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Between Monday 25 October 2021 and Monday 01 November 2021, 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 25 October 2021 and Monday 01 November 2021.

350,409 Misinforming Tweets
New:+237 Trend:+21
175,425 Fact-checking Tweets
New:+643 Trend:-116
14,975 Fact-checks
102 Fact-checking Organisations

Key Content and Topics

During the period between Monday 25 October 2021 and Monday 01 November 2021, 237 new URLs have been identified as potential misinforming content. Out of the 9 topics identified by Fact-checking organisations (Figure 1), most of the new shared URLs were about Vaccine with an increase of +438 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 Masks 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. Vaccines: Information relating to vaccines (e.g., side effects, effectiveness).
  8. Masks: Information concerning the usage of masks.
  9. 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 +14 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 -36 compared to the previous period.

The all time most important topic is Authorities with a total of 129,965 URL shares and the least popular topic is Masks with 12 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 100 128 35621
https://twitter.com/NICKIMINAJ/status/1437532566945341441 FactCheck.org Vaccine 66 4 30423
https://m.facebook.com/home.php Vistinomer Other 29 23 183
https://www.galluranews.org/iss-istituto-superiore-di-sanita-i-dati-reali-che-smentiscono-la-pandemia/ Facta Conspiracy Theory 8 1 59
https://www.armstrongeconomics.com/world-news/corruption/belarusian-president-claims-imf-world-bank-offered-him-a-bribe-to-impose-covid-restrictions/ TEMPO Conspiracy Theory 3 1 839
https://www.pourquoidocteur.fr/Articles/Question-d-actu/32184-EXCLUSIF-Pour-Pr-Montagnier-SARS-CoV-2-serait-virus-manipule-Chinois-l-ADN-de-VIH-podcast Les D├ęcodeurs Conspiracy Theory 3 0 609
https://www.youtube.com/watch?v=dswaElkiRO8 FactCheck.org Other 3 0 280
http://dilyana.bg/project-g-2101-pentagon-biolab-discovered-mers-and-sars-like-coronaviruses-in-bats/ Myth Detector Conspiracy Theory 2 20 163
https://traugott-ickeroth.com/liveticker/ Correctiv Conspiracy Theory 2 3 531
https://www.cdc.gov/mmwr/volumes/69/wr/mm6936a5.htm D├ętecteur de rumeurs Other 2 0 1676

Table 1: Top misinforming content.

Fact-check URL Topic Current Week Previous Week Total
https://factcheck.afp.com/http%253A%252F%252Fdoc.afp.com%252F9M48JR-1 Cure 43 22 203
https://www.aosfatos.org/noticias/relatorios-do-governo-britanico-nao-afirmam-que-vacinas-contra-a-covid-19-causam-aids/ Vaccine 31 24 55
https://www.factcheck.org/2021/04/scicheck-idaho-doctor-makes-baseless-claims-about-safety-of-covid-19-vaccines/ Vaccine 26 26 722
https://factcheck.afp.com/us-cardiologist-makes-false-claims-about-covid-19-vaccination Vaccine 17 6 458
https://www.factcheck.org/2021/03/scicheck-viral-posts-misuse-vaers-data-to-make-false-claims-about-covid-19-vaccines/ Vaccine 16 19 518
https://www.politifact.com/factchecks/2020/may/21/facebook-posts/disposable-homemade-masks-are-effective-stopping-a/ Spread 14 29 1124
https://correctiv.org/faktencheck/2020/10/20/nein-die-who-hat-nicht-bestaetigt-dass-covid-19-weniger-schlimm-als-eine-grippe-sei/ Authorities 13 0 68
https://www.factcheck.org/2021/08/scicheck-researcher-distorts-facts-on-covid-19-vaccine-approval-liability/ Vaccine 12 18 165
https://www.factcheck.org/2021/09/covid-19-the-unvaccinated-pose-a-risk-to-the-vaccinated/ Vaccine 12 17 153
https://healthfeedback.org/claimreview/the-development-of-mrna-vaccines-was-a-collaborative-effort-robert-malone-contributed-to-their-development-but-he-is-not-their-inventor/ Vaccine 11 25 302

Table 2: Top fact-checked content.

Fact-checking

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 910 countries and covering 48 languages.

The largest amount of fact-checked content comes from English (7,934 fact-checks) and the least is Finland (1 fact-checks). Most fact-checked content is in Spanish (4,193) followed by Portuguese (2,525) and Ukrainian (1,823) (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.