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 08 November 2021 and Monday 15 November 2021.
Key Content and Provenance
During the period between Monday 08 November 2021 and Monday 15 November 2021, 10,809 new URLs have been identified as potential misinforming content. Out of the 19 domains identified by Fact-checking organisations (Figure 1), most of the new shared URLs were from facebook.com with an increase of +10,785 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 alkhabrpress.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 facebook.com with a change of +3,068 compared to the previous total spread for the same domain whereas the domain that saw the least relative change was archive.md with a change of -4 compared to the previous period.
The all time most important domain is facebook.com with a total of 18,502 URL shares and the least popular domain is alkhabrpress.com with 1 shares (Figure 2).
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|
|Fact-check URL||Domain||Current Week||Previous Week||Total|
Fact-Checkers and Spreaders Location
The data used for creating the Twitter dataset is obtained from 140 fact-checking organisations.
The largest amount of fact-checked content comes from VoxCheck (350 fact-checks) and the least from Verify Sy (1 fact-checks). Most fact-checked content are from euvsdisinfo.eu (335) followed by LeadStories (255) and AFP fact checking (201) (Figure 3).
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||Country in eastern europe.||16||0||16|
|worldwide||Published or operating in multiple or all jurisdictions on earth; special value for “place of publication” (p291) and “operating area” (p2541).||16||0||16|
|United States of America||Country located mainly in north america.||0||4||4|
|Person||Description||Current Week||Previous Week||Total|
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.
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.