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Between Monday 30 November 2020 and Monday 07 December 2020, misinformation about Vaccine has increasead whereas misinformation about Authorities 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 30 November 2020 and Monday 07 December 2020.

251,574 Misinforming Tweets
New:+550 Trend:+13
108,078 Fact-checking Tweets
New:+1,111 Trend:+229
10,803 Fact-checks
98 Fact-checking Organisations

Key Content and Topics

During the period between Monday 30 November 2020 and Monday 07 December 2020, 550 new URLs have been identified as potential misinforming content. Out of the 8 topics identified by Fact-checking organisations (Figure 1), most of the new shared URLs were about Authorities with an increase of +467 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 +12 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 +134 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 -88 compared to the previous period.

The all time most important topic is Authorities with a total of 102,602 URL shares and the least popular topic is Vaccine with 1,161 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.worldometers.info/ Agencia Ocote Authorities 263 280 28025
https://www.youtube.com/watch?v=6y2I0xAPSQk MediaWise Vaccine 71 0 71
https://www.cdc.gov/mmwr/volumes/69/wr/mm6936a5.htm Détecteur de rumeurs Other 46 75 1249
https://www.nytimes.com/2020/11/29/health/should-covid-19-isolation-periods-be-shorter.html?referringSource=articleShare Détecteur de rumeurs Other 22 7 29
https://childrenshealthdefense.org/news/vaccine-trial-catastrophe-moderna-vaccine-has-20-serious-injury-rate-in-high-dose-group/ Facta Vaccine 20 4 401
https://www.youtube.com/watch?v=p_AyuhbnPOI Faktograf Other 14 11 3740
https://www.facebook.com/108550254295068/videos/2878752842448976 Animal Político Conspiracy Theory 12 0 12
https://cienciaysaludnatural.com/estudio-demuestra-que-los-asintomaticos-no-contagian-el-coronavirus/ Animal Político Conspiracy Theory 10 40 51
https://traugott-ickeroth.com/liveticker/ Correctiv Conspiracy Theory 9 4 328
https://www.lavanguardia.com/vida/20201203/49856183174/oms-recomienda-no-usar-mascarilla-ejercicio-fisico-intenso-video-seo-ext.html Maldita.es Authorities 8 0 8

Table 1: Top misinforming content.

Fact-check URL Topic Current Week Previous Week Total
https://healthfeedback.org/claimreview/cdc-data-shows-higher-number-of-deaths-in-2020-compared-to-previous-years-johns-hopkins-student-article-compared-percentages-not-raw-numbers/ Spread 58 0 58
https://healthfeedback.org/claimreview/a-rise-in-the-number-of-covid-19-cases-and-deaths-starting-in-september-2020-contradicts-the-claim-by-michael-yeadon-that-the-pandemic-is-fundamentally-over-in-the-u-k/ Spread 41 37 103
https://www.politifact.com/factchecks/2020/dec/02/blog-posting/former-pfizer-employee-wrong-coronavirus-pandemic-/ Spread 36 0 36
https://infact.press/2020/06/post-6304/ Causes 30 28 206
https://www.politifact.com/factchecks/2020/may/21/facebook-posts/disposable-homemade-masks-are-effective-stopping-a/ Spread 26 12 751
https://factcheck.afp.com/canadian-doctor-falsely-claims-pandemic-hoax Conspiracy Theory 24 0 24
https://www.aap.com.au/the-us-isnt-headed-for-fewer-deaths-in-2020-with-covid-19/ Spread 21 10 57
https://factuel.afp.com/sida-40-ans-0-vaccin-covid-10-mois-9-vaccins-attention-cette-comparaison-trompeuse Conspiracy Theory 21 0 21
https://piaui.folha.uol.com.br/lupa/2020/12/03/verificamos-vacina-covid-dna/ Vaccine 17 0 17
https://www.factcheck.org/2020/09/cdc-did-not-admit-only-6-of-recorded-deaths-from-covid-19/ Authorities 16 22 1903

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/).