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 18 April 2022 and Monday 25 April 2022.
New:+1,199 Trend:-7,133
69,592 Fact-checking Tweets
New:+1,353 Trend:-739
2,929 Fact-checks
125 Fact-checking Organisations
Key Content and Provenance
During the period between Monday 18 April 2022 and Monday 25 April 2022, 1,199 new URLs have been identified as potential misinforming content. Out of the 197 domains identified by Fact-checking organisations (Figure 1), most of the new shared URLs were from twitter.com with an increase of +462 compared to the previous total spread for the same domain The domain that saw the least increase in spread compared to the previous period total spread was 24-post.com with a change of +0 compared to the previous total spread for the same domain
In relation to the previous week, the domain that saw the biggest relative spread change was facta.news with a change of +330 compared to the previous total spread for the same domain whereas the domain that saw the least relative change was rumble.com with a change of -5,112 compared to the previous period.
The all time most important domain is twitter.com with a total of 108,075 URL shares and the least popular domain is 15min.lt with 1 shares (Figure 2).
Figure 1: Domain importance.
Figure 2: Amount of domains 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 | Domain | Current Week | Previous Week | Total |
|---|---|---|---|---|---|
| https://twitter.com/ArmedForcesUkr/status/1516018161023389703 | LeadStories | twitter.com | 400 | 0 | 400 |
| https://rumble.com/v10miez-world-premiere-watch-the-water.html | LeadStories | rumble.com | 391 | 5503 | 5894 |
| https://tass.ru/politika/14418361 | euvsdisinfo.eu | tass.ru | 96 | 0 | 96 |
| https://www.youtube.com/watch?v=6LQSYmda0Sc | LeadStories | youtube.com | 93 | 142 | 8380 |
| https://www.youtube.com/watch?v=X1b-RKDHZOo | LeadStories | youtube.com | 43 | 63 | 2190 |
| https://www.globaltimes.cn/page/202203/1254217.shtml | StopFake.org | globaltimes.cn | 31 | 15 | 1382 |
| https://twitter.com/jcokechukwu/status/1518351056987697157 | LeadStories | twitter.com | 27 | 0 | 27 |
| https://ria.ru/20220417/biolaboratorii-1783801453.html | Factcheck.ge | ria.ru | 23 | 139 | 162 |
| https://ria.ru/20220419/ukraina-1784261157.html | Factcheck.ge | ria.ru | 22 | 0 | 22 |
| https://thefauxy.com/pakistan-imposes-economic-sanctions-on-russia-refuses-to-repay-loans | Taiwan FactCheck Center | thefauxy.com | 14 | 12 | 3926 |
Table 1: Top misinforming content.
Table 2: Top fact-checked content.
Fact-Checkers and Spreaders Location
The data used for creating the Twitter dataset is obtained from 125 fact-checking organisations.
The largest amount of fact-checked content comes from euvsdisinfo.eu (222 fact-checks) and the least from Verificat (1 fact-checks). Most fact-checked content are from AFP fact checking (181) followed by LeadStories (154) and Factcheck.ge (98) (Figure 3).
Figure 3: Amount of fact-checks by fact-checkers.
Figure 4: Identified location of users spreading fact-checks and misinformation.
Locations and Mentions
Using automatic entity extraction methods, we identify key locations and persons mention in the fact-checking articles in order to identify what location and person are the most discussed in misinforming content.
The top mentioned locations and persons are listed in Table 3 and Table 4.
| Location | Description | Current Week | Previous Week | Total |
|---|---|---|---|---|
| Ukraine | Sovereign state in eastern europe. | 1236 | 2781 | 139106 |
| worldwide | Published or operating in multiple or all jurisdictions on earth; special value for “place of publication” (p291) and “operating area” (p2541). | 467 | 5813 | 12135 |
| Americas | Landmass comprising the continents of north america and south america. | 391 | 5503 | 5901 |
| United States of America | Sovereign state in north america. | 199 | 634 | 34740 |
| Russia | Sovereign state in eastern europe and northern asia. | 195 | 825 | 24352 |
| Moscow | Capital and most populous city of russia. | 184 | 1942 | 10008 |
| Europe | Continent on earth, mainly on the northeastern quadrant, i.e. north-western eurasia. | 158 | 169 | 33849 |
| Mariupol | City in donetsk oblast in southeastern ukraine. | 109 | 166 | 1437 |
| Donetsk | Capital city of donetsk oblast in estern ukraine. | 103 | 22 | 1959 |
| Germany | Sovereign state in central europe. | 102 | 273 | 10091 |
Table 3: Top locations mentioned in misinforming posts.
| Person | Description | Current Week | Previous Week | Total |
|---|---|---|---|---|
| Anthony Fauci | American immunologist and head of the u.s. National institute of allergy and infectious diseases. | 391 | 5503 | 5894 |
| Volodymyr Zelenskyi | 6th president of ukraine. | 219 | 1800 | 50725 |
| Vladimir Putin | 2nd and 4th president of russia. | 199 | 234 | 56668 |
| Adolf Hitler | Austrian-born german politician, chancellor and führer of germany, leader of the nazi party (1889-1945). | 101 | 0 | 153 |
| Arsen Pavlov | Russian rebel troup leader in donbass. | 96 | 0 | 96 |
| Sergey Lavrov | Russian politician and foreign minister. | 93 | 4 | 429 |
| Bill Clinton | 42nd president of the united states. | 86 | 20 | 859 |
| Joe Biden | President-elect of the united states, former vice president (2009–2017). | 82 | 241 | 3953 |
| Viktor Yanukovych | Ukrainian politician who was the president of ukraine. | 76 | 41 | 2168 |
| Barack Obama | 44th president of the united states. | 72 | 4 | 540 |
Table 4: Top people mentioned in misinforming posts.
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 5: 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.