War in Ukraine and Disinformation Newsletter 12 May 2022
12 May 2022
Russian propaganda targets non-Western audiences on Twitter; Chinese sources amplify Russian disinformation
We selected the most relevant media and research publications that explain how misinformation and influence operations during the Russia-Ukraine war are changing the global information environment. The newsletter is a collaboration between the Programme on Democracy and Technology and PeaceTech Lab. It is prepared by Dr Aliaksandr Herasimenka with the assistance of Danielle Recanati.
Chinese, Iranian and Russian state-backed media on Ukraine
Each week, we track how the global digital platform audiences interact with reporting on Ukraine by Chinese, Iranian and Russian state-backed media in English*. In March, we found that the audience of these media engaged – liked, commented or shared – most actively with the following topics:
We found that each topic received at least 18,000 engagements on social media. The social media audiences of Chinese state-backed media we track engaged especially actively with articles covering Russian claims about the work of biological research labs in Ukraine. Based on the computation of audience engagement, we found that these unconfirmed claims were more successfully amplified by Chinese rather than Russian state-backed media across the audiences measured. Russian state-backed coverage focused on NATO and Russia’s sanctions on US officials. Iran’s state-backed media covered all the mentioned topics nearly equally.
Twitter accounts of Russian diplomats
Twitter has announced that it will limit content from more than 300 official Russian government accounts, including that of Russian President Putin. However, in our analysis of 321 Twitter accounts of the Russian government and diplomats stationed in more than 130 countries, we found that Twitter inconsistently labels a significant share of Russian diplomatic accounts. DemTech researcher Marcel Schliebs found that less than half of embassy accounts and only about a quarter of central government accounts were labelled in accordance with Twitter’s own policy for labelling government accounts. This suggests that Twitter might not be able to limit all the known Twitter accounts of Russian diplomats.
The Massacre of Bucha – the discovery of mass graves and streets lined with dead civilians a town on the outskirts of the Ukrainian capital – became a war episode that attracted numerous attempts to spread propaganda. Russian state-linked sources spread several narratives that blamed the Ukraine side for the killings. For example, they shared video clips where a corpse can be “seen” moving its hand or where National Police of Ukraine entered Bucha, which allegedly proved no massacre occurred. However, fact-checking organisations showed that these were false claims. German intelligence analysed satellite imagery and intercepted radio messages indicating Russia’s involvement in the massacres.
Russian state-backed media content is one of the most shared across Spanish-speaking Twitter. According to the Digital Forensic Research Lab’s Esteban Ponce de Leon, RT en Español is now the third most shared site on Twitter for Spanish-language information about Russia’s invasion, outperforming local news sources, as well as international outlets like the BBC and CNN. DemTech alumnus Samuel Woolley expressed his concern in the Washington Post article that this demonstrates “RT’s success.”
Meta suspended some of the quality controls that ensure that posts from users in Russia, Ukraine and other Eastern European countries meet its rules. The New York Times reports that Meta has made more than half a dozen content policy revisions since Russia invaded Ukraine last month. “The workers could not keep up with shifting rules about what kinds of posts were allowed about the war in Ukraine,” the media reports.
Chinese sources amplify Russian disinformation about Ukraine and link Putin claims of “nazism in Ukraine” to the Hong Kong protests. This supposed to encourage solidarity between Russian and Chinese people against “foreign forces interfering with internal affairs,” the Guardian reports citing a Taiwan-based cyber monitoring group, Doublethink Lab. Russian authorities had pushed a narrative of “nazism in Ukraine” as a key justification for its invasion of the country. China has claimed a neutral stance on the war, but has refused to label Russia’s act as an “invasion.”
Ukrainians’ susceptibility to Russian disinformation depends on the topic and their ties to Russia. A recent study published in the International Journal of Press/Politics suggests that Ukrainians are more likely to believe disinformation about the economy than disinformation about politics, historical experience, or the military. Individuals who have partisan or ethnolinguistic ties to Russia are more likely to believe pro-Kremlin disinformation across topics.
Non-western countries might be the main target of Russia’s pro-war propaganda abroad. Researcher Carl Miller analysed Twitter accounts that supported Putin’s policies from BRICS, and Africa and Asia more broadly. He found that many of the accounts spread deceptive information, appear to be brand new, fake, hacked, or work in coordination with one another. Before the invasion, many of these accounts tweeted about political issues ranging from showing strong support for Indian Prime Minister Narendra Modi to promoting Tamil nationalism in Sri Lanka, the researcher claims.
Meta is failing to label 91% of Russian propaganda posts about Ukraine. In 2019, Meta announced that it would label state-controlled media to counter disinformation targeting US elections. Researchers at the Center for Countering Digital Hate examined almost 4,000 articles by RT, Sputnik News and TASS on Facebook and posts featuring the 100 most popular articles from this sample and found that the company is not complying with this commitment.
Data for the period between 14-03-22 to 22-03-22: we collect data from several popular platforms using their Application Programme Interfaces. Our research is informed by a combination of manual and automatic coding of online content. We capture articles that mention “Ukraine,” “Luhansk,” “Donetsk,” “NATO,” and “Russia” in the title or caption of the article and that are shared on platforms. The articles are filtered down to only articles written in English. After selecting the articles, we gather the full text for each one to create a model. This model groups topics of articles together based on how similar the contents in the article text were to each other. We label the article clusters by reviewing the top 20 words most likely to appear in the articles for that cluster and the top five articles with the strongest connection to the topic model. The table below shows the news outlets included in the topic model.
|People’s Daily, ECNS, CCTV, CGTN, China Daily, Global Times, Xinhua Net, Beijing Review||China|
|RT, Sputnik News, Tass||Russia|
|Tasnim News, Press TV, IRNA||Iran|
Research by Anna George, Dorian Quelle and Marcel Schliebs, Programme on Democracy and Technology
12 May 2022
4 May 2022
26 April 2022
20 April 2022