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Between Monday 04 May 2020 and Monday 11 May 2020, misinformation about Spread has increasead whereas misinformation about Causes has reduced.

The Fact-checking Observatory is an automatic service that collects misinforming content on Twitter using URLs that have been identified as potential misinformation by fact-checking websites. Using this data, the Fact-checking Observatory automatically generates weekly reports that updates the state of misinformation spread of fact-checked misinformation on Twitter.

This analysis is limited to URLs identified by Fact-checking organisations. The collected data only consist of non-blocked Twitter content and may be incomplete.

This report updates the status of misinformation spread between Monday 04 May 2020 and Monday 11 May 2020.

214,127 Misinforming Tweets
New:+6,988 Trend:-3,735
58,535 Fact-checking Tweets
New:+4,245 Trend:+54
10,803 Fact-checks
98 Fact-checking Organisations

Key Content and Topics

During the period between Monday 04 May 2020 and Monday 11 May 2020, 6,988 new URLs have been identified as potential misinforming content. Out of the 7 topics identified by Fact-checking organisations (Figure 1), most of the new shared URLs were about Spread with an increase of +4,818 compared to the previous total spread for the same topic. The topic that saw the least increase in spread compared to the previous period total spread was Symptoms with a change of +17 compared to the previous total spread for the same topic.

The topics used for the analysis are obtained from the COVID-19 specific fact-check alliance database and are defined as follows:

  1. Authorities: Information relating to government or authorities communication and general involvement during the COVID-19 pandemic (e.g., crime, government, aid, lockdown).
  2. Causes: Information about the virus causes and outbreaks (e.g., China, animals).
  3. Conspiracy theories: COVID-19-related conspiracy theories (e.g., 5G, biological weapon).
  4. Cures: Information about potential virus cures (e.g., vaccines, hydroxychloroquine, bleach).
  5. Spread: Information relating to the spread of COVID-19 (e.g., travel, animals).
  6. Symptoms: Information relating to symptoms and symptomatic treatments of COVID-19 (e.g., cough, sore throat).
  7. Other: Any topic that does not fit directly the aforementioned categories.

In relation to the previous week, the topic that saw the biggest relative spread change was Spread with a change of +4,290 compared to the previous total spread for the same topic whereas the topic that saw the least relative change was Spread with a change of -5,806 compared to the previous period.

The all time most important topic is Other with a total of 79,739 URL shares and the least popular topic is Symptoms with 2,158 shares (Figure 2).

Figure 1: Topic Importance.

Figure 2: Amount of topic shares per week.

The top misinforming content and fact-checking articles shared since the last report are listed in Table 1 and Table 2.

Misinforming URL Fact-check URL Topic Current Week Previous Week Total
https://www.latimes.com/california/story/2020-05-05/mutant-coronavirus-has-emerged-more-contagious-than-original Détecteur de rumeurs Spread 4536 0 4536
https://www.worldometers.info/ Agencia Ocote Authorities 779 1031 14544
https://www.lastampa.it/esteri/2020/05/04/news/test-sul-sangue-effettuati-in-giappone-rivela-la-mortalita-da-coronavirus-e-di-gran-lunga-inferiore-all-influenza-1.38801430 Open Other 241 0 241
https://twitter.com/Ievyrincon/status/1257882451982024707 La Silla Vacía Other 140 0 140
https://www.freep.com/story/news/2020/05/05/michigan-capitol-building-protest-picture/3084192001/ PolitiFact Other 111 0 111
https://twitter.com/mikandynothem/status/1259556010408075264 PolitiFact Authorities 96 0 96
https://www.youtube.com/watch?v=eQVYMWY9g24 LeadStories Authorities 62 0 62
https://www.youtube.com/watch?v=dQkgXabo-A0 Maldita.es Conspiracy Theory 43 167 1216
https://www.the-scientist.com/news-opinion/lab-made-coronavirus-triggers-debate-34502 LeadStories Conspiracy Theory 43 63 1582
https://www.dailytelegraph.com.au/lifestyle/health/coronavirus-nsw-dossier-lays-out-case-against-china-bat-virus-program/news-story/e1833c0893bfdac16d21dca6ce364bfb Factcheck.kz Conspiracy Theory 41 35 76

Table 1: Top misinforming content.

Fact-check URL Topic Current Week Previous Week Total
https://www.washingtonpost.com/politics/2020/05/06/trump-campaigns-egregious-editing-cnn-clip/ Other 338 0 338
https://www.lemonde.fr/les-decodeurs/article/2020/05/05/non-les-marins-du-charles-de-gaulle-n-ont-pas-ete-gueris-a-la-chloroquine_6038720_4355770.html Cure 191 0 191
https://www.washingtonpost.com/politics/2020/05/05/fact-checking-trumps-knocks-obama-his-fox-town-hall/ Authorities 159 0 159
https://www.factcheck.org/2020/05/the-falsehoods-of-the-plandemic-video/ Conspiracy Theory 135 0 135
https://www.washingtonpost.com/politics/2020/05/08/jimmy-kimmels-false-claim-that-pence-carried-empty-boxes/ Other 117 0 117
https://www.factcheck.org/2020/05/cdc-hasnt-reduced-covid-19-death-toll/ Authorities 112 0 112
https://www.politifact.com/factchecks/2020/may/07/lincoln-project/mourning-america-ad-critical-trump-misleads-bailou/ Authorities 86 0 86
https://www.politifact.com/factchecks/2020/apr/08/donald-trump/trump-said-obama-admin-left-him-bare-stockpile-wro/ Other 69 44 324
https://www.politifact.com/factchecks/2020/apr/23/facebook-posts/anti-vaxxers-spread-conspiracy-about-bill-gates-an/ Conspiracy Theory 60 2 62
https://factuel.afp.com/les-marins-du-charles-de-gaulle-contamines-par-le-covid-19-traites-la-chloroquine-larmee-dement Cure 59 0 59

Table 2: Top fact-checked content.


The data used for creating the Twitter dataset is obtained from the Poynter Coronavirus Fact Alliance. The alliance consists of 98 fact-checking organisation based in 635 countries and covering 46 languages.

The largest amount of fact-checked content comes from English (6,130 fact-checks) and the least is Finland (1 fact-checks). Most fact-checked content is in Spanish (3,367) followed by Portuguese (1,998) and French (963) (Figure 3).

Figure 3: Amount of fact-checks by language.

Figure 4: Amount of fact-checked content per contry.

Determining a direct impact of fact-checking on the spread of misinformation is not easy. However, it is possible to determine how well a particular corrective information is spreading in relation to its corresponding misinformation.

Figure 5 shows how misinformation and fact-checking content has spread in various topics for the last two analysis periods and overall.

Figure 5: Topical misinformation and fact-checks spread.

Demographic Impact

Using automatic methods, Twitter account demographics are extracted for user age, gender and account type (i.e., identify if an account belong to an individual or organisation).

Figure 6 displays how misinformation and fact-checks are spread by different demographics.

Figure 6: Misinformation and Fact-check spread for different demographics. Top: Gender, Center: Age group, Bottom: Account type.

Data Collection and Methodology

The full methodology and information about the limitation and dataset used for this analysis can be accessed in the [methodology page](https://fcobservatory.org/faq/).