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 27 February 2023 and Monday 06 March 2023.

254,478 Misinforming Tweets
New:+508 Trend:+123
91,872 Fact-checking Tweets
New:+298 Trend:-58
5,776 Fact-checks
143 Fact-checking Organisations

Key Content and Provenance

During the period between Monday 27 February 2023 and Monday 06 March 2023, 508 new URLs have been identified as potential misinforming content. Out of the 289 domains identified by Fact-checking organisations (Figure 1), most of the new shared URLs were from twitter.com with an increase of +428 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 +144 compared to the previous total spread for the same domain whereas the domain that saw the least relative change was fullfact.org with a change of -65 compared to the previous period.

The all time most important domain is twitter.com with a total of 183,680 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/JJIzydorczyk/status/1630251854201331712 Demagog twitter.com 311 0 311
https://twitter.com/snicklink/status/1629578813494444033 Correctiv twitter.com 111 257 368
https://www.globaltimes.cn/page/202203/1254217.shtml StopFake.org globaltimes.cn 32 3 1607
https://www.pronews.gr/amyna-asfaleia/ektakto-o-v-zelenski-zitise-apo-tis-xores-tou-nato-na-steiloun-strato-stin-oukrania-vinteo Ellinika Hoaxes (Greek Hoaxes) pronews.gr 10 0 10
https://sputniknews.lat/20230227/las-armas-enviadas-a-ucrania-acaban-en-manos-de-bandas-criminales-en-suecia-segun-reportes--1136243086.html euvsdisinfo.eu sputniknews.lat 9 0 9
https://www.youtube.com/watch?v=LAU3ktiq5yg Fundacja “Przeciwdziałamy Dezinformacji” youtube.com 5 5 762
https://www.youtube.com/watch?v=6LQSYmda0Sc LeadStories youtube.com 3 3 9044
https://unherd.com/2022/03/how-ukrainian-women-will-suffer Maldita.es unherd.com 3 1 949
https://twitter.com/JahnTeam/status/1510597099137736705 Correctiv twitter.com 3 0 1387
https://www.el.gr/diethni/strimogmenos-zelenski-pros-ipa-stei Ellinika Hoaxes (Greek Hoaxes) el.gr 3 0 3

Table 1: Top misinforming content.

Fact-check URL Domain Current Week Previous Week Total
https://factcheck.afp.com/doc.afp.com.33AB726 afp.com 82 0 82
https://factcheck.afp.com/doc.afp.com.33A82WT afp.com 21 0 21
https://factcheck.afp.com/doc.afp.com.33A98PR afp.com 20 0 20
https://factuel.afp.com/doc.afp.com.33AF44Q afp.com 20 0 20
https://factcheck.afp.com/doc.afp.com.32JY8PP-1 afp.com 16 18 153
https://factcheck.afp.com/doc.afp.com.32486M8 afp.com 10 2 195
https://www.knack.be/factcheck/factcheck-nee-deze-video-toont-geen-protest-om-ontslag-zelenski-te-eisen-maar-manifestatie-na-moord-op-slovaakse-journalist/ knack.be 9 0 14
https://www.ellinikahoaxes.gr/2023/03/02/kurt-isis-ukraine-missing-context/ ellinikahoaxes.gr 7 0 7
https://correctiv.org/faktencheck/2023/02/27/dieselbe-iban-anderer-zweck-gelder-fuer-die-tuerkei-und-syrien-landen-nicht-in-der-ukraine/ correctiv.org 6 0 6
https://mythdetector.ge/en/kremlin-propaganda-claims-that-zelenskyy-has-a-doppelganger/ mythdetector.ge 6 0 6

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’]. 433 475 134551
P [‘Country in central europe’]. 332 53 15445
G [‘Country in central europe’]. 137 353 15457
E [‘Continent’]. 74 34 17893
R [‘Statue in chadron, united states of america - frédéric auguste bartholdi - 1950’]. 41 23 8156
F [‘Italian comune’]. 35 10 3100
S [‘Sculpture on liberty island in new york harbor in new york city, new york, united states’]. 23 40 8453
N [‘Most populous city in the united states of america’]. 18 24 3884
D [‘Capital and largest city of syria’]. 16 5 2347
A [‘Country in central and south asia’]. 15 37 6017

Table 3: Top locations mentioned in misinforming posts.

Person Description Current Week Previous Week Total
V [‘President of russia (1999–2008, 2012–present)’]. 201 113 61251
J [‘President of the united states since 2021’]. 143 44 15518
B [‘King of thailand (1927-2016)’]. 141 324 2665
S [‘Russian political figure’]. 113 257 721
P [‘266th pope of the catholic church’]. 44 41 2446
E [‘President of france since 2017’]. 30 28 7891
M [‘Ukrainian politician’]. 25 21 3112
O [‘Ukrainian politician and entertainer’]. 8 0 2133
A [‘Austrian-born german politician, dictator of germany from 1933 until his death in 1945’]. 4 24 4853
H [‘Ukrainian energy minister’]. 4 16 2268

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.