Abstract

Concerns over the existence of a global “information disorder” marked by the contamination of the public sphere with deception campaigns have grown in recent years. This “disorder” has domestic and international dimensions, with multiple state actors standing accused of malicious influence abroad. Previous research, focused on the Global North, has neglected the potential role of anti-colonial and anti-imperialist sentiments in shaping public opinion in the Global South, where problems with foreign influence operations have persisted for decades. Using survey data (N = 4,613) collected in Angola, Ethiopia, South Africa, and Zambia in late 2022, this paper addresses this knowledge gap by exploring the relationship between individuals’ worldviews and news consumption, and their support of strategic disinformation narratives favored by Russia and China, both of which have been active in trying to use the news media to influence public opinion. At a country level, we find that support for these narratives is most pronounced in Ethiopia and South Africa, while at an individual level, we find limited evidence that news consumption is connected to the adoption of these narratives. In discussing these findings, we argue that African public opinion is simultaneously shaped by global, geopolitical shifts and domestic, and local contestations.

Having control over how and what type of information flows from one country to another, particularly at times of military conflict or political struggle, has always been important to nation states (Lasswell, 1927). This is particularly acute in Africa, which has seen geopolitical confrontation play out in the form of proxy wars, from the colonial and post-colonial periods through the Cold War and beyond (Schmidt, 2013; Friedman, 2015). Military conflicts aside, information itself has for a long time been a contested battleground, and a subject of interest to scholars (la Cour, 2020), However, in recent years, geopolitical tensions have intensified this phenomenon, and international conflicts and disputes are increasingly taking on the character of “information wars” (Webster, 2003, p. 57). At the same time, older approaches to propaganda are increasingly being complemented by public diplomacy to extend influence over foreign publics (Rawnsley, 2015). Establishing credibility and trust as an authentic communicator to gain support is a key aspect of these efforts (Zaharna, 2004, p. 224).

All “information wars” have historically been mediated, but today, they are increasingly being waged on the internet and particularly on social media. In much of Africa, platforms such as Twitter, Facebook, or Instagram have become spaces for “epistemic proxy wars” (Pohjonen, 2022, p. 236) where competing truth claims reflect geopolitical and domestic conflicts. More and more states are competing for influence on the continent in online spaces, using not only public diplomacy strategies but also availing themselves of influence operations and disinformation campaigns that are aimed at promoting state-sponsored strategic disinformation narratives. In this paper, we understand “strategic disinformation narratives” as discursive constructions, designed to spread falsehoods, mislead, or distort facts to gain geopolitical influence. These efforts are directed at both online and legacy media spaces, as can be seen in both China’s and Russia’s re-establishment of African outposts—many of which had been in operation during the Cold War (Pradet, 1963)—for their global media platforms, including television, radio, wire services and online media (Douzet, Limonier, Mihoubi, & Rene, 2021). These occur at the same time as the US remains engaged in a new “scramble for Africa” to expand its influence as well as its military presence in the face of geopolitical threats (Turse, 2015, p. 11).

To disseminate their strategic disinformation narratives in Africa, actors like Russia and China are relying on a range of tools and activities. In the case of Russia, narratives, ideas, and content produced by its media agency Sputnik News and broadcast channel Russia Today (RT) are also relayed and circulated by local media networks (Douzet et al., 2021, p. 51). In the case of China, state media outlets such as China Global Television Network (CGTN), Xinhua, and China Radio International (CRI) have been central to Beijing’s efforts to strengthen China-Africa relations and support China’s economic activities on the continent (Zhang, Wasserman, & Mano, 2016). So crucial a part has media been to the Chinese approach to extend its influence on the continent that some have suggested that China–Africa relations need to be viewed through the lens of mediatization theory, that is the view that communication is seen as the basis for the permeation of China’s material and symbolic power on the continent (Li, 2017, p. 6).

Western media powers like the US, the UK, and France remain active (and oftentimes contested) players in the African information space, through platforms such as the Voice of America (VOA), BBC Africa, and France24. Once perceived as dominant (Wasserman, 2018), these actors are now competing for attention with other foreign media. In the current climate of “information disorder” (Wardle & Derakshan, 2017), where the public sphere is characterized by false information, rumors, hate speech, and deception, concern has been growing about the role China and Russia are playing in the media space of many African countries and the extent to which Russian and Chinese strategic narratives may include disinformation and inauthentic content. This concern has been growing globally, particularly since the 2016 US elections, which are seen as a prime example of how the Russian government was able to use social media to influence public opinion elsewhere (McGregor, Barrett, & Kreiss, 2022). In the wake of its invasion of Ukraine in 2022, Russia also targeted online information spaces in the Global South to raise support for its military actions (Blankenship & Ordu, 2022a). Russian disinformation campaigns sought to capitalize on divided African opinions about the military conflict in Ukraine to secure and deepen its influence on the continent (Blankenship & Ordu, 2022a).

Scholarly works on the renewed interest of global powers to influence public opinion in Africa are on the rise. Research has primarily focused on mapping the breadth of activities aimed at influencing public opinion through the news media (e.g., KAS, 2021) and uncovering networks of covert influence activities, particularly on social media (e.g., Grossman, Bush & DiResta, 2019). Much less work has gone into understanding the impact of these efforts or unpacking the factors that might lead to the success (or failure) of attempts by foreign actors to disseminate disinformation connected to geopolitical debates. This paper is a first attempt at addressing the latter by examining the role that two sets of factors at the individual level (media consumption and worldviews) play in supporting strategic disinformation narratives by foreign actors. We focus our analysis on four Sub-Saharan countries (Angola, Ethiopia, South Africa, and Zambia) with different degrees of engagement with China and Russia. In doing so, we are also able to examine country-level differences and their connection to foreign policy.

Strategic Narratives and Disinformation

Strategic narratives can be defined as “tools that political actors employ to promote their interests, values, and aspirations for the international order by managing expectations and altering the discursive environment” (Miskimmon, OLoughlin, & Roselle, 2017, p. 3). Narratives were important during most of the Cold War but have become again more strategic in recent years as geopolitical power relations shifted, and authoritarian regimes have adopted new ways to legitimize their rule (Dukalskis, 2018). One such shift occurred in the aftermath of the 9/11 attacks on the US when a need was identified to replace the Cold War narrative of “containment” and US President George W. Bush’s “Global War on Terror” with more unifying ones (Freedman, 2015). Such a narrative could help build consensus to support the implementation of national strategy and foreign policy (Freedman, 2015). The emergence of the BRICS (Brazil, Russia, India, China, and South Africa) group of countries was another recent shift that led to the questioning of strategic narratives underpinning the international system, and an assertion of these countries’ collective identity with an emphasis on infrastructural development (Van Noort, 2017).

The growing influence of social media in the global media ecology, alongside the creation and extension of nation-branding TV news channels (Morales, 2020), and the increasing divide between Western liberal democracies and autocratic illiberal regimes such as Russia, China, or Iran, have brought renewed attention to the role of strategic media narratives (Hagström & Gustafsson, 2021). Occurring within a growing global “information disorder” (Wardle & Derakshan, 2017), these narratives often avail themselves of the affordances of evolving digital platforms to create what may be called “strategic disinformation narratives”, that is, narratives designed to spread falsehoods, mislead, or distort facts to gain geopolitical influence. The renewed Russian invasion of Ukraine in 2022 illustrated how much distortion or obscuration of facts can be used to construct an alternative narrative to justify the war and gain international support (Blankenship & Ordu, 2022b). In constructing its range of strategic disinformation narratives aimed at countries in the Global South (from the idea that the War in Ukraine was caused by NATO to the claim that Russia is fighting Nazism in Ukraine), Russia has drawn on pre-existing tensions and grievances towards the West and utilized tropes such as racism and colonialism (Blankenship & Ordu, 2022b). These competing strategic narratives have increasingly been playing out online, and no longer are only aimed at strengthening the image of these countries on the continent, but also providing contesting ideological visions. China and Russia have both been particularly active players in this geopolitical game, pushing out not only pro-China or pro-Russian messages but also anti-Western ones.

Oftentimes, the boundary between strategic narratives and disinformation is blurry. In the case of Russia, especially during the most recent invasion of Ukraine, but also regarding its military partnerships with countries in the Sahel, its strategic narratives take the form of pure information warfare linked to a military strategy that directly opposes the European Union’s (EU) efforts in the region (Lebovich & Murphy, 2022). In pursuing this strategic objective, Russia has been using predominantly social media, coupled with state media outlets like Sputnik and RT, to amplify anti-French sentiments (Shurkin, 2022). Russia’s information warfare includes disinformation that is spread through web pages designed to look like legitimate local news sources but which in fact promote Russia’s foreign policy playbook (Grossman et al., 2019).

Another foreign actor that has looked at reshaping African public opinion in recent years is China. Unlike in the case of Russia, where a clear information warfare approach can be discerned, it is more difficult to establish the boundary between propaganda, efforts to harness soft power, and disinformation in the case of China. As mentioned above, China has extended the footprint of its state-owned media on the continent significantly, but it has also launched social media campaigns to counter critical views about events and policies that have negatively impacted its global image (Repnikova & Chen, 2023). Allegations of ethnic cleansing in Xinjiang, suppression of pro-democracy protests in Hong Kong, and China’s handling of the COVID-19 pandemic through ongoing lockdowns (Yang, 2022) have all contributed to the diminishing of China’s global image, including in some African countries (Madrid-Morales & Wasserman, 2022). Beijing has taken to more aggressively countering criticism through coordinated top-down information campaigns (Douzet et al., 2021; Kinetz, 2021), led by “Wolf Warrior” diplomats, and by using the domestic media in target countries to promote ideas aligned with China’s preferred strategic narratives (Rolland, 2021).

African Foreign Policy and Strategic Narratives

The recent attempts by both China and Russia to extend their influence in Africa using news media platforms, a heightened social media presence, and information warfare—which includes misleading or false information—should be seen against a longer historical backdrop of Sino- and Russo-African relations. Interactions between China, Russia, and Africa go back to the support provided to some African countries during their struggles against colonialism and apartheid (Pradet, 1963; Shinn, 2019). These legacies may matter when assessing the impact of Russian- and Chinese-favored narratives. Appeals to this history of interactions have most recently been made during the invasion of Ukraine by Russia and may have resulted in the decision of several African countries to abstain from a UN vote to condemn Russia’s actions (Tawat, 2022). Moreover, Russia’s diplomacy in Africa also took the form of regular tours of the continent by Russian foreign minister Sergey Lavrov in 2023, who visited 10 countries (McGlynn, 2023). This was followed shortly after by joint naval exercises between South Africa, China, and Russia (Sguazzin, 2023).

In addition to historical legacies, in understanding the impact of strategic narratives, it may also be useful to consider more contemporary foreign policy alignments. For example, in the wider global geopolitical repositioning that we describe above, Russia and China have actively involved South Africa, which was invited to join BRICS in 2010, as the sole African representative. Critics of South Africa’s membership have seen this alignment as representing a new type of imperialism and a “scramble for Africa” (Taylor, 2017). However, since its inclusion in the grouping, South Africa has used its membership to discursively position itself as the economic leader on the continent by capitalizing on its association with a prestigious club of emerging economic powers. South Africa’s hosting of BRICS summits has also provided it with an opportunity to showcase itself on a global stage (Nkoana-Mashabane, 2012). However, this positioning of South Africa within BRICS has, at the same time, put it in a difficult diplomatic position, particularly in connection to Russia’s invasion of Ukraine. South Africa’s adoption of a formally non-aligned position with regard to the conflict, while refusing to condemn it, has suggested to some observers that the country is moving closer to the BRICS sphere of influence and further away from the “Western” orbit (Caballero, 2023).

A clear example of how South Africa’s membership of BRICS caused it to walk a tightrope was the political wrangling around the attendance of Russia’s President Vladimir Putin at the BRICS summit in South Africa in August 2023. Media speculation was rife that Putin would face arrest under an International Criminal Court (ICC) order if he attended, as South Africa is an ICC signatory and would have been obligated to aid in his arrest. In what was widely seen as a diplomatic coup for South Africa’s President Cyril Ramaphosa, Putin announced that he would not attend in person but participate virtually via videoconference (Eligon, 2023). This diplomatic crisis brought to the fore the competing media narratives surrounding the implication of South Africa’s membership of the BRICS group for its future relationship with Western superpowers.

As the only African nation in BRICS, South Africa offers a theoretically relevant reference point to examine how widely adopted Chinese and Russian strategic disinformation narratives are across the continent. Given the diverse shared histories and depth of diplomatic, economic, and military ties, not all countries in Africa might respond in the same way to the same narratives (Schmitt, 2018). South Africa’s membership of BRICS, and its recent foreign policy statements, would seem to indicate that certain Chinese- and Russian-favored narratives would have high adoption/support rates and that these rates would probably be higher than in other countries on the continent. Building on this argument, we formulate the following hypothesis:

 

H1: The support for Chinese- and Russian-favored strategic disinformation narratives will be higher in South Africa than in other African countries.

Foreign Media Consumption and Public Opinion in Africa

In trying to spread their countries’ strategic narratives across Africa, Chinese, and Russian media have come in direct competition with media outlets of Western countries, which have also historically been present on the continent, particularly in their former colonial spheres of influence (Wasserman, 2018). These competing narratives had already been part of the battle for influence during the postcolonial era. Throughout the Cold War, the USSR, and the US saw Africa as an important terrain to strive for discursive dominance (Russell & Pichon, 2019). Today, global media outlets linked to former colonial powers, such as France and the UK, continue their presence on the African continent, but these channels now must compete for attention in an increasingly crowded space for global media on the continent. Not only have Russia and China expanded their footprint on the continent in recent years, but African news channels themselves have displayed pan-African ambitions, such as the South African Broadcasting Corporation (SABC) and E News Channel Africa (eNCA) which are aimed at reaching audiences beyond the borders of South Africa (Ndlovu, 2018).

There is already some evidence that attempts to shape public opinion via the news media are paying off, albeit in a still limited way. Recent survey data (Madrid-Morales & Wasserman, 2022) have shown a positive relationship between the consumption of English-language Chinese media in Sub-Saharan Africa and positive attitudes toward China. Chinese state-owned media, that survey showed, have a limited but growing following on the continent, and those media users who do report getting news from Chinese media have better attitudes towards China than those who do not get their news from those outlets. However different African countries would likely see different degrees of exposure to different foreign media. For instance, in Angola and Ethiopia, two of the countries included in the empirical part of this paper, it might be that audiences would have less exposure to Chinese or Russian media given that these countries provide limited content in Portuguese and no content in Amharic. At the same time, exposure in Zambia and South Africa could be higher given that English-language content offered by channels such as CGTN and RT would be more widely understood. Another factor that may influence audience attitudes is the prominence of China and Russia on the news agendas. For instance, in South Africa, because of its BRICS membership, news about China and Russia, or South Africa’s relations with these countries are likely to be more common than in other countries, where topics related to China and/or Russia might not generate a lot of media coverage. Considering the existing evidence, we propose the following hypothesis:

 

H2: Consumption of Chinese/Russian media will lead to a higher adoption of Chinese-/Russian-favored strategic narratives.

Anti-Americanism and Chinese and Russian Strategic Narratives

There has been some debate in the literature regarding the extent of pro- or anti-American sentiment in Sub-Saharan Africa. Globally, attitudes towards the US have waxed and waned in response to crises such as the Iraq war in 2003, or the election of a popular president like Barack Obama or an unpopular one like Donald Trump. As Chiozza (2009, p. 4) notes, “Popular opinion of the United States takes a loose and multifaceted form in which negative and positive elements coexist with no apparent tensions.” Anti-Americanism more broadly in the Global South has also been associated with nationalism, Marxism, or Islamic fundamentalism (Rubinstein & Smith, 1988). Previous survey data have suggested that Africans have more positive attitudes towards the US than China, Iran, Russia, and Japan combined (Duncan, Moehler, & Silver, 2015). Pro-American attitudes on the continent can be explained as resulting from Africans’ experience with statist, authoritarian, and weak governments, leading to admiration for the US domestic political model (Duncan et al., 2015). Equally important for this current study is Duncan et al. (2015) finding that the more politically informed respondents are, and the more they follow world news, the more likely they are to be anti-American.

At the same time, there is also a legacy of anti-Western and, in particular, anti-US sentiment in parts of Sub-Saharan Africa. In a 2021 poll conducted by Afrobarometer, a non-partisan research network that conducts public attitude surveys, China scored higher (63% of respondents) than the US (60%) in response to the question of whether China’s, or the US’ influence on their country was more positive (Sanny & Selormey, 2021). This matters because oftentimes foreign policy is interpreted through this domestic lens. Russia has also used what has been referred to as “memory diplomacy” in its dealings with African countries, to remind them of Russia’s support during their struggles for independence (McGlynn, 2023). In its most recent attempts to garner African support for its invasion of Ukraine, Russia has again invoked this anti-imperialist rhetoric (McGlynn, 2023). Elsewhere on the continent, anti-Western sentiments had already been seen in Ethiopia’s expulsion of United Nations officials over the UN’s criticism of Ethiopia’s war against Tigray (Anna, 2021). Ethiopia also revoked the licenses of several foreign media outlets working in the region, barring them from operating, a move widely seen as retribution for critical coverage of the Tigray conflict (IPI, 2023).

Amidst ongoing anti-Western and anti-imperialist rhetoric, African governments often look to China as an alternative model for development. Countries such as Kenya and Zimbabwe have increasingly "looked East” to find a new economic partner (Youde, 2007). Politicians also often make pro-Russia statements, such as those by the Economic Freedom Fighters (EFF) in South Africa (Fabricius, 2022), which are sometimes framed in the language of anti-imperialism, resonating with a long-standing tendency for African rulers to justify their decisions against the backdrop of historical colonial injustices (e.g., in Zimbabwe, see Phimister & Raftopoulos, 2004). The US might be respected or aspired to as a place to study by some or seen as having an attractive popular culture by others, but decades of military interventions and covert operations appear to have made some people reluctant to support US policies. Conversely, in some of these countries, sentiment towards China and Russia has been improving or, at least, remains ambivalent. Considering this dynamic of possible tilting of African countries towards “the East,” we hypothesize:

 

H3a: Pro-US worldviews will be negatively associated with support of the Chinese- and Russian-favored strategic narratives.

 

H3b: Pro-China and Russia worldviews will be positively associated with support of Chinese- and Russian-favored strategic narratives.

Methods

This paper uses data from a non-probability sample online survey fielded in Angola, Ethiopia, South Africa, and Zambia between November 14, 2022, and December 8, 2022 (N = 4,613). Surveys were distributed in one of the official languages in each country: English in South Africa and Zambia, Portuguese in Angola, and Amharic in Ethiopia. Translations were conducted from the English version by a native speaker of the target language and cross-translated for accuracy by another native speaker. The design of this study was approved by the Ethics Committees of the University of Sheffield’s School of Journalism, Media and Communication and the University of Cape Town’ Centre for Film and Media Studies.

Sampling

Respondents were recruited by TGM, a company providing access to panels of respondents, through various online channels. We sought to recruit 1,200 participants per country, but difficulties in recruiting older participants in Angola resulted in a smaller sample size than planned for the country (nAngola = 998, nEthiopia = 1,203, nSouth Africa = 1,203, and nZambia = 1,209). Each participant received compensation for their participation based on TGM’s reward system. During the data collection stage, to increase data quality, we monitored responses and removed from the final sample both speeders (respondents who completed the survey in less than one-third of the median completion time) and straight-liners, defined as respondents who “give identical (or nearly identical) answers to items in a battery of questions using the same response scale” (Kim, Dykema, Stevenson, Black, & Moberg, 2019). In total, we discarded n = 112 responses. To increase the representativity of the sample, we enforced quotas around age, gender, and place of residence. Despite our efforts, limits in the composition of the online panels we drew on meant that our sample skews younger (M = 31.19; SD = 9.96), more urban (68.7% live in the capital or surrounding area), and more highly educated (the median educational attainment is “Some university”) than the national average in each of the countries. In addition, in Angola, and to a lesser extent in Ethiopia, our sample does not match census gender ratios as it has a larger proportion of males than females. Supplementary Table A1 in the Appendix summarizes descriptive statistics for all demographic variables by country. Similar problems with representativeness have been reported by other studies that use online panels in Sub-Saharan Africa and elsewhere (Andrews, Nonnecke, & Preece, 2003). While these limitations mean that we are unable to generalize the findings presented below to the entire population of the four countries under study, our data do offer insights into a subset of the population (young, urban, and educated online media consumers) that is of relevance to the topic this paper focuses on.

Country Selection

The four countries included in the study (Angola, Ethiopia, South Africa, and Zambia) were selected because of their close political, military, economic, and media ties with China, Russia, or both countries. Table 1 presents an overview of indicators that highlight the depth of ties. For example, in 2021, China was the number one destination of Angolan and South African exports, the second one for Zambia, and the seventh for Ethiopia (UN Comtrade, 2022). China is also the main supplier of military equipment to Zambia, and one of the top 20 for Ethiopia (SIPRI, 2022). Diplomatically, all countries in the sample have high levels of agreement with China in UN voting patterns (Bailey, Strezhnev, & Voeten, 2017). In addition, for South Africa and Zambia, China is also an important media partner. Multiple South African media organizations have entered content agreements with Chinese news outlets, and, in Zambia, StarTimes has a long-running joint venture with the national broadcaster, ZNBC (KAS, 2021). While these countries’ ties with Russia appear modest in comparison to China’s, in some areas, they are also significant. For example, Angola counts Russia as the number one provider of military equipment and is South Africa’s second (SIPRI, 2022). Diplomatic alignment between the four countries and Russia is also relatively high at over 70%. For comparison, the agreement with the U.S. stands at around 30% (Bailey et al., 2017). South Africa is used throughout this study as a point of comparison due to its unique geopolitical connection with China and Russia because of their shared membership of BRICS. This allows us to compare, at a country level, the possible role that this closer political alignment in international affairs might have on domestic public opinion.

Table 1.

Economic, Military, Political, and Media Ties Between Russia and China, and sampled countries

AngolaEthiopiaSouth AfricaZambia
Russia
 Exports to Russia in 2021*US$2.4M
(53/149 countries)
US$26.7M
(28/165 countries)
US$686M
(34/211 countries)
US$6.93M
(46/139 countries)
 Imports from Russia in 2021*US$187M
(94/192 countries)
US$174M
(95/192 countries)
US$616M
(64/192 countries)
US$17.6M
(138/192 countries)
 UN votes (average % agreement 2011–2022)77.60%75.20%76.50%74.40%
 Military supplies (% of arms imports by Russia 2011–2022)§56.90%9.50%12.00%8.20%
 Media presence/cooperationLowLowSomeLow
China
 Exports to China in 2021*US$20.4B
(1/149 countries)
US$148M
(7/165 countries)
US$20.6B
(1/211 countries)
US$2.26B
(2/139 countries)
 Imports from China in 2021*US$2.28B
(97/209 countries)
US$2.8B
(85/209 countries)
US$20.5B
(34/209 countries)
US$951M
(125/209 countries)
 UN Votes (average % agreement 2011–2022)95.70%94.90%93.80%95.60%
 Military supplies (% of arms imports by China 2011–2022)§8.50%16.20%50.90%
 Media presence and cooperationLowSomeHighHigh
AngolaEthiopiaSouth AfricaZambia
Russia
 Exports to Russia in 2021*US$2.4M
(53/149 countries)
US$26.7M
(28/165 countries)
US$686M
(34/211 countries)
US$6.93M
(46/139 countries)
 Imports from Russia in 2021*US$187M
(94/192 countries)
US$174M
(95/192 countries)
US$616M
(64/192 countries)
US$17.6M
(138/192 countries)
 UN votes (average % agreement 2011–2022)77.60%75.20%76.50%74.40%
 Military supplies (% of arms imports by Russia 2011–2022)§56.90%9.50%12.00%8.20%
 Media presence/cooperationLowLowSomeLow
China
 Exports to China in 2021*US$20.4B
(1/149 countries)
US$148M
(7/165 countries)
US$20.6B
(1/211 countries)
US$2.26B
(2/139 countries)
 Imports from China in 2021*US$2.28B
(97/209 countries)
US$2.8B
(85/209 countries)
US$20.5B
(34/209 countries)
US$951M
(125/209 countries)
 UN Votes (average % agreement 2011–2022)95.70%94.90%93.80%95.60%
 Military supplies (% of arms imports by China 2011–2022)§8.50%16.20%50.90%
 Media presence and cooperationLowSomeHighHigh
Table 1.

Economic, Military, Political, and Media Ties Between Russia and China, and sampled countries

AngolaEthiopiaSouth AfricaZambia
Russia
 Exports to Russia in 2021*US$2.4M
(53/149 countries)
US$26.7M
(28/165 countries)
US$686M
(34/211 countries)
US$6.93M
(46/139 countries)
 Imports from Russia in 2021*US$187M
(94/192 countries)
US$174M
(95/192 countries)
US$616M
(64/192 countries)
US$17.6M
(138/192 countries)
 UN votes (average % agreement 2011–2022)77.60%75.20%76.50%74.40%
 Military supplies (% of arms imports by Russia 2011–2022)§56.90%9.50%12.00%8.20%
 Media presence/cooperationLowLowSomeLow
China
 Exports to China in 2021*US$20.4B
(1/149 countries)
US$148M
(7/165 countries)
US$20.6B
(1/211 countries)
US$2.26B
(2/139 countries)
 Imports from China in 2021*US$2.28B
(97/209 countries)
US$2.8B
(85/209 countries)
US$20.5B
(34/209 countries)
US$951M
(125/209 countries)
 UN Votes (average % agreement 2011–2022)95.70%94.90%93.80%95.60%
 Military supplies (% of arms imports by China 2011–2022)§8.50%16.20%50.90%
 Media presence and cooperationLowSomeHighHigh
AngolaEthiopiaSouth AfricaZambia
Russia
 Exports to Russia in 2021*US$2.4M
(53/149 countries)
US$26.7M
(28/165 countries)
US$686M
(34/211 countries)
US$6.93M
(46/139 countries)
 Imports from Russia in 2021*US$187M
(94/192 countries)
US$174M
(95/192 countries)
US$616M
(64/192 countries)
US$17.6M
(138/192 countries)
 UN votes (average % agreement 2011–2022)77.60%75.20%76.50%74.40%
 Military supplies (% of arms imports by Russia 2011–2022)§56.90%9.50%12.00%8.20%
 Media presence/cooperationLowLowSomeLow
China
 Exports to China in 2021*US$20.4B
(1/149 countries)
US$148M
(7/165 countries)
US$20.6B
(1/211 countries)
US$2.26B
(2/139 countries)
 Imports from China in 2021*US$2.28B
(97/209 countries)
US$2.8B
(85/209 countries)
US$20.5B
(34/209 countries)
US$951M
(125/209 countries)
 UN Votes (average % agreement 2011–2022)95.70%94.90%93.80%95.60%
 Military supplies (% of arms imports by China 2011–2022)§8.50%16.20%50.90%
 Media presence and cooperationLowSomeHighHigh

Measures

To measure the dependent variables in this study, the adoption of strategic disinformation narratives, we presented survey respondents with four statements, two of which included a favored narrative by the Russian government (“The war in Ukraine is a consequence of NATO’s expansion in Eastern Europe” and “Sanctions against Russia are the main cause for the current food and energy crises”), and two included a favored narrative by the Chinese government (“Foreign forces organized anti-government protests in Hong Kong in 2019” and “If a war break outs in Taiwan, it would be the United States’ fault”). We selected these narratives among those mentioned in reports prepared by Blankenship & Ordu (2022a; 2022b) and Kurlantzick (2020). We presented a longer list of narratives to a range of scholars with expertise in Russian/Chinese foreign policy and/or in the media environment of the four countries where the surveys were fielded. The four included in the study are those that were identified as most prevalent by the experts. For each statement, we asked respondents “To your knowledge, this statement is …?,” and offered four possible responses, “Definitely not true,” coded as (1) in the analysis, “Probably not true” (2), “Probably true”, (3) and “Definitely true” (4). We treat each narrative as a separate dependent variable in the study.

To measure media consumption, we adopt a framework that considers both the type of media being used (e.g., traditional, or social media) and the news sources within a given country (e.g., CNN as a US-based news source or RT as a Russian one). More specifically, we first created two measures, social media use and traditional media use, based on responses to the question “Have you got news from any of these types of media in the last 7 days? You can select multiple options,” which included options for both traditional (TV, newspaper, and radio) and social media (Facebook, WhatsApp, YouTube, Twitter, and TikTok) use. Each measure ranged from 0 to 1. Then, we computed separate measures (also ranging from 0 to 1) for exposure to US news sources, exposure to Chinese news sources and exposure to Russian news sources from the question “Have you got news from any of these sources in the last 7 days? You can select multiple options.” In this case, we provided a list of 10 news organizations: two from the US (VOA and CNN), two Russian (Sputnik and RT) and two Chinese (China Daily and CGTN), and four other decoys, that were not used in the analysis, namely two local (the national broadcaster of each country and a website), and two global sources (Al Jazeera and BBC). Next, we multiplied the frequency of engagement with specific sources and the frequency of using both traditional and social media platforms, to compute 6 separate measures of news consumption and exposure. Table 2 summarizes basic descriptive statistics (M and SD) for each of them.

Table 2.

Descriptive Statistics of Independent and Control Variables

AngolaEthiopiaSouth
Africa
Zambia
M (SD)M (SD)M (SD)M (SD)
Media consumption and exposure
 Exposure to U.S. sources × news consumption on social media.29 (.43).28 (.44).32 (.42).28 (.45)
 Exposure to U.S. sources × news consumption on traditional media.29 (.46).23 (.39).38 (.47).32 (.53)
 Exposure to Chinese sources × news consumption on social media.04 (.19).08 (.24).08 (.31).06 (.24)
 Exposure to Chinese sources × news consumption on traditional media.04 (.19).07 (.22).08 (.33).07 (.28)
 Exposure to Russian sources × news consumption on social media.04 (0.17).02 (.12).05 (.25).01 (.09)
 Exposure to Russian sources × news consumption on traditional media.04 (.18).02 (.11).05 (.26).01 (.11)
Worldviews
 Geopolitical views of the US.88 (.25).84 (.25).75 (.34).84 (.28)
 Geopolitical views of China.76 (.33).83 (.26).52 (.4).57 (.37)
 Geopolitical views of Russia.90 (.23).51 (.37).73 (.35).85 (.27)
Control variables
 Trust in news2.71 (.77)2.9 (.63)3.09 (.92)3.02 (.71)
 Interest in politics2.32 (1.10)2.44 (.98)3.04 (1.16)2.72 (1.07)
 Risk of foreign influence2.79 (1.10)2.55 (.90)2.96 (.98)2.91 (1.02)
N9981,2031,2031,209
AngolaEthiopiaSouth
Africa
Zambia
M (SD)M (SD)M (SD)M (SD)
Media consumption and exposure
 Exposure to U.S. sources × news consumption on social media.29 (.43).28 (.44).32 (.42).28 (.45)
 Exposure to U.S. sources × news consumption on traditional media.29 (.46).23 (.39).38 (.47).32 (.53)
 Exposure to Chinese sources × news consumption on social media.04 (.19).08 (.24).08 (.31).06 (.24)
 Exposure to Chinese sources × news consumption on traditional media.04 (.19).07 (.22).08 (.33).07 (.28)
 Exposure to Russian sources × news consumption on social media.04 (0.17).02 (.12).05 (.25).01 (.09)
 Exposure to Russian sources × news consumption on traditional media.04 (.18).02 (.11).05 (.26).01 (.11)
Worldviews
 Geopolitical views of the US.88 (.25).84 (.25).75 (.34).84 (.28)
 Geopolitical views of China.76 (.33).83 (.26).52 (.4).57 (.37)
 Geopolitical views of Russia.90 (.23).51 (.37).73 (.35).85 (.27)
Control variables
 Trust in news2.71 (.77)2.9 (.63)3.09 (.92)3.02 (.71)
 Interest in politics2.32 (1.10)2.44 (.98)3.04 (1.16)2.72 (1.07)
 Risk of foreign influence2.79 (1.10)2.55 (.90)2.96 (.98)2.91 (1.02)
N9981,2031,2031,209
Table 2.

Descriptive Statistics of Independent and Control Variables

AngolaEthiopiaSouth
Africa
Zambia
M (SD)M (SD)M (SD)M (SD)
Media consumption and exposure
 Exposure to U.S. sources × news consumption on social media.29 (.43).28 (.44).32 (.42).28 (.45)
 Exposure to U.S. sources × news consumption on traditional media.29 (.46).23 (.39).38 (.47).32 (.53)
 Exposure to Chinese sources × news consumption on social media.04 (.19).08 (.24).08 (.31).06 (.24)
 Exposure to Chinese sources × news consumption on traditional media.04 (.19).07 (.22).08 (.33).07 (.28)
 Exposure to Russian sources × news consumption on social media.04 (0.17).02 (.12).05 (.25).01 (.09)
 Exposure to Russian sources × news consumption on traditional media.04 (.18).02 (.11).05 (.26).01 (.11)
Worldviews
 Geopolitical views of the US.88 (.25).84 (.25).75 (.34).84 (.28)
 Geopolitical views of China.76 (.33).83 (.26).52 (.4).57 (.37)
 Geopolitical views of Russia.90 (.23).51 (.37).73 (.35).85 (.27)
Control variables
 Trust in news2.71 (.77)2.9 (.63)3.09 (.92)3.02 (.71)
 Interest in politics2.32 (1.10)2.44 (.98)3.04 (1.16)2.72 (1.07)
 Risk of foreign influence2.79 (1.10)2.55 (.90)2.96 (.98)2.91 (1.02)
N9981,2031,2031,209
AngolaEthiopiaSouth
Africa
Zambia
M (SD)M (SD)M (SD)M (SD)
Media consumption and exposure
 Exposure to U.S. sources × news consumption on social media.29 (.43).28 (.44).32 (.42).28 (.45)
 Exposure to U.S. sources × news consumption on traditional media.29 (.46).23 (.39).38 (.47).32 (.53)
 Exposure to Chinese sources × news consumption on social media.04 (.19).08 (.24).08 (.31).06 (.24)
 Exposure to Chinese sources × news consumption on traditional media.04 (.19).07 (.22).08 (.33).07 (.28)
 Exposure to Russian sources × news consumption on social media.04 (0.17).02 (.12).05 (.25).01 (.09)
 Exposure to Russian sources × news consumption on traditional media.04 (.18).02 (.11).05 (.26).01 (.11)
Worldviews
 Geopolitical views of the US.88 (.25).84 (.25).75 (.34).84 (.28)
 Geopolitical views of China.76 (.33).83 (.26).52 (.4).57 (.37)
 Geopolitical views of Russia.90 (.23).51 (.37).73 (.35).85 (.27)
Control variables
 Trust in news2.71 (.77)2.9 (.63)3.09 (.92)3.02 (.71)
 Interest in politics2.32 (1.10)2.44 (.98)3.04 (1.16)2.72 (1.07)
 Risk of foreign influence2.79 (1.10)2.55 (.90)2.96 (.98)2.91 (1.02)
N9981,2031,2031,209

To measure individuals’ worldviews, we focused on two aspects. First, we measured evaluations of the influence that China, Russia, and the US have on each respondents’ country (“Do you think that the economic and political influence of X in your country is …?”). We borrowed the wording of this question from Afrobarometer (2023). Four possible responses were provided (“Very negative” = 0, “Somewhat negative” = 1, “Somewhat positive” = 2 and “Very positive” = 3). For each of the three countries, we recorded responses to range from 0 (=negative) to 1 (=positive). Second, we looked at perceptions of China, Russia, and the US as “a partner”, “a competitor” or “an enemy”, following the language suggested by Gagliardone, Stremlau, & Nkrumah (2012). Answers to this question were recorded as three binary variables (1 = a partner, 0 = not a partner), one for the US, one for China, and one for Russia. Finally, we averaged the two measures for each country and generated three composite variables (geopolitical views of the US, China, and Russia), that we use in the analyses below.

The survey instrument also included two additional control variables, trust in news and interest in politics, that have been suggested as relevant in previous literature on political disinformation (Ahmed et al., 2022), as well as one variable proposed for this study, perceived risk of foreign influence. To measure trust in news and interest in politics we used a five-item scale (from “not at all” = 0 to “extremely” = 4) to the questions “How much do you trust the media?” and “How interested are you in politics?.” We only include a measure of the perceived risk of foreign influence because of the context in which the survey was fielded, where influence operations during recent electoral processes were prominent in domestic news media. To this end, we asked “In your view, how much risk is there that foreign countries might use social media to influence the elections in your country?” with four possible answers, from “No risk at all” (= 0) to “A very big risk” (= 3).

Findings

To test H1, which focuses on country-level differences and in which we hypothesize that South Africa, due to its membership in BRICS, will exhibit higher levels of support for Chinese and Russian strategic disinformation narratives than the other three countries, we make use of an ANCOVA test, with age, gender, education level, and country as covariates. Table 3 offers a summary of the estimated means. We find statistically significant differences between countries for all four narratives (Hong Kong narrative: F(3, 4604) = 7.92, p < .001; Taiwan narrative: F(3, 4561) = 41.75, p < .001; NATO narrative: F(3, 4605) = 4.86, p = .002; food crisis narrative: F(3, 4603) = 7.06, p < .001). Pairwise comparisons between the means of each country confirm, as predicted, that for the two strategic narratives favored by China, South Africa has statistically significantly higher means than Angola and Zambia. However, there is no difference with Ethiopia in the Hong Kong strategic narrative, and, when it comes to the Taiwan narrative, Ethiopia stands out with an estimated mean of 2.68 (SD = .25), compared to 2.47 (SD = .25) for South Africa. The difference is statistically significant. Further supporting H1, in the case of Russia-favored narratives we find the strongest support for the statement, “Sanctions against Russia are the main cause for the current food and energy crises” among South African respondents (M = 3.07; SD = .25). All pairwise comparisons with the other three countries are statistically significant. However, when it comes to the other statement, “The war in Ukraine is a consequence of NATO’s expansion in Eastern Europe,” our hypothesis is not supported, as South Africa has a lower mean than both Angola and Zambia. The differences between countries, however, are not statistically significant.

Table 3.

ANCOVA Estimates for Support of Strategic Disinformation Narratives by Country

AngolaEthiopiaSouth AfricaZambia
M
(SD)
M
(SD)
M
(SD)
M
(SD)
Foreign forces organized anti-government protests in Hong Kong in 20192.40 (.24)2.51 (.22)2.53 (.22)2.43 (.21)
If a war break outs in Taiwan, it would be the United States’ fault2.34 (.27)2.68 (.25)2.47 (.25)2.32 (.24)
The war in Ukraine is a consequence of NATO’s expansion in Eastern Europe.2.90 (.29)2.76 (.26)2.80 (.26)2.85 (.25)
Sanctions against Russia are the main cause of the current food and energy crises2.90 (.28)2.91 (.26)3.07 (.25)2.91 (.25)
N9981,2031,2031,209
AngolaEthiopiaSouth AfricaZambia
M
(SD)
M
(SD)
M
(SD)
M
(SD)
Foreign forces organized anti-government protests in Hong Kong in 20192.40 (.24)2.51 (.22)2.53 (.22)2.43 (.21)
If a war break outs in Taiwan, it would be the United States’ fault2.34 (.27)2.68 (.25)2.47 (.25)2.32 (.24)
The war in Ukraine is a consequence of NATO’s expansion in Eastern Europe.2.90 (.29)2.76 (.26)2.80 (.26)2.85 (.25)
Sanctions against Russia are the main cause of the current food and energy crises2.90 (.28)2.91 (.26)3.07 (.25)2.91 (.25)
N9981,2031,2031,209
Table 3.

ANCOVA Estimates for Support of Strategic Disinformation Narratives by Country

AngolaEthiopiaSouth AfricaZambia
M
(SD)
M
(SD)
M
(SD)
M
(SD)
Foreign forces organized anti-government protests in Hong Kong in 20192.40 (.24)2.51 (.22)2.53 (.22)2.43 (.21)
If a war break outs in Taiwan, it would be the United States’ fault2.34 (.27)2.68 (.25)2.47 (.25)2.32 (.24)
The war in Ukraine is a consequence of NATO’s expansion in Eastern Europe.2.90 (.29)2.76 (.26)2.80 (.26)2.85 (.25)
Sanctions against Russia are the main cause of the current food and energy crises2.90 (.28)2.91 (.26)3.07 (.25)2.91 (.25)
N9981,2031,2031,209
AngolaEthiopiaSouth AfricaZambia
M
(SD)
M
(SD)
M
(SD)
M
(SD)
Foreign forces organized anti-government protests in Hong Kong in 20192.40 (.24)2.51 (.22)2.53 (.22)2.43 (.21)
If a war break outs in Taiwan, it would be the United States’ fault2.34 (.27)2.68 (.25)2.47 (.25)2.32 (.24)
The war in Ukraine is a consequence of NATO’s expansion in Eastern Europe.2.90 (.29)2.76 (.26)2.80 (.26)2.85 (.25)
Sanctions against Russia are the main cause of the current food and energy crises2.90 (.28)2.91 (.26)3.07 (.25)2.91 (.25)
N9981,2031,2031,209

Next, we focus on H2 & H3ab, all of which explore individual-level predictors. To test these hypotheses, we fitted four Ordinary Least Squares (OLS) regression models, one for each narrative (see Table 4). We found no clear and consistent relationship between exposure to news content from China or Russia, either on social media or on traditional media, and the support of strategic disinformation narratives. Only in Model 3 (NATO narrative), we find a significant association between media consumption of US media and support for that Russia-favored strategic narrative. More specifically, we find that higher levels of exposure to US sources through social media, where discordant and fringe voices might be more prevalent, are associated with more support for the statement (ß = .16, SE = .05, p = .001). Conversely, higher levels of exposure to US sources through traditional media, where pro-establishment voices are more likely to be found, are associated with less support for the statement (ß = −.13, SE = .05, p = .005). Considering these results, we would reject H2. Despite efforts by multiple countries to influence public opinion through the news media, our data seems to suggest that exposure to such content does not have a significant impact on individuals’ support of strategic disinformation narratives favored by China and Russia.

Table 4.

OLS Regression Coefficients

Model 1
Hong Kong
Narrative
Model 2
Taiwan
narrative
Model 3
NATO to blame
narrative
Model 4
Food crisis
narrative
ßSEßSEßSEßSE
Media consumption and news exposure
 Social media consumption and U.S. media exposure.06.04−.01.050.16**.05.08.05
 Traditional media consumption and U.S. media exposure−.05.04−.02.05−.13**.05−.08.05
 Social media consumption and Chinese media exposure.17.10−.06.11
 Traditional media consumption and Chinese media exposure−.12.10.03.11
 Social media consumption and Russian media exposure.10.20.05.20
 Traditional media consumption and Russian media exposure.00.19.07.19
Worldviews
 Geopolitical views of the US−.14**.04−.65**.04−.32**.04−.14**.04
 Geopolitical views of China.16**.04.26**.04
 Geopolitical views of Russia.37**.04.05.04
Control variables
 Trust in the media.03.02−.01.02.03.02.07**.02
 Interest in politics.05**.01.06**.01.06**.01.05**.01
 Risk of foreign interference.06**.01.08**.01.08**.01.08**.01
Demographic variables
 Gender (Male = 1).00.02.12**.03.11**.03−.03.03
 Age−.01**.00.00.00−.01**.00−.01**.00
 Educational attainment−.02*.01.02.01.03**.01.00.01
 Country (Ethiopia = 1)−.08*.04.00.04.1**0.04−.08*.04
 Country (South Africa = 1).00.03.12**.04−.1**.04−0.1**.04
 Country (Zambia = 1)−.08*.03−.0**.03.1**.04−.1**.04
 Intercept2.36**.092.27**.092.25**.102.70**.10
   R2.32.12.08.03
Model 1
Hong Kong
Narrative
Model 2
Taiwan
narrative
Model 3
NATO to blame
narrative
Model 4
Food crisis
narrative
ßSEßSEßSEßSE
Media consumption and news exposure
 Social media consumption and U.S. media exposure.06.04−.01.050.16**.05.08.05
 Traditional media consumption and U.S. media exposure−.05.04−.02.05−.13**.05−.08.05
 Social media consumption and Chinese media exposure.17.10−.06.11
 Traditional media consumption and Chinese media exposure−.12.10.03.11
 Social media consumption and Russian media exposure.10.20.05.20
 Traditional media consumption and Russian media exposure.00.19.07.19
Worldviews
 Geopolitical views of the US−.14**.04−.65**.04−.32**.04−.14**.04
 Geopolitical views of China.16**.04.26**.04
 Geopolitical views of Russia.37**.04.05.04
Control variables
 Trust in the media.03.02−.01.02.03.02.07**.02
 Interest in politics.05**.01.06**.01.06**.01.05**.01
 Risk of foreign interference.06**.01.08**.01.08**.01.08**.01
Demographic variables
 Gender (Male = 1).00.02.12**.03.11**.03−.03.03
 Age−.01**.00.00.00−.01**.00−.01**.00
 Educational attainment−.02*.01.02.01.03**.01.00.01
 Country (Ethiopia = 1)−.08*.04.00.04.1**0.04−.08*.04
 Country (South Africa = 1).00.03.12**.04−.1**.04−0.1**.04
 Country (Zambia = 1)−.08*.03−.0**.03.1**.04−.1**.04
 Intercept2.36**.092.27**.092.25**.102.70**.10
   R2.32.12.08.03

**p < .01;

*p < .05.

Table 4.

OLS Regression Coefficients

Model 1
Hong Kong
Narrative
Model 2
Taiwan
narrative
Model 3
NATO to blame
narrative
Model 4
Food crisis
narrative
ßSEßSEßSEßSE
Media consumption and news exposure
 Social media consumption and U.S. media exposure.06.04−.01.050.16**.05.08.05
 Traditional media consumption and U.S. media exposure−.05.04−.02.05−.13**.05−.08.05
 Social media consumption and Chinese media exposure.17.10−.06.11
 Traditional media consumption and Chinese media exposure−.12.10.03.11
 Social media consumption and Russian media exposure.10.20.05.20
 Traditional media consumption and Russian media exposure.00.19.07.19
Worldviews
 Geopolitical views of the US−.14**.04−.65**.04−.32**.04−.14**.04
 Geopolitical views of China.16**.04.26**.04
 Geopolitical views of Russia.37**.04.05.04
Control variables
 Trust in the media.03.02−.01.02.03.02.07**.02
 Interest in politics.05**.01.06**.01.06**.01.05**.01
 Risk of foreign interference.06**.01.08**.01.08**.01.08**.01
Demographic variables
 Gender (Male = 1).00.02.12**.03.11**.03−.03.03
 Age−.01**.00.00.00−.01**.00−.01**.00
 Educational attainment−.02*.01.02.01.03**.01.00.01
 Country (Ethiopia = 1)−.08*.04.00.04.1**0.04−.08*.04
 Country (South Africa = 1).00.03.12**.04−.1**.04−0.1**.04
 Country (Zambia = 1)−.08*.03−.0**.03.1**.04−.1**.04
 Intercept2.36**.092.27**.092.25**.102.70**.10
   R2.32.12.08.03
Model 1
Hong Kong
Narrative
Model 2
Taiwan
narrative
Model 3
NATO to blame
narrative
Model 4
Food crisis
narrative
ßSEßSEßSEßSE
Media consumption and news exposure
 Social media consumption and U.S. media exposure.06.04−.01.050.16**.05.08.05
 Traditional media consumption and U.S. media exposure−.05.04−.02.05−.13**.05−.08.05
 Social media consumption and Chinese media exposure.17.10−.06.11
 Traditional media consumption and Chinese media exposure−.12.10.03.11
 Social media consumption and Russian media exposure.10.20.05.20
 Traditional media consumption and Russian media exposure.00.19.07.19
Worldviews
 Geopolitical views of the US−.14**.04−.65**.04−.32**.04−.14**.04
 Geopolitical views of China.16**.04.26**.04
 Geopolitical views of Russia.37**.04.05.04
Control variables
 Trust in the media.03.02−.01.02.03.02.07**.02
 Interest in politics.05**.01.06**.01.06**.01.05**.01
 Risk of foreign interference.06**.01.08**.01.08**.01.08**.01
Demographic variables
 Gender (Male = 1).00.02.12**.03.11**.03−.03.03
 Age−.01**.00.00.00−.01**.00−.01**.00
 Educational attainment−.02*.01.02.01.03**.01.00.01
 Country (Ethiopia = 1)−.08*.04.00.04.1**0.04−.08*.04
 Country (South Africa = 1).00.03.12**.04−.1**.04−0.1**.04
 Country (Zambia = 1)−.08*.03−.0**.03.1**.04−.1**.04
 Intercept2.36**.092.27**.092.25**.102.70**.10
   R2.32.12.08.03

**p < .01;

*p < .05.

We did find enough evidence to retain H3a and partially retain H3b. In all four models, as we hypothesized, perceiving the US as a positive geopolitical actor was negatively associated with supporting Chinese or Russian strategic narratives (Model 1: ß = −.14, SE = .04, p < .001; Model 2: ß = −.65, SE = .04, p < .001; Model 3: ß = −.32, SE = .04, p < .001; Model 4: ß = −.14, SE = .04, p = .001). Contrarywise, and in support of H3b, having positive geopolitical views of China was found to be positively associated with support for Chinese strategic narratives in both Models 1 (ß = .16, SE = .04, p < .001) and 2 (ß = .26, SE = .04, p < .001). In the case of Russia, we find the same pattern in Models 3 (ß = .37, SE = .04, p < .001) and 4 (ß = .05, SE = .04, p = .193), but only Model 3 returns a statistically significant coefficient. This rather consistent pattern in the relationship between worldviews and support for strategic disinformation narratives might be a product of domestic processes or might be explained by other forms of media consumption that are not captured by our model.

While we did not consider other factors when formulating our hypotheses, our analysis reveals some other significant relationships in the data. Both interest in politics (Model 1: ß = .05, SE = .01, p < .001; Model 2: ß = .06, SE = .01, p < .001; Model 3: ß = .06, SE = .01, p < .001; Model 4: ß = .05, SE = .01, p < .001) and perceived risk of foreign interference in elections (Model 1: ß = .06, SE = .01, p < .001; Model 2: ß = .08, SE = .01, p < .001; Model 3: ß = .08, SE = .01, p < .001; Model 4: ß = .08, SE = .01, p < .001) appear as significant predictors of higher support for all strategic disinformation narratives. We also find that men seem to be more inclined to adopt these narratives. Finally, after controlling for all other factors, a few differences between countries remain, in line with what our analysis of covariance suggested.

Discussion and Conclusion

In the context of growing competition by foreign powers, particularly China and Russia, to influence public opinion in Sub-Saharan Africa, this paper constitutes the first attempt at comparing the impact that these efforts are having across a range of very diverse countries. It is also the first study to examine how individual-level factors might contribute to the adoption of certain strategic disinformation narratives favored by Beijing and Moscow. Our analysis reveals that there are significant differences in the support for Chinese- and Russian-favored narratives in the four countries we studied. As expected, it was in South Africa, the only African country that is a member of BRICS, where we found the highest levels of support for most of the narratives we tested. We also find relatively high levels of prevalence of said narratives in Ethiopia, a country that has recently been invited to join the group as it plans to grow its membership (Nyabiage, 2023). At an individual level, we do not find evidence of a consistent significant effect of exposure to certain news content on the support for strategic disinformation narratives. While much of the literature on the geopolitics of disinformation in Sub-Saharan Africa has focused on the media presence of actors such as China and Russia, our data suggest that consumption of that type of content is low and, possibly, not a vehicle for direct influence over public opinion. This finding supports previous research (e.g., Repnikova, 2020; Madrid-Morales & Wasserman, 2022) which has also shown limited uptake and influence of Chinese media in African media spaces. That said, the lack of longitudinal data and the self-reported nature of some of the media consumption variables weakens our assessment regarding the impact of willing or incidental exposure to Russian or Chinese news content.

This study has other limitations. Primarily, having collected data through a series of online surveys means that our findings can only speak of a small subset of the population. Because our sample skews young, urban, and highly educated, the findings presented in this paper should be read as describing online populations. While this means that we cannot speak of the general population, studying online publics is still of relevance in this case, as they are also often the target publics of many of the influence operations by foreign actors that this paper describes. After all, as research has shown (Grossman et al., 2019; Graphika & Stanford Internet Observatory, 2022), a range of foreign State and non-State actors are using predominantly online spaces to disseminate their favored strategic narratives. In addition to the limitations derived from our sampling procedure, our findings are also constrained by the fact that, in two of the countries we studied (Angola and Ethiopia), neither Chinese nor Russian media are producing content in local languages. This does mean that publics are much less likely to consume content from those sources. Were other researchers willing to explore further the findings presented in this paper in follow-up studies, it might be worth engaging with different research approaches, such as qualitative interviews involving a social media walk through, go-along, or scroll-back, that could provide more fine-grained details on how (and whether or not) publics in non-English speaking countries come across Chinese and Russian targeted messaging.

The most consistent relationship that our analysis reveals is between different worldviews and support of Chinese- and Russian-favored strategic disinformation narratives. We find that those respondents who see China/Russia as allies and perceive them as having a positive impact on their countries tend to be supportive of their strategic narratives. This also applies to those who have negative views of the US: anti-US sentiment is also a strong predictor of support for Chinese and Russian narratives. One way to interpret this would be in connection to Huntington’s (1999) argument that the US is the last and only global superpower whose interests often conflict with those of other major regional powers. However, the US can no longer force its will upon other countries and requires the legitimation of international bodies or the cooperation of other powers to achieve its aims. On several global political issues such as conflict in the Middle East or the global climate crisis, the US often finds itself alone, with a few partners or allies, and against most of the world. As Adhikari (2019, p. 1528) shows, such disagreement with US policies is often reflected in the voting record in the UN General Assembly and is consequently penalized when foreign aid is allocated. Given such resistance against its politics, Huntington (1999, p. 36) calls the US a “lonely superpower” or a “rogue superpower” in that it has “preeminence in every domain of power—economic, military, diplomatic, ideological, technological, and cultural—with the reach and capabilities to promote its interests in virtually every part of the world” to a greater extent than any other major regional powers can do. At the same, Huntington (1999, p. 42) further argues, that it is viewed by people in many countries around the world as “intrusive, interventionist, exploitative, unilateralist, hegemonic, hypocritical, and applying double standards, engaging in what they label “financial imperialism” and “intellectual colonialism,” with a foreign policy driven overwhelmingly by domestic politics”. This foreign policy results in “widespread feelings of fear, resentment or envy” (Huntington, 1999, p. 44) among citizens of countries around the world. These views may also underpin the attitudes we found among respondents in our study.

More broadly, our findings hint at the importance that longer social and political histories have in molding domestic attitudes, particularly when it comes to the influence of strategic disinformation narratives and irrespective of the content of, or the actor behind the message itself. At the very least, the impact of foreign disinformation in African societies should be considered as a confluence between global information flows and domestic attitudes shaped by history and place. Implicit in this finding is the assumption that counter-disinformation efforts in the region should go beyond merely debunking disinformation or providing journalistic counter narratives. The findings of this paper support the notion that African media are simultaneously characterized by global, geopolitical shifts and domestic, local contestations. The data presented here show that foreign influence in African-mediated public spheres contends with contextual factors that prevent simplistic readings of how disinformation impacts African publics. Our findings are a reminder that, as is the case with other media “effects”, disinformation is filtered through social attitudes, historical legacies, and political discourses. In this sense, our findings “illustrate the complex interrelationship between global geopolitical influence and domestic attitudes, and how information flows and shifts always occur on several levels at once, and ( … ) continue to evolve across time and borders, in ways that only a holistic approach can hope to do justice to” (Wasserman, 2018, p. 171).

As more and more foreign countries engage in activities aimed at influencing public opinion in Africa, State actors that have dominated the space, particularly former colonial powers, are showing interest in developing strategies to counter the presence of new (and-not-so-new) State and non-State actors, from Russia and China to Turkey, Iran, and others. The European Union has a dedicated team within the External Action Service to fight disinformation within the bloc and beyond, particularly from Russia, with a budget of over 11 million euro (EEAS, 2021). There are also similar initiatives to combat foreign disinformation in the world within different member states (Fitzpatrick, 2021; Suliman, 2022). The United States has appointed a Special Envoy and Coordinator to its Global Engagement Center within the Department of State with the mission to “direct, lead, synchronize, integrate, and coordinate U.S. Federal Government efforts to recognize, understand, expose, and counter foreign state and non-State propaganda and disinformation efforts” (GEC, 2023). The work of these entities has largely focused on “naming and shaming” rogue actors and on shining light on the increased range of activities aimed at influencing public opinion overseas (STRAT.2, 2023). Much less attention has gone into understanding the historical context in which current expressions of disinformation are occurring. The data presented in this paper show that anti-US, anti-imperialist and, possibly anti-West messaging, resonates with a significant number of Angolans, Ethiopians, South Africans, and Zambians. Their support for some of the narratives presented to them in this paper might not stem from the success of influence operations, but instead be a response to decades of US, French and British interventionism in Africa, and beyond. This would call, not for the pointing of fingers towards the actions of other actors, but a reflection on those conducted by the US and other countries in the past, and present.

Biographical Notes

Dani Madrid-Morales (PhD, City University of Hong Kong) is a Lecturer in Journalism at the University of Sheffield, United Kingdom. His research focuses on global political communication, with a strong focus on State-sponsored news channels, global information flows, and disinformation in East and Southern Africa. He has published extensively on these topics in journals such as International Journal of Communication, Journalism Studies, and Digital Journalism.

Herman Wasserman is Professor of Journalism and Chair of the Department of Journalism at Stellenbosch University, South Africa. He has published widely on media in Africa. His books include Tabloid Journalism in South Africa, Media, Geopolitics and Power and Media, Conflict and Democracy in Africa. His latest book is Disinformation in the Global South (co-edited with Dani Madrid-Morales), published in 2022.

Saifuddin Ahmed (PhD, University of California-Davis) is an Assistant Professor in the Wee Kim Wee School of Communication and Information at Nanyang Technological University, Singapore. His research interests lie in new and emerging media, political communication, election studies, and public opinion. He is particularly interested in the transformative role of new media in civic and political engagement in technologically emerging societies.

Funding

This work was supported by internal research funding from the University of Cape Town, South Africa.

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