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Between Monday 28 June 2021 and Monday 05 July 2021, misinformation about Cure 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 28 June 2021 and Monday 05 July 2021.

312,168 Misinforming Tweets
New:+614 Trend:-714
154,549 Fact-checking Tweets
New:+918 Trend:-235
13,386 Fact-checks
102 Fact-checking Organisations

Key Content and Topics

During the period between Monday 28 June 2021 and Monday 05 July 2021, 614 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 +993 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 Face Mask with a change of +0 compared to the previous total spread for the same topic whereas the topic that saw the least relative change was Face Mask with a change of -786 compared to the previous period.

The all time most important topic is Authorities with a total of 126,084 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://www.youtube.com/watch?v=Du2wm5nhTXY PolitiFact Vaccine 417 1095 3722
https://www.worldometers.info/ Agencia Ocote Authorities 143 158 33425
https://www.brighteon.com/10be15cc-987e-44b9-83b5-1db88e60ae36 Ellinika Hoaxes Vaccine 19 0 43
https://www.youtube.com/watch?v=dswaElkiRO8 FactCheck.org Other 4 10 190
https://dailyexpose.co.uk/2021/05/23/an-exclusive-interview-with-dr-roger-hodkinson-when-the-history-of-this-madness-is-written-reputations-will-be-slaughtered-and-there-will-be-blood-in-the-gutter/ FactCheck.org Vaccine 2 9 325
https://www.the-scientist.com/news-opinion/lab-made-coronavirus-triggers-debate-34502 LeadStories Conspiracy Theory 2 3 2086
https://c19study.com D├ętecteur de rumeurs Cure 2 2 29223
https://mcusercontent.com/92561d6dedb66a43fe9a6548f/files/bead7203-0798-4ac8-abe2-076208015556/Public_health_emergency_of_international_concert_Geert_Vanden_Bossche.01.pdf D├ętecteur de rumeurs Vaccine 2 1 474
https://traugott-ickeroth.com/liveticker/ Correctiv Conspiracy Theory 2 0 486
https://medicalracism.childrenshealthdefense.org/medical-racism-the-new-apartheid/ FactCheck.org Vaccine 2 0 161

Table 1: Top misinforming content.

Fact-check URL Topic Current Week Previous Week Total
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 27 15 149
https://factcheck.afp.com/us-cardiologist-makes-false-claims-about-covid-19-vaccination Vaccine 24 15 189
https://factuel.afp.com/http%253A%252F%252Fdoc.afp.com%252F9DD2KF-1 Vaccine 24 0 24
https://factuel.afp.com/attention-ce-tutoriel-trompeur-pretendant-montrer-le-nombre-de-deces-dus-la-vaccination-anti-covid Vaccine 22 2 119
https://factuel.afp.com/http%253A%252F%252Fdoc.afp.com%252F9DD2DW Vaccine 21 0 21
https://healthfeedback.org/claimreview/pcr-tests-on-vaccinated-and-unvaccinated-people-are-evaluated-using-the-same-criteria-the-cdc-didnt-change-criteria-for-detecting-infection-in-vaccinated-people-as-alleged-in-off-guardian-a/ Authorities 19 14 49
https://www.newtral.es/bulo-grafeno-magnetico-vacuna-coronavirus/20210612/ Vaccine 19 5 38
https://teyit.org/analiz-nobel-odulu-sahibi-luc-montagnierin-covid-19-asisi-olanlarin-iki-yil-icinde-olecegini-acikladigi-iddiasi Vaccine 18 7 107
https://www.politifact.com/factchecks/2021/jun/16/youtube-videos/no-sign-covid-19-vaccines-spike-protein-toxic-or-c/ Vaccine 17 39 183
https://factuel.afp.com/non-cette-resolution-du-conseil-de-leurope-ne-proscrirait-pas-une-obligation-vaccinale Vaccine 15 1 48

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 789 countries and covering 48 languages.

The largest amount of fact-checked content comes from English (7,126 fact-checks) and the least is Finland (1 fact-checks). Most fact-checked content is in Spanish (3,913) followed by Portuguese (2,426) and Ukrainian (1,521) (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/).