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Coronavirus Goes Viral: Quantifying the COVID-19 Misinformation Epidemic on Twitter

Overview of attention for article published in Cureus, March 2020
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
10 news outlets
blogs
1 blog
policy
2 policy sources
twitter
81 X users

Citations

dimensions_citation
676 Dimensions

Readers on

mendeley
754 Mendeley
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Title
Coronavirus Goes Viral: Quantifying the COVID-19 Misinformation Epidemic on Twitter
Published in
Cureus, March 2020
DOI 10.7759/cureus.7255
Pubmed ID
Authors

Ramez Kouzy, Joseph Abi Jaoude, Afif Kraitem, Molly B El Alam, Basil Karam, Elio Adib, Jabra Zarka, Cindy Traboulsi, Elie W Akl, Khalil Baddour

Abstract

Background Since the beginning of the coronavirus disease 2019 (COVID-19) epidemic, misinformation has been spreading uninhibited over traditional and social media at a rapid pace. We sought to analyze the magnitude of misinformation that is being spread on Twitter (Twitter, Inc., San Francisco, CA) regarding the coronavirus epidemic.  Materials and methods We conducted a search on Twitter using 14 different trending hashtags and keywords related to the COVID-19 epidemic. We then summarized and assessed individual tweets for misinformation in comparison to verified and peer-reviewed resources. Descriptive statistics were used to compare terms and hashtags, and to identify individual tweets and account characteristics. Results The study included 673 tweets. Most tweets were posted by informal individuals/groups (66%), and 129 (19.2%) belonged to verified Twitter accounts. The majority of included tweets contained serious content (91.2%); 548 tweets (81.4%) included genuine information pertaining to the COVID-19 epidemic. Around 70% of the tweets tackled medical/public health information, while the others were pertaining to sociopolitical and financial factors. In total, 153 tweets (24.8%) included misinformation, and 107 (17.4%) included unverifiable information regarding the COVID-19 epidemic. The rate of misinformation was higher among informal individual/group accounts (33.8%, p: <0.001). Tweets from unverified Twitter accounts contained more misinformation (31.0% vs 12.6% for verified accounts, p: <0.001). Tweets from healthcare/public health accounts had the lowest rate of unverifiable information (12.3%, p: 0.04). The number of likes and retweets per tweet was not associated with a difference in either false or unverifiable content. The keyword "COVID-19" had the lowest rate of misinformation and unverifiable information, while the keywords "#2019_ncov" and "Corona" were associated with the highest amount of misinformation and unverifiable content respectively. Conclusions Medical misinformation and unverifiable content pertaining to the global COVID-19 epidemic are being propagated at an alarming rate on social media. We provide an early quantification of the magnitude of misinformation spread and highlight the importance of early interventions in order to curb this phenomenon that endangers public safety at a time when awareness and appropriate preventive actions are paramount.

X Demographics

X Demographics

The data shown below were collected from the profiles of 81 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 754 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 754 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 102 14%
Student > Master 94 12%
Researcher 80 11%
Student > Ph. D. Student 65 9%
Student > Doctoral Student 41 5%
Other 138 18%
Unknown 234 31%
Readers by discipline Count As %
Medicine and Dentistry 97 13%
Social Sciences 91 12%
Computer Science 66 9%
Psychology 32 4%
Nursing and Health Professions 29 4%
Other 162 21%
Unknown 277 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 152. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 January 2023.
All research outputs
#279,037
of 25,974,666 outputs
Outputs from Cureus
#257
of 26,508 outputs
Outputs of similar age
#8,055
of 392,719 outputs
Outputs of similar age from Cureus
#8
of 505 outputs
Altmetric has tracked 25,974,666 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 26,508 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.1. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 392,719 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 505 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.