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Between Monday 17 May 2021 and Monday 24 May 2021, misinformation about Vaccine has increasead whereas misinformation about Conspiracy Theory 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 17 May 2021 and Monday 24 May 2021.

306,017 Misinforming Tweets
New:+263 Trend:-117
145,561 Fact-checking Tweets
New:+1,092 Trend:+236
12,531 Fact-checks
100 Fact-checking Organisations

Key Content and Topics

During the period between Monday 17 May 2021 and Monday 24 May 2021, 263 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 +411 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 Cure with a change of +227 compared to the previous total spread for the same topic whereas the topic that saw the least relative change was Cure with a change of -202 compared to the previous period.

The all time most important topic is Authorities with a total of 124,545 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.worldometers.info/ Agencia Ocote Authorities 149 153 32646
https://madisonarealymesupportgroup.com/2020/09/30/proof-that-the-pandemic-was-planned-with-purpose/ Newschecker Conspiracy Theory 18 92 1356
https://youtu.be/EQHSvSL0qtI Newsmeter.in Cure 9 0 16
https://c19study.com DĂ©tecteur de rumeurs Cure 8 11 29179
https://www.youtube.com/watch?v=p_AyuhbnPOI Faktograf Other 6 7 3801
https://medicalracism.childrenshealthdefense.org/medical-racism-the-new-apartheid/ FactCheck.org Vaccine 6 1 153
https://twitter.com/MariolySosaP/status/1381243002904047617 Animal PolĂ­tico Vaccine 5 1 64
https://nypost.com/2020/02/22/dont-buy-chinas-story-the-coronavirus-may-have-leaked-from-a-lab/ Science Feedback Conspiracy Theory 5 0 1698
https://www.the-scientist.com/news-opinion/lab-made-coronavirus-triggers-debate-34502 LeadStories Conspiracy Theory 4 55 2039
https://okdiario.com/espana/tribunal-haya-registra-denuncia-contra-sanchez-genocidio-50-000-personas-5727974 Newtral.es Authorities 4 3 422

Table 1: Top misinforming content.

Fact-check URL Topic Current Week Previous Week Total
https://politica.estadao.com.br/blogs/estadao-verifica/site-engana-ao-afirmar-que-baixa-mortalidade-por-covid-19-em-cuba-e-por-conta-da-hidroxicloroquina/ Cure 168 1 199
https://www.factcheck.org/2021/05/post-misleads-on-japans-policy-for-donating-blood-after-covid-19-vaccination/ Vaccine 52 12 64
https://www.factcheck.org/2021/05/scicheck-instagram-posts-spread-texas-lawmakers-false-claims-on-vaccine-testing/ Vaccine 45 0 45
https://piaui.folha.uol.com.br/lupa/2020/09/01/verificamos-fda-china-cloroquina/ Cure 23 0 63
https://www.factcheck.org/2021/05/scicheck-magnet-videos-refuel-bogus-claim-of-vaccine-microchips/ Vaccine 21 28 49
https://www.factcheck.org/2021/05/scicheck-covid-19-vaccines-spike-protein-only-get-into-those-who-receive-it-no-shedding/ Vaccine 19 34 53
https://www.factcheck.org/2021/05/scicheck-tucker-carlson-misrepresents-vaccine-safety-reporting-data/ Vaccine 16 25 41
https://www.politifact.com/factchecks/2021/mar/31/blog-posting/european-database-does-not-prove-covid-19-vaccines/ Vaccine 16 10 86
https://www.newtral.es/bulo-vacunas-metales-pesados-imanes/20210515/ Vaccine 16 9 25
https://www.factcheck.org/2020/09/cdc-did-not-admit-only-6-of-recorded-deaths-from-covid-19/ Authorities 14 9 2119

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 100 fact-checking organisation based in 723 countries and covering 48 languages.

The largest amount of fact-checked content comes from English (6,724 fact-checks) and the least is Finland (1 fact-checks). Most fact-checked content is in Spanish (3,762) followed by Portuguese (2,251) and Ukrainian (1,335) (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/).