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. 2022 Dec 15;19(24):16849.
doi: 10.3390/ijerph192416849.

Disinformation: A Bibliometric Review

Shixiong Wang  1 , Fangfang Su  2 , Lu Ye  2 , Yuan Jing  1
Affiliations

Disinformation: A Bibliometric Review

Shixiong Wang et al. Int J Environ Res Public Health. .

Abstract

Objectives: This paper aimed to provide a systematic review of relevant articles from the perspectives of literature distribution, research hotspots, and existing results to obtain the frontier directions in the field of disinformation.

Methods: We analyzed disinformation publications published between 2002 and 2021 using bibliometric methods based on the Web of Science. There were 5666 papers analyzed using Derwent Data Analyzer (DDA).

Results: The result shows that the USA was the most influential country in this area, while Ecker and Lewandowsky from the University of Western Australia published the largest volumes of papers. Keywords such as "social media", "COVID-19", and "vaccination" have gained immense popularity recently.

Conclusions: We summarized four themes that are of the biggest concern to scholars: group heterogeneity of misinformation in memory, disinformation mechanism in social media, public health related to COVID-19, and application of big data technology in the infodemic. The future agenda of disinformation is summarized from three aspects: the mechanism of disinformation, social media users, and the application of algorithms. This work can be a meaningful resource for researchers' study in the area of disinformation.

Keywords: bibliometric analysis; disinformation; hot topics; keywords analysis.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Number of yearly papers in the top 20 high-yield countries/regions.
Figure 2
Figure 2
Cooperation network map of the top 20 high-yield countries/regions.
Figure 3
Figure 3
DDA cluster diagram of cooperation among the top 30 authors.
Figure 4
Figure 4
Cooperation cluster diagram of the top 30 institutions with the highest productivity.
Figure 5
Figure 5
Annual variation bubble chart of disinformation research keywords.
See this image and copyright information in PMC

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