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Between Monday 31 May 2021 and Monday 07 June 2021, misinformation about Conspiracy Theory has increasead whereas misinformation about Authorities 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 May 2021 and Monday 07 June 2021.

306,591 Misinforming Tweets
New:+321 Trend:+20
149,193 Fact-checking Tweets
New:+1,084 Trend:-251
12,868 Fact-checks
101 Fact-checking Organisations

Key Content and Topics

During the period between Monday 31 May 2021 and Monday 07 June 2021, 321 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 +398 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 +73 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 -248 compared to the previous period.

The all time most important topic is Authorities with a total of 125,036 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 130 148 32892
https://www.zerohedge.com/geopolitical/coronavirus-contains-hiv-insertions-stoking-fears-over-artificially-created-bioweapon FactCheck.org Conspiracy Theory 66 4 3077
https://www.the-scientist.com/news-opinion/lab-made-coronavirus-triggers-debate-34502 LeadStories Conspiracy Theory 18 16 2070
https://c19study.com D├ętecteur de rumeurs Cure 14 12 29205
https://madisonarealymesupportgroup.com/2020/09/30/proof-that-the-pandemic-was-planned-with-purpose/ Newschecker Conspiracy Theory 12 41 1409
https://traugott-ickeroth.com/liveticker/ Correctiv Conspiracy Theory 9 10 479
https://www.armstrongeconomics.com/world-news/corruption/belarusian-president-claims-imf-world-bank-offered-him-a-bribe-to-impose-covid-restrictions/ TEMPO Conspiracy Theory 5 7 745
https://twitter.com/zlj517/status/1238111898828066823 Taiwan FactCheck Center Authorities 5 5 31
https://www.foxnews.com/politics/coronavirus-wuhan-lab-china-compete-us-sources FactCheck Georgia Other 4 6 5077
https://www.agi.it/estero/news/2020-04-17/coronavirus-montagnier-wuhan-8364636/ Open Conspiracy Theory 4 3 233

Table 1: Top misinforming content.

Fact-check URL Topic Current Week Previous Week Total
https://piaui.folha.uol.com.br/lupa/2020/07/24/verificamos-estudo-henry-ford-hidroxicloroquina-covid-19/ Cure 91 2 152
https://factcheck.afp.com/canadas-top-court-not-hearing-case-about-covid-19-crimes Authorities 50 11 107
https://factcheck.afp.com/us-cardiologist-makes-false-claims-about-covid-19-vaccination Vaccine 28 14 123
https://piaui.folha.uol.com.br/lupa/2021/01/22/verificamos-estados-unidos-recomendar-hidroxicloroquina/ Cure 28 1 265
https://factcheck.afp.com/principles-nuremberg-code-are-compatible-vaccination Conspiracy Theory 24 2 59
https://teyit.org/analiz-mikrobiyolog-dr-sucharit-bhakdinin-koronavirus-iddialari Vaccine 22 1 39
https://healthfeedback.org/claimreview/covid-19-vaccines-are-safer-than-the-risk-of-covid-19-infection-for-people-of-all-ages-wendy-bell-radio/ Vaccine 15 5 20
https://www.newtral.es/bulo-variantes-coronavirus-luc-montagnier/20210601/ Vaccine 14 0 14
https://www.politifact.com/factchecks/2021/mar/31/blog-posting/european-database-does-not-prove-covid-19-vaccines/ Vaccine 12 22 120
https://www.factcheck.org/2021/05/scicheck-instagram-posts-spread-texas-lawmakers-false-claims-on-vaccine-testing/ Vaccine 12 19 76

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 749 countries and covering 48 languages.

The largest amount of fact-checked content comes from English (7,002 fact-checks) and the least is Finland (1 fact-checks). Most fact-checked content is in Spanish (3,816) followed by Portuguese (2,333) 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/).