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Between Monday 07 September 2020 and Monday 14 September 2020, misinformation about Other has increasead whereas misinformation about Spread 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 07 September 2020 and Monday 14 September 2020.

242,008 Misinforming Tweets
New:+812 Trend:+242
94,978 Fact-checking Tweets
New:+1,570 Trend:-312
10,803 Fact-checks
98 Fact-checking Organisations

Key Content and Topics

During the period between Monday 07 September 2020 and Monday 14 September 2020, 812 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 Authorities with an increase of +1,279 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 Vaccine with a change of +13 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 Conspiracy Theory with a change of +117 compared to the previous total spread for the same topic whereas the topic that saw the least relative change was Conspiracy Theory with a change of -141 compared to the previous period.

The all time most important topic is Other with a total of 92,766 URL shares and the least popular topic is Vaccine with 957 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 406 385 23361
https://www.cdc.gov/mmwr/volumes/69/wr/mm6936a5.htm Détecteur de rumeurs Other 145 0 145
https://www.youtube.com/watch?v=_NEgaWGevZE VoxCheck Conspiracy Theory 34 0 34
https://www.tvnz.co.nz/one-news/new-zealand/not-lockdowns-controversial-epidemiologist-calls-end-irrational-covid-19-elimination-strategy AAP FactCheck Symptoms 22 9 31
http://www.francesoir.fr/le-confinement-tout-ce-que-lon-ne-vous-pas-dit-aberration-humaine-sanitaire-economique Les Décodeurs Authorities 18 4 306
https://www.whitehouse.gov/briefings-statements/remarks-president-trump-vice-president-pence-members-coronavirus-task-force-press-briefing-5/ PolitiFact Authorities 18 0 76
https://www.youtube.com/watch?v=p_AyuhbnPOI Faktograf Other 17 11 3599
https://twitter.com/realDonaldTrump/status/1250852583318736896 LeadStories Authorities 15 6 5382
https://twitter.com/MariaAmpudiaG_/status/1303085933244407815 Animal Político Symptoms 13 0 13
https://okdiario.com/espana/tribunal-haya-registra-denuncia-contra-sanchez-genocidio-50-000-personas-5727974 Newtral.es Authorities 11 0 399

Table 1: Top misinforming content.

Fact-check URL Topic Current Week Previous Week Total
https://www.factcheck.org/2020/09/cdc-did-not-admit-only-6-of-recorded-deaths-from-covid-19/ Authorities 367 657 1024
https://www.thejournal.ie/how-many-people-have-died-from-covid-19-in-ireland-5198763-Sep2020/ Conspiracy Theory 85 0 85
https://www.politifact.com/factchecks/2020/mar/27/donald-trump/fact-checking-whether-biden-called-trump-xenophobi/ Authorities 67 13 468
https://chequeado.com/el-explicador/es-falso-que-los-protagonistas-de-la-quema-de-barbijos-en-el-obelisco-militan-en-la-campora/ Other 52 0 52
https://www.factcheck.org/2020/07/herman-cain-died-of-covid-19-not-cancer/ Other 30 20 259
https://www.politifact.com/factchecks/2020/apr/08/donald-trump/trump-said-obama-admin-left-him-bare-stockpile-wro/ Other 26 11 652
https://www.washingtonpost.com/politics/2020/04/07/trumps-claim-that-he-imposed-first-china-ban/ Authorities 25 9 682
https://healthfeedback.org/claimreview/covid-19-test-kits-were-not-purchased-in-2017-and-2018-claim-is-based-on-mislabeled-data/ Other 23 0 23
https://healthfeedback.org/claimreview/misinterpreted-new-york-times-report-leads-to-false-claim-that-the-number-of-covid-19-cases-in-the-u-s-is-inflated-by-up-to-90/ Other 23 0 23
https://www.politifact.com/factchecks/2020/mar/04/facebook-posts/president-obama-declared-h1n1-public-health-emerge/ Authorities 21 7 3738

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 98 fact-checking organisation based in 635 countries and covering 46 languages.

The largest amount of fact-checked content comes from English (6,130 fact-checks) and the least is Finland (1 fact-checks). Most fact-checked content is in Spanish (3,367) followed by Portuguese (1,998) and French (963) (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/).