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Between Monday 02 August 2021 and Monday 09 August 2021, misinformation about Vaccine has increasead whereas misinformation about Spread 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 02 August 2021 and Monday 09 August 2021.

316,836 Misinforming Tweets
New:+1,316 Trend:+779
162,900 Fact-checking Tweets
New:+1,698 Trend:-394
13,901 Fact-checks
102 Fact-checking Organisations

Key Content and Topics

During the period between Monday 02 August 2021 and Monday 09 August 2021, 1,316 new URLs have been identified as potential misinforming content. Out of the 10 topics identified by Fact-checking organisations (Figure 1), most of the new shared URLs were about Vaccine with an increase of +1,842 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 Face Mask with a change of +0 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 Vaccine with a change of +819 compared to the previous total spread for the same topic whereas the topic that saw the least relative change was Vaccine with a change of -524 compared to the previous period.

The all time most important topic is Authorities with a total of 127,691 URL shares and the least popular topic is Face Mask with 1 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://twitter.com/EmeraldRobinson/status/1423274794343190531 FactCheck.org Vaccine 814 0 814
https://www.youtube.com/watch?v=Du2wm5nhTXY PolitiFact Vaccine 229 226 5060
https://www.worldometers.info/ Agencia Ocote Authorities 171 185 34283
https://madisonarealymesupportgroup.com/2020/09/30/proof-that-the-pandemic-was-planned-with-purpose/ Newschecker Conspiracy Theory 38 22 1510
https://www.youtube.com/watch?v=dswaElkiRO8 FactCheck.org Other 8 2 205
https://www.nytimes.com/2021/04/26/us/florida-centner-academy-vaccine.html Détecteur de rumeurs Vaccine 7 1 922
https://mcusercontent.com/92561d6dedb66a43fe9a6548f/files/bead7203-0798-4ac8-abe2-076208015556/Public_health_emergency_of_international_concert_Geert_Vanden_Bossche.01.pdf Détecteur de rumeurs Vaccine 6 4 487
https://tercalivre.com.br/estudo-frances-aponta-eficacia-da-ivermectina/ Estadão Verifica Cure 5 5 36
https://www.the-scientist.com/news-opinion/lab-made-coronavirus-triggers-debate-34502 LeadStories Conspiracy Theory 5 4 2104
https://www.cdc.gov/mmwr/volumes/69/wr/mm6936a5.htm Détecteur de rumeurs Other 5 3 1667

Table 1: Top misinforming content.

Fact-check URL Topic Current Week Previous Week Total
https://www.factcheck.org/2021/07/scicheck-viral-claim-gets-bidens-covid-19-travel-and-immigration-policies-wrong/ Authorities 106 34 140
https://www.factcheck.org/2021/07/scicheck-viral-posts-misrepresent-cdc-announcement-on-covid-19-pcr-test/ Conspiracy Theory 93 588 681
https://www.factcheck.org/2021/07/scicheck-covid-19-surges-among-unvaccinated-in-florida-contrary-to-baseless-claims/ Spread 80 55 135
https://www.factcheck.org/2021/04/scicheck-idaho-doctor-makes-baseless-claims-about-safety-of-covid-19-vaccines/ Vaccine 63 9 211
https://www.factcheck.org/2021/08/scicheck-pfizer-ceo-got-the-covid-19-vaccine/ Vaccine 59 0 59
https://www.politifact.com/factchecks/2021/jul/23/tiktok-posts/biden-harris-doubted-trump-covid-19-vaccines-not-v/ Vaccine 58 45 124
https://www.factcheck.org/2021/08/scicheck-sequencing-used-to-identify-delta-other-coronavirus-variants/ Other 45 0 45
https://www.factcheck.org/2021/02/biden-hasnt-reduced-covid-19-testing-at-the-border/ Authorities 38 40 307
https://www.politifact.com/factchecks/2021/jul/30/facebook-posts/uk-health-official-misspoke-when-he-said-60-hospit/ Vaccine 34 17 51
https://factuel.afp.com/non-il-ny-pas-800-lits-de-reanimation-en-moins-en-ile-de-france-depuis-mars-2020 Authorities 29 0 95

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 102 fact-checking organisation based in 824 countries and covering 48 languages.

The largest amount of fact-checked content comes from English (7,324 fact-checks) and the least is Finland (1 fact-checks). Most fact-checked content is in Spanish (4,015) followed by Portuguese (2,445) and Ukrainian (1,655) (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/).