in the propagation and realism of fake news, raising pressing ethical concerns. These contributions collectively provide a comprehensive overview of the current state and future trajectories of fake news research, offering valuable insights for academia, policymakers, and industry.

Indexed as

Deep fakeEthicsFake newsGenerative AIProminence percentileSustainable development goal

Identifiers

PMID38322879
PMCPMC10844021

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.