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 11 July 2022 and Monday 18 July 2022.
New:+168 Trend:-15
77,016 Fact-checking Tweets
New:+398 Trend:-46
3,813 Fact-checks
138 Fact-checking Organisations
Key Content and Provenance
During the period between Monday 11 July 2022 and Monday 18 July 2022, 168 new URLs have been identified as potential misinforming content. Out of the 227 domains identified by Fact-checking organisations (Figure 1), most of the new shared URLs were from stopfake.org with an increase of +125 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 correctiv.org with a change of +95 compared to the previous total spread for the same domain whereas the domain that saw the least relative change was knack.be with a change of -109 compared to the previous period.
The all time most important domain is twitter.com with a total of 154,809 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.
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 138 fact-checking organisations.
The largest amount of fact-checked content comes from euvsdisinfo.eu (295 fact-checks) and the least from Verify Sy (1 fact-checks). Most fact-checked content are from LeadStories (255) followed by AFP fact checking (199) and Factcheck.ge (138) (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. | 351 | 318 | 145343 |
| Russia | Sovereign state in eastern europe and northern asia. | 176 | 44 | 23548 |
| Germany | Country in central europe. | 69 | 27 | 10506 |
| United States of America | Sovereign state in north america. | 61 | 57 | 33858 |
| Europe | Continent on earth, mainly on the northeastern quadrant, i.e. north-western eurasia. | 51 | 78 | 34509 |
| Earth | Third planet from the sun in the solar system. | 48 | 43 | 21100 |
| Spain | Sovereign state in southwestern europe with territories in the mediterranean sea, the atlantic ocean and northern africa. | 39 | 28 | 5197 |
| Moscow | Capital and most populous city of russia. | 37 | 15 | 10667 |
| Madrid | Capital and largest city of spain. | 34 | 0 | 2141 |
| Italy | Sovereign state in southern europe. | 33 | 2 | 1589 |
Table 3: Top locations mentioned in misinforming posts.
| Person | Description | Current Week | Previous Week | Total |
|---|---|---|---|---|
| Volodymyr Zelenskyy | Sixth and current president of ukraine. | 39 | 53 | 51859 |
| Leonardo da Vinci | Italian renaissance polymath (1452-1519). | 33 | 0 | 33 |
| Vladimir Putin | 2nd and 4th president of russia. | 27 | 93 | 53970 |
| Jens Stoltenberg | Norwegian politician, 13th secretary-general of nato, 27th prime minister of norway. | 24 | 1 | 238 |
| Joe Biden | President-elect of the united states, former vice president (2009–2017). | 20 | 5 | 4153 |
| President of the United States | Head of state and head of government of the united states of america. | 17 | 7 | 5789 |
| Ursula von der Leyen | German politician, president of the european commission. | 14 | 1 | 2238 |
| Serhiy Marchenko | Ukrainian economist and politician. | 14 | 1 | 15 |
| Anthony Fauci | American immunologist and head of the u.s. National institute of allergy and infectious diseases. | 12 | 17 | 6598 |
| Richard Nixon | 37th president of the united states of america (1913-1994). | 11 | 0 | 1688 |
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.