Between Monday 31 October 2022 and Monday 07 November 2022, misinformation about Vaccine has increasead whereas misinformation about Cure 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 31 October 2022 and Monday 07 November 2022.

288,600 Misinforming Tweets
New:+5 Trend:-12
205,062 Fact-checking Tweets
New:+242 Trend:-3
16,529 Fact-checks
101 Fact-checking Organisations

Key Content and Topics

During the period between Monday 31 October 2022 and Monday 07 November 2022, 5 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 Vaccine with an increase of +137 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 Causes 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 +10 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 -10 compared to the previous period.

The all time most important topic is Other with a total of 107,296 URL shares and the least popular topic is Symptoms with 3,304 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.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 2 3 647
https://biohackinfo.com/news-bill-gates-id2020-vaccine-implant-covid-19-digital-certificates/ Factcheck.kz Conspiracy Theory 1 0 1487
https://traugott-ickeroth.com/liveticker/ Correctiv Conspiracy Theory 1 0 626
https://medicalracism.childrenshealthdefense.org/medical-racism-the-new-apartheid/ FactCheck.org Vaccine 1 0 202
https://www.mediterranee-infection.com/wp-content/uploads/2020/03/Hydroxychloroquine_final_DOI_IJAA.pdf TjekDet.dk Cure 0 3 2115
https://www.youtube.com/watch?v=tCZu8a5r5y4 MediaWise Other 0 2 192
https://twitter.com/NICKIMINAJ/status/1437532566945341441 FactCheck.org Vaccine 0 1 30758
https://www.the-scientist.com/news-opinion/lab-made-coronavirus-triggers-debate-34502 LeadStories Conspiracy Theory 0 1 2168
https://nypost.com/2020/02/22/dont-buy-chinas-story-the-coronavirus-may-have-leaked-from-a-lab/ Science Feedback Conspiracy Theory 0 1 1710
https://www.cnews.fr/france/2020-04-17/le-coronavirus-est-un-virus-sorti-dun-laboratoire-chinois-avec-de-ladn-de-vih franceinfo Causes 0 1 519

Table 1: Top misinforming content.

Fact-check URL Topic Current Week Previous Week Total
https://healthfeedback.org/claimreview/joe-rogan-interview-with-peter-mccullough-contains-multiple-false-and-unsubstantiated-claims-about-the-covid-19-pandemic-and-vaccines/ Conspiracy Theory 17 27 1438
https://healthfeedback.org/claimreview/study-lund-university-didnt-show-covid-19-mrna-vaccines-change-dna-epoch-times/ Vaccine 15 0 171
https://healthfeedback.org/claimreview/article-by-cardiologist-aseem-malhotra-made-unsupported-claims-about-benefits-risks-covid-19-vaccination/ Vaccine 11 2 13
https://healthfeedback.org/claimreview/mike-adams-flawed-analysis-clot-embalmer-richard-hirschman-doesnt-demonstrate-link-between-blood-clots-and-covid-19-vaccines-epoch-times/ Vaccine 10 8 32
https://www.factcheck.org/2021/04/scicheck-idaho-doctor-makes-baseless-claims-about-safety-of-covid-19-vaccines/ Vaccine 10 5 1206
https://healthfeedback.org/claimreview/scientific-studies-show-pfizer-biontech-covid-19-vaccine-reduces-transmission-claim-rob-roos-misleading/ Vaccine 8 1 9
https://www.factcheck.org/2020/06/nuremberg-code-addresses-experimentation-not-vaccines/ Cure 6 0 482
https://www.factcheck.org/2022/11/scicheck-bodybuilder-died-from-covid-19-not-the-vaccine-as-social-media-posts-claim/ Vaccine 6 0 6
https://healthfeedback.org/claimreview/robert-malone-misleading-unsubstantiated-claims-covid-19-safety-efficacy-vaccines-joe-rogan-experience-spotify-podcast/ Vaccine 5 0 159
https://www.lemonde.fr/les-decodeurs/article/2020/03/20/cette-photo-montrant-des-cercueils-en-italie-n-a-rien-a-voir-avec-l-epidemie-de-covid-19_6033801_4355770.html Spread 5 0 46

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 101 fact-checking organisation based in 1001 countries and covering 46 languages.

The largest amount of fact-checked content comes from English (8,888 fact-checks) and the least is Finland (1 fact-checks). Most fact-checked content is in Spanish (4,598) followed by Portuguese (2,801) and Ukrainian (2,073) (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.