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Between Monday 13 September 2021 and Monday 20 September 2021, misinformation about Vaccine has increasead whereas misinformation about Other 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 13 September 2021 and Monday 20 September 2021.

348,753 Misinforming Tweets
New:+30,543 Trend:+30,273
170,178 Fact-checking Tweets
New:+1,242 Trend:+56
14,483 Fact-checks
102 Fact-checking Organisations

Key Content and Topics

During the period between Monday 13 September 2021 and Monday 20 September 2021, 30,543 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 +31,156 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 +30,360 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 -34 compared to the previous period.

The all time most important topic is Authorities with a total of 128,800 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://twitter.com/NICKIMINAJ/status/1437532566945341441 FactCheck.org Vaccine 30235 0 30235
https://www.worldometers.info/ Agencia Ocote Authorities 146 143 34897
https://www.youtube.com/watch?v=Du2wm5nhTXY PolitiFact Vaccine 96 76 5567
https://filiperafaeli.substack.com/p/hidroxicloroquina-para-profilaxia AgĂȘncia Lupa Cure 19 0 102
https://madisonarealymesupportgroup.com/2020/09/30/proof-that-the-pandemic-was-planned-with-purpose/ Newschecker Conspiracy Theory 8 3 1533
https://www.youtube.com/watch?v=dswaElkiRO8 FactCheck.org Other 4 15 260
https://www.bitchute.com/video/InH89amCpy7S/ FactCheck.org Vaccine 4 1 37
http://www.defenddemocracy.press/bill-gates-former-doctor-says-billionaire-refused-to-vaccinate-his-children/ TEMPO Vaccine 3 2 319
https://www.the-scientist.com/news-opinion/lab-made-coronavirus-triggers-debate-34502 LeadStories Conspiracy Theory 3 1 2119
https://medicalracism.childrenshealthdefense.org/medical-racism-the-new-apartheid/ FactCheck.org Vaccine 3 0 172

Table 1: Top misinforming content.

Fact-check URL Topic Current Week Previous Week Total
https://www.factcheck.org/2021/04/scicheck-idaho-doctor-makes-baseless-claims-about-safety-of-covid-19-vaccines/ Vaccine 105 56 412
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 53 34 162
https://healthfeedback.org/claimreview/no-data-available-to-suggest-a-link-between-indias-reduction-of-covid-19-cases-and-the-use-of-ivermectin-jim-hoft-gateway-pundit/ Cure 50 50 497
https://www.dogrulukpayi.com/dogrulama/biontech-ceo-su-ugur-sahin-in-covid-19-asisi-olmadigi-iddiasi Vaccine 49 87 272
https://factcheck.afp.com/http%253A%252F%252Fdoc.afp.com%252F9M48JR-1 Cure 32 25 57
https://healthfeedback.org/claimreview/janci-chunn-lindsays-claims-that-covid-19-vaccines-are-unsafe-are-inaccurate-and-unsupported-by-scientific-evidence/ Vaccine 29 12 81
https://www.politifact.com/factchecks/2021/jul/23/tiktok-posts/biden-harris-doubted-trump-covid-19-vaccines-not-v/ Vaccine 28 55 298
https://www.factcheck.org/2021/03/scicheck-viral-posts-misuse-vaers-data-to-make-false-claims-about-covid-19-vaccines/ Vaccine 26 11 391
https://teyit.org/analiz-asi-ureticilerinin-asi-olmasinin-yasak-oldugu-iddiasi Vaccine 26 2 41
https://factcheck.afp.com/http%253A%252F%252Fdoc.afp.com%252F9MU3HH-1 Vaccine 24 0 24

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 868 countries and covering 48 languages.

The largest amount of fact-checked content comes from English (7,706 fact-checks) and the least is Finland (1 fact-checks). Most fact-checked content is in Spanish (4,127) followed by Portuguese (2,495) and Ukrainian (1,764) (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.