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 20 February 2023 and Monday 27 February 2023.

253,970 Misinforming Tweets
New:+385 Trend:+337
91,574 Fact-checking Tweets
New:+356 Trend:+168
5,776 Fact-checks
143 Fact-checking Organisations

Key Content and Provenance

During the period between Monday 20 February 2023 and Monday 27 February 2023, 385 new URLs have been identified as potential misinforming content. Out of the 288 domains identified by Fact-checking organisations (Figure 1), most of the new shared URLs were from twitter.com with an increase of +284 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 15min.lt 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 twitter.com with a change of +278 compared to the previous total spread for the same domain whereas the domain that saw the least relative change was stopfake.org with a change of -30 compared to the previous period.

The all time most important domain is twitter.com with a total of 183,252 URL shares and the least popular domain is 24-post.com 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/snicklink/status/1629578813494444033 Correctiv twitter.com 257 0 257
https://twitter.com/runews/status/1622170096675299329 AFP Fact Check twitter.com 27 6 2419
https://sputniknews.lat/20230220/la-visita-de-biden-confirma-que-ucrania-hace-lo-que-eeuu-le-dice-que-haga-1136006903.html euvsdisinfo.eu sputniknews.lat 20 0 20
https://sputniknews.lat/20230222/el-secuestro-de-ninos-ucranianos-y-otros-crimenes-mediaticos-de-occidente-1136052074.html euvsdisinfo.eu sputniknews.lat 15 0 15
https://www.kp.ru/daily/27467/4723314/ euvsdisinfo.eu kp.ru 13 1 14
https://reseauinternational.net/un-an-doperation-speciale-quel-bilan/ euvsdisinfo.eu reseauinternational.net 13 0 13
https://www.youtube.com/watch?v=LAU3ktiq5yg Fundacja “Przeciwdziałamy Dezinformacji” youtube.com 5 0 757
https://ria.ru/20230221/pushilin-1853311310.html euvsdisinfo.eu ria.ru 5 0 5
https://tass.com/defense/1580745 euvsdisinfo.eu tass.com 4 0 4
https://www.globaltimes.cn/page/202203/1254217.shtml StopFake.org globaltimes.cn 3 9 1575

Table 1: Top misinforming content.

Fact-check URL Domain Current Week Previous Week Total
https://fullfact.org/online/ukraine-footage-actor-body-bag/ fullfact.org 63 0 264
https://verifica.efe.com/es-falso-que-borrell-haya-dicho-que-la-ue-es-el-ejercito-de-ucrania/ efe.com 25 0 25
https://factcheck.afp.com/doc.afp.com.32JY8PP-1 afp.com 18 3 137
https://www.factcheck.org/2022/03/video-shows-climate-protest-in-austria-not-crisis-actors-in-ukraine/ factcheck.org 16 0 84
https://correctiv.org/faktencheck/2023/02/20/foto-zeigt-kein-ukrainisches-tattoo-studio-das-hakenkreuze-zum-halben-preis-entfernt/ correctiv.org 16 0 16
https://correctiv.org/faktencheck/2023/02/21/nein-das-verteidigungsministerium-wies-ukrainische-soldaten-nicht-via-plakat-auf-das-verbot-von-hakenkreuzen-hin/ correctiv.org 15 0 15
https://verifica.efe.com/gobierno-britanico-no-ha-enviado-carta-refugiados-ucranianos/ efe.com 13 0 13
https://mythdetector.ge/en/does-volodymyr-zelenskyy-own-a-usd-35-million-villa-in-miami/ mythdetector.ge 11 0 14
https://faktencheck.afp.com/doc.afp.com.326W6PZ afp.com 10 0 14
https://factcheck.afp.com/doc.afp.com.339Q9TF afp.com 10 0 10

Table 2: Top fact-checked content.

Fact-Checkers and Spreaders Location

The data used for creating the Twitter dataset is obtained from 143 fact-checking organisations.

The largest amount of fact-checked content comes from euvsdisinfo.eu (840 fact-checks) and the least from Verify Sy (1 fact-checks). Most fact-checked content are from VoxCheck (352) followed by Factcheck.ge (277) and AFP fact checking (255) (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
U [‘Country in eastern europe’]. 475 205 134118
G [‘Country in central europe’]. 353 55 15320
M [‘Country in north america’]. 72 18 5405
P [‘Country in central europe’]. 53 31 15113
B [‘Capital city of iraq’]. 46 45 13359
I [‘Country in western asia’]. 41 32 24633
S [‘Sculpture on liberty island in new york harbor in new york city, new york, united states’]. 40 17 8430
A [‘Country in central and south asia’]. 37 4 6002
E [‘Continent’]. 34 40 17819
V [‘Sovereign state in northern south america’]. 28 1 2642

Table 3: Top locations mentioned in misinforming posts.

Person Description Current Week Previous Week Total
B [‘King of thailand (1927-2016)’]. 324 4 2524
S [‘Russian political figure’]. 257 0 608
V [‘President of russia (1999–2008, 2012–present)’]. 113 76 61050
J [‘President of the united states since 2021’]. 44 17 15375
P [‘266th pope of the catholic church’]. 41 3 2402
E [‘President of france since 2017’]. 28 12 7861
U [‘President of the european commission since 2019’]. 28 12 4935
A [‘Austrian-born german politician, dictator of germany from 1933 until his death in 1945’]. 24 6 4849
M [‘Ukrainian politician’]. 21 8 3087
H [‘Ukrainian energy minister’]. 16 16 2264

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.