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Between Monday 08 November 2021 and Monday 15 November 2021, misinformation about Other has increasead whereas misinformation about Vaccine 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 08 November 2021 and Monday 15 November 2021.

351,652 Misinforming Tweets
New:+311 Trend:-124
178,403 Fact-checking Tweets
New:+780 Trend:-69
15,084 Fact-checks
102 Fact-checking Organisations

Key Content and Topics

During the period between Monday 08 November 2021 and Monday 15 November 2021, 311 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 +527 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 Conspiracy Theory with a change of +12 compared to the previous total spread for the same topic whereas the topic that saw the least relative change was Conspiracy Theory with a change of -136 compared to the previous period.

The all time most important topic is Authorities with a total of 130,892 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 106 119 35846
https://www.instagram.com/accounts/login/ StopFake.org Authorities 98 89 571
https://m.facebook.com/home.php Vistinomer Other 24 22 229
https://1scandal.com/etats-unis-la-cour-supreme-annule-la-vaccination-universelle/ La Silla VacĂ­a Vaccine 23 64 87
https://realrawnews.com/2021/08/marines-rebuke-def-sec-no-mandatory-vaccinations-for-my-marines/ FactCheck.org Vaccine 15 1 39
https://twitter.com/NICKIMINAJ/status/1437532566945341441 FactCheck.org Vaccine 6 109 30538
https://www.cnews.fr/france/2020-04-17/le-coronavirus-est-un-virus-sorti-dun-laboratoire-chinois-avec-de-ladn-de-vih franceinfo Causes 5 5 499
http://xn----ctbsbazhbctieai.ru-an.info/%D0%BD%D0%BE%D0%B2%D0%BE%D1%81%D1%82%D0%B8/%D0%B1%D0%B8%D0%BE%D0%BB%D0%BE%D0%B3%D0%B8%D1%87%D0%B5%D1%81%D0%BA%D0%B0%D1%8F-%D0%B2%D0%BE%D0%B9%D0%BD%D0%B0-%D0%BF%D1%80%D0%B8%D0%B2%D0%B8%D0%B2%D0%BA%D0%B0%D0%BC%D0%B8-%D1%83%D0%B1%D0%B8%D0%B2%D0%B0%D1%8E%D1%82-%D0%BC%D0%B8%D0%BB%D0%BB%D0%B8%D0%BE%D0%BD%D1%8B/ VoxCheck Vaccine 4 2 77
https://www.stylourbano.com.br/foi-descoberto-oxido-de-grafeno-nas-vacinas-o-que-torna-o-vacinado-uma-especie-de-condutor/ AgĂȘncia Lupa Vaccine 3 2 62
https://medicalracism.childrenshealthdefense.org/medical-racism-the-new-apartheid/ FactCheck.org Vaccine 3 1 179

Table 1: Top misinforming content.

Fact-check URL Topic Current Week Previous Week Total
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 44 19 365
https://www.factcheck.org/2021/11/scicheck-desantis-comments-social-media-posts-mislead-on-covid-19s-toll-in-florida/ Other 43 47 90
https://www.factcheck.org/2021/11/scicheck-japan-continues-to-use-vaccines-not-ivermectin-to-fight-covid-19/ Vaccine 35 51 86
https://healthfeedback.org/claimreview/no-evidence-suggests-a-causal-link-between-ivermectin-recommendation-and-the-decline-of-covid-19-cases-in-the-indian-state-of-uttar-pradesh/ Cure 27 50 217
https://www.factcheck.org/2021/04/scicheck-idaho-doctor-makes-baseless-claims-about-safety-of-covid-19-vaccines/ Vaccine 20 11 751
https://www.factcheck.org/2021/11/scicheck-video-questioning-vaccine-efficacy-pushes-falsehood-about-israel-data/ Vaccine 19 0 19
https://healthfeedback.org/claimreview/no-scientific-evidence-for-claim-by-pathologist-ryan-cole-that-covid-19-vaccines-weaken-the-immune-system/ Vaccine 16 5 171
https://www.factcheck.org/2021/03/scicheck-viral-posts-misuse-vaers-data-to-make-false-claims-about-covid-19-vaccines/ Vaccine 15 21 553
https://www.factcheck.org/2021/09/covid-19-the-unvaccinated-pose-a-risk-to-the-vaccinated/ Vaccine 14 15 182
https://healthfeedback.org/claimreview/claims-that-a-harvard-study-showed-covid-19-vaccines-are-ineffective-misrepresent-the-conclusions-from-the-authors-fail-to-account-for-the-studys-limitations/ Vaccine 14 11 53

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 918 countries and covering 48 languages.

The largest amount of fact-checked content comes from English (7,966 fact-checks) and the least is Finland (1 fact-checks). Most fact-checked content is in Spanish (4,224) followed by Portuguese (2,539) 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.