An Analysis of RT’s Economic Content and Context on Facebook Citation: Authors. Title. Pages…. DOI:000000/11111. (2024)

1 Introduction

Increased gas prices, interrupted supply chains, rising inflation rates, shifting currency values, volatile cryptocurrencies, and bank failures have rendered the impacts of a globalized economy personal. Economic fluctuations have also produced societal ramifications such as support for populism [1, 2, 3], selected policy alternatives [4, 5, 6], and electoral outcomes [7, 8, 9, 10].

Perhaps as a result, economic content now forms an integral part of public diplomacy efforts. Economic messaging plays a key role in attracting the attention of global audiences [11]. It also influences public attitudes on national issues, such as the war effort in Crimea [12]. Previous examinations of Russian advertorials distributed in the United States and India [13], as well as posts by a German Ambassador using social media to reach Pakistani audiences [14], document the high frequency of economic messaging in public diplomacy. Previous analyses of communications between members of the BRIC alliance go so far as to highlight economic aims as the chief objective of their public diplomacy efforts [15]. The priority positioning of economics in public diplomacy prompts some scholars to even incorporate the concept into their definitions. Milam and Avery, for example, maintain that public diplomacy is the “direct or indirect engagement of foreign publics in support of national security, political, cultural, and economic objectives” [16, p.329].

Some countries facing economic challenges such as declining currency values and increasing public debt have invested heavily in media platforms to expand their global influence. Russia’s RT serves as an illustration, as the media outreach platform functions as a chief component of Russia’s mediated public diplomacy strategy [17, 18]. After spending hundreds of millions of dollars to staff more than 20 international bureaus [19, 20], RT channels, websites, and social media platforms have attracted billions of views from citizens in more than 100 countries [21, 22].

This study examines five years of RT Facebook’s non-Russian language accounts to expand understandings of the economic dimensions of public diplomacy. It explores which topics are most prevalent in the posts on RT accounts and assesses how previously unexplored economic context variables interface with RT’s economic messaging strategies. To explain, we begin by recounting how the rise of social media has transformed public diplomacy. We then demonstrate how our study expands upon previous work related to RT’s economic messaging strategies and messaging contexts. We conclude by describing and discussing our study’s approach, results, and directions for future research.

2 Social Media and Public Diplomacy

Public diplomacy’s chief goal of engaging with foreign audiences to influence international environments has not changed over time [23], but the rise of social media has transformed its practice [24]. Certain social media platforms now capitalize on the viewership declines of standard news platforms (e.g., radio and television) by positioning themselves as both sources of news and as venues for socialization [25]. Whether followers actively seek out social media newsfeeds or not, online audiences have incidental exposure to such newsfeeds [26]. Users also rely on established social media sites like Facebook, Twitter, and YouTube even when their primary news sources are alternative social media platforms like Truth Social, Gettr, Gab, and Bitchute [27]. Consequently, most governments now capitalize on the cost-effectiveness and accessibility of social media to post much of their public diplomacy content [28]. The approach expands followers by delivering information around the globe. It also allows members of the diplomatic corps and their staff to gather data regarding the audience engagement levels with certain types of messaging content in ways that are useful for maximizing the value of public diplomacy efforts [29].

By expanding the number and range of reachable followers, public diplomacy via social media proliferates opportunities for audience targeting and engagement [30]. Multiple language accounts associated with online platforms such as RT, CGTN, and Voice of America position nation-states to deliver selected content to citizens of states efficiently, even those ruled by authoritarian regimes [31]. They also permit outreach to groups that cross state boundaries that share language fluencies. RT, for example, has 35 different subscriber groups that diverge based on their nationalities, languages, and interests [32].

The affordances of particular social media platforms offer certain constraints and opportunities for public diplomacy. Each social media platform has unique characteristics that prompt new “logics of social practices” for their own networked publics [33, p.220]. More specifically, the affordances of each platform prompt and often govern what constitutes appropriate discourse and the nature of audience interactions [34, 35]. Affordances also contribute to “sociability, sharing, interaction, hom*ophily, social capital and power, and network effects” [36, p.9]. Consumers and producers of content, as a result, comply with certain communication rules and norms simply by selecting to view a particular social media platform or risk alienating their followers on such platforms.

Considered as a whole, the use of social media for public diplomacy purposes has produced mixed results. Some studies highlight the limited value of public diplomacy efforts on social media due to the followers’ lack of trust in the platform’s content [37] or in the country that is posting the content [38]. Others, however, document that exposure to such forums produces success in undermining popular support for the existing world order [39], changing perceptions of the US and its allies [21, 40], and heightening frictions amongst global alliances [41]. Simply put, public diplomacy efforts delivered via social media have the capacity within certain contexts to project soft power in ways to maximize the chances of accomplishing their objectives through dialogic interactions with foreign publics [42, 14, 43].

Beyond transforming an audience’s makeup and potential reactions, social media also transforms the expectations of messaging content of public diplomacy efforts. Followers of social media platforms demand that public diplomacy posts be more open, transparent, real-time, and engaging [42, 14]. Further, social media’s capacity to reinforce and amplify messages through repetition increases the number of followers [31], primes audiences to expect certain types of content [44], fosters emotional responses and persuasive outcomes in followers [45, 46], polarizes audiences [47], spreads misinformation (Kragh and Åsberg 2017), and reinforces ideologically based networks [48].

2.1 Russian Public Diplomacy and the Economy

While social media has recently changed public diplomacy practices, the influential role of economic messaging broadly considered has long been understood. Since Dierdre McCloskey’s [49] germinal foray linking communication and economic studies, research has documented intersections between economic communications and various ideological perspectives, including capitalism [50, 51], neoliberalism [52, 53], and socialism [54, 49]. Economic messaging also has indirect media effects by attracting support for specific economic policies [54, 4, 55, 56], influencing perceptions of presidential leadership [7, 57, 58], functioning as a needed response to economic crises [5, 59, 60, 61], serving as a persuasive presidential strategy [62, 63], and functioning to build and challenge communities at both the national and global levels [50, 54, 64].

Growing recognition and acceptance of the societal impacts of economic messaging has prompted efforts to better understand Russia’s economic public diplomacy efforts. Previous studies, however, are limited in their consideration of platforms that serve as delivery mechanisms for such content. Past research projects on Russia’s economic content have focused on the use of newspapers (e.g., [13, 65]), television (e.g., [66]), and Twitter (e.g., [14]). This study expands understanding of Russia’s platform-specific messaging strategies by focusing on RT’s use of Facebook. With two billion daily active users [67] and affordances of anonymity and network amplification, Facebook offers Russia access to a wide global audience with potential susceptibility to its RT messaging campaign. Thus, a fulsome accounting of Russia’s economic approach would not be complete without consideration of the Facebook platform, as it is the largest social media application in the contemporary global media environment.

Previous studies regarding Russia’s use of economic messaging in public diplomacy, while useful, are also limited in their examinations of narrow timespans and subject matter, as well as in their dated findings. By way of illustration, existing economically-related studies examine two months of RT programming following the fifth BRICs summit in 2013 [66], one year of advertorial content in Indian and US newspapers during 2011 [13], communication efforts by the Russian and Polish governments in the immediate aftermath of a 2010 airplane crash that killed Polish President Lech Kaczynski and most of his Cabinet [65], international news coverage of four superpower summit meetings held between the US and Russia from 1987 to 1990 [68], and selected posts of Russian Minister of Foreign Affairs spokesperson Maria Zakharova in recent years [69]. By examining the last five years of RT’s Facebook posts, this study updates these earlier studies and assesses the most frequently recurring and reinforced economic content topics by RT over time. Our study’s expanded time frame also permits a more nuanced examination of economically related context factors that consistently correspond to changes in the output levels of RT’s economic content of the platform’s preferred topics.

A third area of concern regarding previous studies of Russia’s use of economic messaging relates to considerations of the audience’s scope. While one study of China’s use of economic messaging encompasses more than 30 embassies’ public diplomacy [31], we found no comparable, large-scale study of Russia’s global economic efforts. Instead, the rare earlier work on the relationship between economic context variables and messaging content focuses on bilateral public diplomacy efforts, such as between two countries like Poland and Russia [65]. By examining all outward-facing languages of RT accounts apart from Serbian (which was not available until after the beginning of our study’s timespan), this study compares the use of representative economic topics across content RT conveys in English, French, German, Arabic, and Spanish. Examinations of the various accounts offer an opportunity to see if and how RT’s economic messaging differs towards language-based communities.

To help fill these gaps regarding Russia’s public diplomacy efforts, we will provide a long-term perspective of the language-targeting approaches of Russia on the largest social media app. To accomplish this task, we ask:

RQ1: How have RT’s official Facebook posts on its various language- specific accounts utilized economic messaging?

Several studies examining the role of economic contexts establish a correspondence between environmental indicators and information campaigns [70, 71, 72, 73, 74]. Yet, previous examinations of economic content of Russian public diplomacy efforts are rare [56]. One study, for example, describes the formation of the BRIC economic alliances as a key factor in contemporary global power struggles (Li and Marsh 2016). Another, examining Chinese embassies in both Russia and 29 other countries, concludes that the number of the embassy’s social media followers does not always correlate with the country’s economic size or level of bilateral economic relations [31]. A third finds that trade balances between Russia and Poland correspond to higher levels of attention to global media posts, regardless of the involved regime or culture [65]. This study adds to previous theories of economic public diplomacy and context variables by analyzing two previously unexplored variables —the role of currency rates and oil prices —as potential context factors that might correlate with levels of economic messaging. Identifying impactful context factors can better provide national governments and social media users alike with the ability to more accurately anticipate when and how governments use economic messaging in public diplomacy efforts.

More specifically, the need to analyze currency values in the context of public diplomacy stems from their growing interconnectedness in a globalized world. Multiple factors affect a nation’s currency values including inflation, political stability levels, macroeconomic indicators (e.g., interest rates, public debt levels, central bank intervention, etc.), and appreciation or depreciation of powerful global currencies (such as the US Dollar, Euro, British Pound, and Kuwaiti Dinar). In 1995, for example, the Mexican government switched the Peso from a fixed to a floating rate, triggering a massive drop in its value [75, 76, 77]. The 2016 Brexit referendum led to the exit of the United Kingdom from the European Union in 2019, causing a significant depreciation not only in the British Pound but also in the US, Australian, and Canadian Dollars [78]. In a 2024 interview between Tucker Carlson and Vladimir Putin, President of Russia, Putin surmised the key role of the currencies in global economics: “To use the dollar as a tool of foreign policy struggle is one of the biggest strategic mistakes made by the US political leadership. The dollar is the cornerstone of the United States power. I think everyone understands very well that no matter how many dollars are printed, they’re quickly dispersed all over the world” [79, loc01:17:47]. Further, the fact that currency rates can and do change quickly makes them optimal for discerning any corresponding relationships between swift changes in state-sponsored media messaging and situational factors. Thus, we ask:

RQ2: How have economic post levels across RT’s language-specific accounts corresponded to changes in currency values over time?

The need to examine oil prices as a possible influential economic context factor emerges from the variable’s function as a critical component of global energy policies since the mid-1970s. The prominent placement of oil prices in global priorities has emerged from correlations between oil prices and levels of global peace and conflict, the role of state and international organizations in managing supply and demand, the diverse interests of various actors in energy policy ranging from governments to businesses and environmental groups, and shifts in global demand and supply structures such as the increasing demand from countries like Russia and China [80]. Further, oil-producing countries’ domestic policies also influence global oil prices and impact certain oil cartels [81, 82]. Russia’s Ural Oil, for example, references its own oil prices separate from the other three bigger consortium’s of Brent Oil, OPEC, and West Texas Intermediate. To ascertain if and how oil prices correlate with Russia’s economic public diplomacy efforts, we ask:

RQ3: How have economic post levels across RT’s language-specific accounts corresponded to changes in oil prices over time?

2.1.1 Methodology

We collected 513,836 Facebook posts across RT’s non-Russian language- and country-specific pages using CrowdTangle (a META search program) during the 5 years between 2018-09-01 and 2023-09-01. The pages were RT Main (in English), RT France, RT en Español, RT UK, RT Arabic, RT America, and RT DE. Our extracted data included the full text of posts in their original languages, and the dates of the posts. To narrow the corpus to economic content, our coauthors who are native speakers of RT’s language accounts, created a search word list through a compilation of economic literacy words relating to finance and macro/micro-economics in English, French, German, Spanish, and Arabic (for a total of 320 words) (see Tables S1 and S2). The final corpus for analysis comprised 38,186 posts with economic content.

Figure 1 illustrates our research design. All data analyses used R (version 4.3.0 in R Studio Version 2023.03.0) and Python (3.9.16 in Visual Studio Code Version: 1.77.0). This study’s code appears in Open-Source Framework and GitHub.

We used transform-based topic modeling (BERTopic) [83] with multilingual embeddings (paraphrase-multilingual-MiniLM-L12-v2) [84] to reveal the topical structure of the corpus. We hyper-tuned the parameters to include at least five percent of the documents related to each topic. The generative nature of BERTopic provides one topic label for each document, and an outlier topic of -1 for documents so diffuse in their content that they defy a clear focus. We used OpenAI validated by one native speaker to relabel the topic names using documents (RT posts) with the highest probabilities. Our qualitative analysis assessed the content of topics for each unique page.

See Also

Transcript of Trump Manhattan Trial, April 26, 2024Helix Energy Solutions Group, Inc. (NYSE:HLX) Q1 2024 Earnings Call Transcript

To assess what, if any, financial changes corresponded to changes in total RT Facebook economic posts, we identified the monthly (1) sum of RT posts per page and per topic, (2) mean of Ural Oil prices, and (3) mean of USD value against the Ruble’s value. The inverse representative currency exchange rates display a USD per currency unit to reveal the power of the RUB against the USD [85]. Thus, an inverse representative rate of 1.5 RUB to USD means 1 RUB will buy 1.5 USD, meaning that a decrease in the representative rate means the currency is becoming weaker. In contrast, an increase in the representative rate means the currency is becoming stronger in the global exchange market.

Since the study’s timespan was 2018 to 2023, we assessed whether our findings remained constant in relation to two dominant external events as exogenous variables. The first was when the WHO declared the coronavirus pandemic on March 11th, 2021 [86], and the second corresponded to when Russia began military operations against Ukraine on February 24th, 2022 [87]. Table1 summarizes the definitions of the independent and dependent variables.

Variable Name	Definition
Dependent Variables (x)
Inverse Russian Ruble Representative Rate	1/ Russian Ruble “Representative exchange rates, which are reported to the Fund by the issuing central bank, are expressed in terms of currency units per US dollar, except for those indicated by (1) which are in terms of US dollars per currency unit” (The International Monetary Fund (IMF), 2023).
Urals Oil monthly averages	Ural oil monthly prices acquired from OPEC (OPEC, 2023)
Independent Variable (y)
BERTopic per month per page	The 6 BERTopics per page monthly post values
Exogenous Variables
Interruption 1 – COVID-19 Pandemic	All weeks prior to March 11th, 2021 marked as 0, including March 11th, 2021 and post marked as 1
Interruption 2 – Russia & Ukraine Military Conflict	All weeks prior to February 24th, 2022 marked as 0, including February 24th, 2022 and post marked as 1

For our statistical analysis, we used Vector Autoregressive Models (VAR) (see Figure 2). We selected this model for three primary reasons: 1) to capture the dynamic interdependencies between variables, 2) to include endogenous and exogenous variables, and 3) to identify causal relationships between variables [88, 89, 90]. For a summary of our Vector Autoregressive Analysis, see Figure 2.

To analyze the robustness of our VAR analysis, we tested our data using Augmented Dickey–Fuller (ADF) t-statistic test for unit root to test a rejection criterion of p=0.05 (Tables S3 and S15). We visually corroborated the results with Autocorrelation Function (ACF) (Figures S3 to S46). We then selected appropriate lags with Bayesian Information Criterion (BIC) or Schwarz Criterion (SC) testing lags from one to six (Tables S4 and S16) [88, 89, 90]. Further, to demonstrate how a dependent variable responded to the independent variable and to understand any relationship’s effect size without noise, we graphed the results using the Impulse Response Function (IRF) [88, 89, 91, 92]. To document that the residual of all times series were random, we utilized post-hoc tests of Johansen test for co-integration with a rejection criteria of p = 0.05 (Tables S13 and S25) [93, 91] and Ljung-Box tests for co-integration (Tables S14 and S26) [94, 89]. To interpret the results of the VAR analysis, we ran Granger Causality tests [89, 90].

3 Results

3.1 RQ1: Economic Content in RT Posts

Seven percent of overall RT’s Facebook posts focused on economic topics (figure 3). Six overarching economic topics characterized the posts in RT’s multilingual corpus. Recent News Headlines was the leading topic, followed by US-Russia-Ukraine Sanctions and Covid Pandemic and Related Issues. See Table2 for topic labels and post counts across the full corpus and by language account.

\keepXColumns

Topic Label	Bitcoin Crypto Value	City Crisis Protest	Covid Pandemic Issues	Middle East Wars	Recent News	US-Russia-Ukraine Sanctions
RT	135	445	199	113	2343	2153
RT America	54	13	103	17	520	420
RT Arabic	39	7	5	5	855	1671
RT DE	19	17	180	34	1432	843
RT French	25	103	1480	119	7515	2559
RT Spanish	1051	1115	641	101	7588	3251
RT UK	23	21	63	11	738	159
TOTAL	1346	1721	2671	400	20991	11056

Qualitatively each of the RT topics focused on different aspects of economic messaging. The most emphasized topic, Recent News Headlines, spanned a spectrum of economic and societal issues globally. Posts ranged from the Yellow Vests protests in Paris and boycotts against the Turkish President to the US Federal Reserve’s interest rates and China’s sale of US debt (e.g., RT America on June 10, 2020). Posts delved into the Bank of England’s Venezuelan gold seizure and the effects of sanctions on Venezuela’s pandemic response (e.g., RT America on April 22, 2020 and RT UK May 20, 2020). The main channel of RT addressed corruption, societal concerns, and everyday challenges like debt evasion and the financial impacts of personal actions. RT DE discussed local German issues, including penalties for minor public infractions and mask mandates. RT French emphasized press freedom and civic rights amid law enforcement challenges. RT en Español focused on Latin American topics such as Colombia’s defense spending during the pandemic, Venezuela’s economic crisis caused by external pressures, and Ecuador’s public dissent against austerity measures (e.g., RT en Español on May 12, 2020, February 13, 2019 and October 8, 2019).

The second most emphasized topic, US-Russia-Ukraine Sanctions, focused on the conflict and sanctions across all the pages. In RT Main, RT UK, RT French, and RT DE, the posts highlighted the rising utility costs resulting from Europe EU sanctions on Russia and the importance of Russian energy. RT Arabic took a different approach, discussing Russia’s role in the Middle East brokering deals between an Indian businessmen and Saudi Arabia (e.g., RT Arabic post on November 11, 2021). RT en Español drew attention to the global consequences of sanctions, such as using posts claiming Russia and Iran had ended the use of the US dollar in bilateral economic transactions, opting instead for their own national currencies (e.g., RT en Español February 5, 2019).

Posts representative of third most emphasized topic Covid Pandemic and Related Issues were heavily focused on the post-pandemic period. RT generally criticized Western governments policies for causing economic problems and drew attention to price differences between Pfizer and Russian vaccines. Further, they highlighted dramatic increases in wealth for the top American billionaires, a phenomenon exacerbating concerns about wealth concentration during a notable period of widespread economic hardship. RT America primarily discussed significant stock sell-offs by top US executives and the Amazon CEO before the COVID-19 pandemic hit to raise questions about insider trading (e.g., RT America on 2020-03-24). RT UK similarly focused on criticizing UK policies regarding UK capital, COVID restrictions, and corruption. RT Arabic had only five posts related to this topic and all focused on a Russian mathematical model designed to cure Covid-19 and its resulting economic lockdowns. RT DE and RT French focused on the pandemic’s effects and policy responses, with RT en Español highlighted Latin America’s interactions with Russia and China amidst the pandemic.

Representative posts associated with the fourth most emphasized topic City Crisis Protest and Disaster presented a tapestry of global events deeply interwoven with consequential economic ramifications. RT America highlighted protests in Iraq, ensuing attacks on US embassies, and Virginian debates over climate policy and public education funding (e.g., RT America on January 27th, 2020 and January 28th, 2019). RT UK highlighted the economic uncertainties stirred by Brexit and the Extinction Rebellion’s protests in London. RT Arabic reported on the immediate financial costs of a possible solar storm and on broader economic trends (e.g., the decline of the Turkish lire) to expose the fragile underpinnings of national economies in the face of global challenges. Meanwhile, RT DE, RT French, and RT en Español chronicled a range of natural and man-made catastrophes across Europe to South America, with each account shedding light on the economic devastation left behind and the pressing need for economic aid and recovery initiatives.

RT channels posts associated with the fifth highest topic Bitcoin Cryptocurrency Value encompassed the broad landscape of cryptocurrencies. The range of subject matter included RT’s detailing of significant heists, Indonesia’s religious stance against crypto trading (e.g., RT on November 13, 2021), and America’s apprehensions about Bitcoin’s geopolitical implications (e.g., RT America on September 14, 2021). The focus of the posts spanned continents, encompassing America’s scrutiny of China’s burgeoning digital currency, the privacy implications of Facebook’s global financial ventures (e.g., RT America September 13, 2021), and the UK’s potential leap towards a national digital currency amid post-Brexit shifts (e.g., RT UK on April 4 and 21, 2021). RT Arabic highlighted the mercurial fortunes tied to digital currencies (e.g., RT Arabic on May 19, 2022) as exemplified by the dramatic losses of tech leaders and Facebook’s shelving of "Diem" (e.g., RT Arabic February 2, 2022). Posts on RT De and RT French reflected European concerns over privacy, market stability, and the rise of Bitcoin. RT Spanish posts broadened the discourse to include oil market fluctuations and ethical trading issues (e.g., RT en Español March 8th, 2020).

The smallest topic in terms of number of posts, Middle East Wars and Conflict, often spotlighted the stark consequences of geopolitical instability and conflict, with a particular emphasis on Afghanistan. The main channel of RT covered the tumultuous withdrawal of US forces from Afghanistan and the resurgence of the Taliban, highlighting the political fallout the profound economic implications. The main channel’s posts also delved into Afghanistan’s black market opium production, a multi-billion dollar industry that fueled both the global drug trade and terrorist financing. The posts also described plundered wealth by fleeing officials and the economic vacuum left by departing foreign forces (e.g., RT January 8th, 2022). RT America posts emphasized the economic costs of the US’s longest war by discussing the staggering cost to American taxpayers and the fortunes made by defense contractors (e.g., RT America on August 17th, 2021). RT UK focused on the UK’s military re-engagement in Kabul for evacuation operations, signaling ongoing financial and human costs of the conflict despite an official end to combat operations (e.g., RT UK on August 16th, 2021). The same channel also raised concerns about the potential rise in terror threats in the post-Afghanistan collapse and its impact on security spending. RT DE addressed the economic repercussions of war through reports on the vast amounts of US military equipment left behind and critiqued economic strategies that lhad ed to such outcomes (e.g., RT DE on September 13th, 2021). RT DE, RT French and RT en Español explored individual desperation in Afghanistan, prompting drastic measures like organ sales and the international community’s response to the burgeoning humanitarian crisis (e.g., RT French October 12nd, 2021 and RT en Español August 16th, 2021). RT en Español touched on the US financial legacy in Afghanistan, critiquing the vast expenses and questioning the effectiveness of military intervention (e.g., RT en Español April 18th, 2021). In contrast, RT Arabic posts did not discuss Afghanistan and USA but did highlight the United Nations’ call for the Taliban to halt punitive measures like flogging, execution, and stoning (RT Arabic on May 8th, 2023).

Overall, the RT channels highlighted a complex interplay between war, economic interests, and human costs. Collectively, they stressed the cycle where geopolitical strategies directly influenced global and local economies, often with long-lasting and far-reaching consequences. See Figure 4 for independent and dependent variables over time for the rest of the results.

3.2 RQ2: RT Economic Content and the Value of the Russian Ruble

Over the past five years, the value of the Russian Ruble had a statistically significant predictive power on the level of posts related to Recent News Headlines on RT-DE and US-Russia-Ukraine Sanctions on the main RT page. Table 2 displays results for the VAR estimates, and Table 3 demonstrates a unidirectional relationship between the value of the Russian Ruble and the pages. For VAR results of all variables, see Tables S5 to S11; for Granger Causality, see Table S12.

	RT DE Recent News Headlines	RT US-Russia-Ukraine Sanctions
Ruble (-1)	$4506.965^{**}$ (1551.461)	$-3755.434^{*}$ (1791.887)
Interruption 1 (Covid-19)	2.231 (3.040)	9.476∗ (3.782)
Interruption 2 (Russia-Ukraine)	-1.308 (5.549)	16.765∗ (6.899)
Constant	-0.965 (2.965)	2.325 (3.594)
Trend	0.030 (0.149)	$-0.390^{*}$ (0.184)
Num.Obs.	58	58
$R^{2}$	0.320	0.179
$R^{2}$ Adj.	0.254	0.100
${}^{+}p<0.10$, * $p<0.05$, ** $p<0.01$, *** $p<0.001$

Page	Granger Causality P Value
RT DE Recent News Headlines	0.0045∗∗
RT US-Russia-Ukraine Sanctions	0.0385∗
Note: ${}^{*}p<0.05$, ${}^{**}p<0.01$, ${}^{***}p<0.001$

The IRF graphs (Figure 5) visualize the effect of one standard deviation change in the value of the Russian Ruble on post volumes of RT DE related to Recent News Headlines (Panel A) and RT US-Russia-Ukraine Sanctions (Panel B) topics. Panel A shows that a positive trend in the Ruble (currency becoming stronger) led to a temporary increase in the Recent News Headlines topic prominence in RT DE. Panel B shows that a positive trend in the Ruble (currency becoming stronger) increased the topic prominence of US-Russia-Ukraine Sanctions in RT upon the Ruble shock, but the topic prominence sharply declined in the first month, then increased and gradually faded to the baseline level.

3.3 RQ3: RT Economic Content and Ural Oil Prices

For the past five years, the Ural Oil prices (Table 4) had a statistically significant predictive power on RT Arabic’s posts on Covid Pandemic and Related Issues, RT Main’s posts on Covid Pandemic and Related Issues and US-Russia-Ukraine Sanctions, RT DE’s posts on Bitcoin Cryptocurrency Value, RT DE’s posts on Covid Pandemic and Related Issues and RT en Español’s posts on US-Russia-Ukraine Sanctions (for more, see Table 4 for Granger causality; Tables S17 to S23 for VAR results of all variables; and Table S24 for Granger Causality).

	RT Arabic Covid Pandemic and Related Issues	RT Covid Pandemic and Related Issues	RT DE Bitcoin Cryptocurrency Value	RT DE Covid Pandemic and Related Issues	RT en Español US-Russia-Ukraine Sanctions	RT US-Russia-Ukraine Sanctions
Ural Oil Price (-1)	$-0.014^{*}$ $(0.007)$	$-0.163^{*}$ $(0.063)$	$-0.026^{*}$ $(0.012)$	$-0.153^{***}$ $(0.040)$	$1.512^{*}$ $(0.654)$	$0.383^{*}$ $(0.186)$
Interruption 1 (Covid-19)	$-0.004$ $(0.133)$	$-0.807$ $(1.158)$	$0.052$ $(0.234)$	$-1.074$ $(0.763)$	$5.734$ $(12.716)$	$7.716^{*}$ $(3.719)$
Interruption 2 (Russia-Ukraine)	$-0.012$ $(0.243)$	$-2.413$ $(2.127)$	$-0.356$ $(0.428)$	$-4.913^{**}$ $(1.411)$	$20.141$ $(23.347)$	$15.260^{*}$ $(6.815)$
Constant	$-0.030$ $(0.132)$	$-0.284$ $(1.144)$	$-0.134$ $(0.229)$	$-1.134$ $(0.755)$	$7.117$ $(12.546)$	$2.660$ $(3.617)$
Trend	$0.001$ $(0.007)$	$0.047$ $(0.057)$	$0.007$ $(0.011)$	$0.107^{**}$ $(0.038)$	$-0.458$ $(0.624)$	$-0.348^{+}$ $(0.181)$
Num.Obs.	58	58	58	58	58	58
R2	0.404	0.139	0.252	0.392	0.140	0.177
R2 Adj.	0.346	0.056	0.180	0.334	0.057	0.098
${}^{+}p<0.10$, * $p<0.05$, ** $p<0.01$, *** $p<0.001$

Page	Granger Causality P Value
RT Arabic Covid Pandemic and Related Issues	0.0383*
RT Covid Pandemic and Related Issues	0.0107*
RT DE Bitcoin Cryptocurrency Value	0.0318*
RT DE Covid Pandemic and Related Issues	0.0002***
RT en Español US-Russia-Ukraine Sanctions	0.0228*
RT US-Russia-Ukraine Sanctions	0.0418*
Note: ${}^{*}p<0.05$, ${}^{**}p<0.01$, ${}^{***}p<0.001$

The IRF graphs (Figure 6) depict the reaction of the RT account pages’ topic prominence following a one standard deviation increase in oil prices. Panel A documents the impact of RT Arabic posts about Covid Pandemic and Related Issues in relation to oil prices; although modest, the response to the change in oil prices showed a consistent negative response, with the effect tapering off and returning to the baseline after approximately five months. The confidence intervals remained tight throughout the horizon. Panel B shows a pronounced negative response to post volume on Bitcoin Cryptocurrency Value in RT DE, reaching its nadir in the second month post-increase. The topic’s prominence gradually reverts to baseline levels, with the effect dissipating entirely by the tenth month. Panel C illustrates that the prominence of Covid Pandemic and Related Issues in RT DE is initially negative, mirroring the pattern observed in RT Arabic’s coverage of the same topic (Panel A), but with a quicker reversion to the mean, suggesting a transient impact of oil prices on this topic. Panel E displays a relatively stable pattern of RT en Español postings on US-Russia-Ukraine Sanctions with minor fluctuations within the confidence interval, indicating a negligible impact of oil price shocks on the topic’s prominence within the observed period. Like the Arabic and DE responses to the COVID-19 Pandemic and Related Issues, the same topic in RT, illustrated in Panel D, shows an evident yet negative impact, which stabilized after an initial decline, indicating a potential transient concern with oil price volatility with COVID-19 coverage. In Panel F, a unique response to US-Russia-Ukraine-Sanctions in RT was detected, characterized by a significant initial increase in topic prominence, followed by a sharp reversal and a gradual return to baseline, highlighting a complex interaction between oil price changes and the coverage of US-Russia-Ukraine Sanctions.

4 Discussion

RT Facebook posts on the economy were a pivotal component of Russia’s public diplomacy efforts during the last five years. The platform posted almost forty thousand messages on economic topics, or seven percent of the full corpus during the study’s timespan. Economic posts as a percentage of Russia’s overall content on Facebook was lower than that of other Russian public diplomacy forums, such as Golan & Viatchaninova’s [13] finding that 26% of Russian advertorials in foreign newspapers addressed economic issues as most salient. Still, Facebook’s network amplification affordance, coupled with its wide audience, positions the social media platform to function as a key contributor to message reinforcement in Russia’s public diplomacy campaign.

RT Facebook does not treat economics as a unitary, hom*ogenous concept. Under the Recent News Headlines, its posts emphasize the relative strengths or weaknesses of global currencies and national economic policies. They also target local economic anxieties such as COVID-19 lockdowns, energy prices in European countries, protests arising from economic grievances in Latin America, and questions about the hegemony of the US Dollar and EU currencies. Further, Posts aligning within topics directly questioning US motivations for sanctions on Russia and the dollar’s value underscore that the United States poses an ongoing threat to the global population. On the whole, RT’s top topics all focus on economic concerns rather than the economic benefits from a Russian alliance.

While the economic content across the full corpus consistently reiterates RT’s topics of anti-sanctions, the US dollar, the Russian Ruble, energy, and protests, the language pages often rely on unique audience strategies for the bulk of the platform’s most representative topics. Consider the topic of the US dollar, for example. RT America highlighted the US dollar’s declining value and the Ruble’s increasing value, while non-anglophone pages like RT DE emphasized that China and Russia would return to the gold standard to free themselves from the US Dollar’s global dominance. Such rumors and misinformation acquire power from social transmission and repeated exposure [95], two factors that further highlight Facebook’s value as a preferred platform for Russian message dissemination.

At times, RT Facebook public diplomacy efforts emphasize distinct economic topics on their language-based pages. RT en Español, for example, placed the largest emphasis on the value of cryptocurrencies. Posts maintained that the cryptocurrencies were denigrating the US Dollar and serving as a viable alternative for the global economy. Such a targeted message has significant implications given that Latin America and the Caribbean (LAC) are leading the way in adopting digital money, led by Bukele who made Bitcoin a legal tender in El Salvador [96, 97, 98].

Mostly, however, the language accounts of RT Facebook utilize similar patterns of topic repetition when discussing economic comments. All language accounts except RT Arabic posts are most often about Recent News Headlines. In fact, the posts constitute almost double the number of posts associated with the second largest topic, US-Russian-Ukrainian Sanctions. While switching the topics’ rank order, RT Arabic posts the same two topics most often. The emphasis on Recent News Headlines suggests that RT Facebook, regardless of language account, is establishing itself as a go-to economics news source. The focus on US-Russian-Ukrainian Sanctions, by contrast, emphasizes the global consequences of the U.S.-led, anti-Russian policy and spiked in relation to posts about recent headlines.

Notably the dominant message factor explaining differential content across language account pages of RT Facebook are national economic contexts. In posts related to the US-Russia-Ukraine Sanction topic, for example, the main RT page emphasized US “economic terrorism” on nations like Venezuela, China, and Russia (RT post on 5/31/2019), RT DE focused on Germany’s defense budget, and RT Arabic emphasized Western sanctions on Russia, Belarus, Turkey, Saudi Arabia, Venezuela, Syria, Hezbollah, and the Myanmar junta. The emphasis on matters of national economic concern worked to position RT as a platform capable of attracting and sustaining global viewers.

During the study’s time frame, major external shocks occurring also result in shifts in the economic content of RT Facebook pages. The onset of the COVID-19 pandemic increased the economic content on RT French and RT DE, perhaps because France and Germany were among the European epicenters of the pandemic at its start due to their close proximity to Italy [99, 91]. The onset of Russia’s most recent invasion of Ukraine, however, increased economic content volume across all pages except for RT French. Russia’s economic costs associated with the war, heightened by the imposition of the Western sanctions, are a likely explanation for the consistent use of the global economic messaging strategy, as the prominence of the US-Russia-Ukraine Sanction topic attests.

Adding to previous notions that trade balances between countries serve as a critical context factor at work in public diplomacy efforts [65], this study documents that the frequency of RT economic content varies in relation to currency fluctuations. Changes in the Ruble’s value affect the topic prominence of Recent News Headlines and US-Russia-Ukraine Sanctions, hinting at a reactive content strategy to economic conditions on the ground. Such shifts, however, are not uniform across all language platforms, highlighting RT’s strategic targeting of regional and linguistic audience sensitivities. The temporary nature of the correspondence between the economy topic’s prominence and the value of the currency is temporary on certain language accounts, suggesting that reactive public diplomacy responses would need to be timely to distract from RT’s heightened topic focus.

The varied responses to oil prices across different topics and languages underscore the adaptability of RT’s targeted economic messaging to external economic factors. Following increased oil prices, for example, the main channel of RT, RT Arabic, and RT DE posts about Covid Pandemic and Related Issues experienced slight declines. However, RT DE’s post volume on Bitcoin Cryptocurrency Value dropped dramatically in relation to rising oil prices, while the most volatile RT messaging shifts both positive and negative focused on US-Russia-Ukraine-Sanctions. Initially, explain how sanctions cause rise in oil prices. The range of topics that experience frequency changes— online currencies, health crises, and economic sanctions — suggest that oil prices constitute a flexible context variable with wide application in Russia’s public diplomacy program.

Overall, this study makes clear that a full accounting of Russia’s economic-based public diplomacy cannot occur without consideration of multiple variables. A nuanced contemplation of specific economic topics, explorations of language-based, audience targeting strategies, an understanding of how economic variables interact with key situational events like pandemics and wars, and attention to changes in currency valuations and oil prices over time combine to define the communicative landscape. Such a multi-factor approach likely has value beyond the Russian context, as the general factors of economic messaging, audience targeting, and economic context changes recur across public diplomacy contexts.

5 Future Areas of Study

The limits of this study are suggestive about productive avenues for future research. First, instead of focusing on a single currency (the Russian Ruble), a more comprehensive analysis should compare levels of public diplomacy social media content with other leading currencies, including the US Dollar, the UK Pound, the Saudi Arabian Rial, and the Euro to build out understandings of the economic context-content relationship. Second, the approach used here (BERTopic) is a generative model where the computer assigns each post to a single topic. This precludes a post from sorting into multiple topics that would be more valid if overcome. However, alternative models such as LDA topic modeling do not have multi-lingual capacities without translation. Thus, a future study comparing LDA with BERTopic would provide valuable insights into the advantages and shortcomings of both topic modeling methods for understanding public diplomacy.

Future studies should also focus on expanding this methodology around the implications of RT’s economic content and how the disseminated information could affect voter perceptions, and global financial behaviors. For example, state-sponsored media releases of information about economic events could influence commodity markets if traders and investors adjust their strategies based on the news’ perceived credibility. This impact on market sentiments could be significant, especially if the information pertains to sanctions, oil prices, currency valuations, and critical economic indicators. This could influence voter perceptions of the state of the economy in a country.

Finally, rather than focusing on RT, economic public diplomacy strategies should be compared on other state-sponsored media entities like China’s CGTN or Iran’s Press. Messaging approaches and platforms may differ, even if the underlying objectives influencing international perception, reinforcing national narratives, and countering Western media perspectives remain similar. This comparison highlights a trend in global information campaigns where economic messaging may be coming increasingly weaponized.

References

• [1]Sean Kates and JoshuaA. Tucker.We never change, do we? economic anxiety and far-right identification in a postcrisis europe*.Social Science Quarterly, 100(2):494–523, 2019.
• [2]Dani Rodrik.Why does globalization fuel populism? economics, culture, and the rise of right-wing populism.Annual Review of Economics, 13(1):133–170, 2021.
• [3]BrandonJ. Schmeichel and David Tang.Individual differences in executive functioning and their relationship to emotional processes and responses.Current Directions in Psychological Science, 24(2):93–98, 4 2015.
• [4]Jack Citrin, DonaldP. Green, Christopher Muste, and Cara Wong.Public opinion toward immigration reform: The role of economic motivations.The Journal of Politics, 59(3):858–881, 8 1997.publisher: The University of Chicago Press.
• [5]Thiemo Fetzer, Lukas Hensel, Johannes Hermle, and Christopher Roth.Coronavirus perceptions and economic anxiety.The Review of Economics and Statistics, 103(5):968–978, 11 2021.
• [6]David A.M. Peterson, KristyC. Carter, DaraM. Wald, William Gustafson, Sidney Hartz, Jacob Donahue, JoeR. Eilers, AnneE. Hamilton, Kyle S.H. Hutchings, FedericoE. Macchiavelli, AaronJ. Mehner, Zaira P.Pagan Cajigas, Olivia Pfeiffer, and AaronJ. VanMiddendorp.Carbon or cash: Evaluating the effectiveness of environmental and economic messages on attitudes about wind energy in the united states.Energy Research & Social Science, 51:119–128, 5 2019.
• [7]R.Michael Alvarez and Jonathan Nagler.Economics, issues and the perot candidacy: Voter choice in the 1992 presidential election.American Journal of Political Science, 39(3):714–744, 1995.publisher: [Midwest Political Science Association, Wiley].
• [8]Mauro Caselli, Andrea Fracasso, and Silvio Traverso.Globalization and electoral outcomes: Evidence from italy.Economics & Politics, 32(1):68–103, 2020.
• [9]PhilipEdward Jones.Economic voting appeals in congressional campaigns.Political Communication, 32(2):206–228, 4 2015.publisher: Routledge.
• [10]Elina DeSimone and PauloReis Mourao.Rhetoric on the economy: have european parties changed their economic messages?Applied Economics, 48(22):2022–2036, 5 2016.publisher: Routledge.
• [11]Kyungmo Kim and GeorgeA. Barnett.The determinants of international news flow: A network analysis.Communication Research, 23(3):323–352, 6 1996.publisher: SAGE Publications Inc.
• [12]Elizabeth Stoycheff and ErikC. Nisbet.Priming the costs of conflict? russian public opinion about the 2014 crimean conflict.International Journal of Public Opinion Research, 29(4):657–675, 12 2017.
• [13]GuyJ. Golan and Evhenia“Zhenia” Viatchaninova.The advertorial as a tool of mediated public diplomacy.International Journal of Communication, 8(0):21, 4 2014.number: 0.
• [14]M.Laeeq Khan, Muhammad Ittefaq, Yadira IxchelMartínez Pantoja, MuhammadMustafa Raziq, and Aqdas Malik.Public engagement model to analyze digital diplomacy on twitter: A social media analytics framework.International Journal of Communication, 15(0):29, 3 2021.number: 0.
• [15]Hongmei Li and LeslieL. Marsh.Brics| building the brics: Media, nation branding and global citizenship — introduction.International Journal of Communication, 10(0):16, 6 2016.number: 0.
• [16]Lacey Milam and ElizabethJohnson Avery.Apps4africa: A new state department public diplomacy initiative.Public Relations Review, 38(2):328–335, 6 2012.
• [17]NilsS. Borchers.“do you really think russia should pay up for that?”: How the russia-based tv channel rt constructs russian-baltic relations.Javnost - The Public, 18(4):89–106, 1 2011.publisher: Routledge.
• [18]Martin Kragh and Sebastian Åsberg.Russia’s strategy for influence through public diplomacy and active measures: the swedish case.Journal of Strategic Studies, 40(6):773–816, 9 2017.publisher: Routledge.
• [19]LukasI. Alpert.Kremlin Speak: Inside Putin’s Propaganda Factory.Tatra Press, New York, N.Y., 11 2014.
• [20]Charlotte Wagnsson.The paperboys of russian messaging: Rt/sputnik audiences as vehicles for malign information influence.Information, Communication & Society, 26(9):1849–1867, 7 2023.publisher: Routledge.
• [21]ErinBaggott Carter and BrettL. Carter.Questioning more: Rt, outward-facing propaganda, and the post-west world order.Security Studies, 30(1):49–78, 1 2021.publisher: Routledge.
• [22]Natalia Knoblock.A look at brexit by rt, a russian news source.Critical Approaches to Discourse Analysis across Disciplines, 13(1):107–126, 2021.
• [23]NicholasJ. Cull.Public Diplomacy: Lessons from the Past.CPD Perspectives on Public Diplomacy. Figueroa Press, Los Angeles, CA, 2009.
• [24]WilliamF. Williamson and JohnRobert Kelley.Public diplomacy 2.0 classroom.Global Media Journal, (Fall), 2012.
• [25]Philip Napoli and Robyn Caplan.Why media companies insist they’re not media companies, why they’re wrong, and why it matters.First Monday, 5 2017.[Online; accessed 2024-03-26].
• [26]Richard Fletcher and RasmusKleis Nielsen.Are people incidentally exposed to news on social media? a comparative analysis.New Media & Society, 20(7):2450–2468, 7 2018.publisher: SAGE Publications.
• [27]Galen Stocking, Amy Mitchell, KaterinaEva Matsa, Regina Widjaya, Mark Jurkowitz, Shreenita Ghosh, Aaron Smith, Sarah Naseer, and ChristopherSt. Aubin.The role of alternative social media in the news and information environment.Technical report, Washington, D.C., 10 2022.[Online; accessed 2023-05-09].
• [28]Jerzy Surma.Social exchange in online social networks. the reciprocity phenomenon on facebook.Computer Communications, 73:342–346, 1 2016.
• [29]Ronit Kampf, Ilan Manor, and Elad Segev.Digital diplomacy 2.0? a cross-national comparison of public engagement in facebook and twitter.The Hague Journal of Diplomacy, 10(4):331–362, 10 2015.publisher: Brill Nijhoff.
• [30]Craig Hayden.Digital diplomacy.The encyclopedia of diplomacy, pages 1–13, 2018.publisher: John Wiley & Sons, Ltd Chichester, West Sussex, UK.
• [31]LuweiRose Luqiu and Fan Yang.Weibo diplomacy: Foreign embassies communicating on chinese social media.Government Information Quarterly, 37(3):101477, 7 2020.
• [32]Rhys Crilley, Marie Gillespie, Bertie Vidgen, and Alistair Willis.Understanding rt’s audiences: Exposure not endorsem*nt for twitter followers of russian state-sponsored media.The International Journal of Press/Politics, 27(1):220–242, 1 2022.publisher: SAGE Publications Inc.
• [33]danah boyd.Social network sites as networked publics: Affordances, dynamics, and implications.In A Networked Self. Routledge, 2010.number-of-pages: 20.
• [34]Don Norman.The design of everyday things: Revised and expanded edition.Basic books, 2013.
• [35]Barry Wellman, Anabel Quan-Haase, Jeffrey Boase, Wenhong Chen, Keith Hampton, Isabel Díaz, and Kakuko Miyata.The Social Affordances of the Internet for Networked Individualism.Journal of Computer-Mediated Communication, 8(3):JCMC834, April 2003.
• [36]Robert Bodle.Assessing social network sites as international platforms: Guiding principles.The Journal of International Communication, 16(2):9–24, 1 2010.publisher: Routledge.
• [37]Andrea Ceron.Internet, news, and political trust: The difference between social media and online media outlets.Journal of Computer-Mediated Communication, 20(5):487–503, 9 2015.
• [38]Herman Wasserman and Dani Madrid-Morales.How influential are chinese media in africa? an audience analysis in kenya and south africa.International Journal of Communication, 12(0):20, 5 2018.number: 0.
• [39]Mona Elswah and PhilipN Howard.“anything that causes chaos”: The organizational behavior of russia today (rt).Journal of Communication, 70(5):623–645, 10 2020.
• [40]Aleksandr Fisher.Demonizing the enemy: the influence of russian state-sponsored media on american audiences.Post-Soviet Affairs, 36(4):281–296, 7 2020.publisher: Routledge.
• [41]Yevgeniy Golovchenko, Cody Buntain, Gregory Eady, MeganA. Brown, and JoshuaA. Tucker.Cross-platform state propaganda: Russian trolls on twitter and youtube during the 2016 u.s. presidential election.The International Journal of Press/Politics, 25(3):357–389, 7 2020.
• [42]Kathy Fitzpatrick.Advancing the new public diplomacy: A public relations perspective.The Hague Journal of Diplomacy, 2(3):187–211, 1 2007.publisher: Brill Nijhoff.
• [43]JosephS. Nye.Soft Power.PublicAffairs, New York; N.Y, first edition edition, 4 2005.
• [44]James Morrison.“scrounger-bashing” as national pastime: the prevalence and ferocity of anti-welfare ideology on niche-interest online forums.Social Semiotics, 31(3):383–401, 5 2021.publisher: Routledge.
• [45]Carlina DiRusso and JessicaGall Myrick.Sustainability in csr messages on social media: How emotional framing and efficacy affect emotional response, memory and persuasion.Environmental Communication, 15(8):1045–1060, 11 2021.publisher: Routledge.
• [46]Danica Jovanovic and Theo VanLeeuwen.Multimodal dialogue on social media.Social Semiotics, 28(5):683–699, 10 2018.publisher: Routledge.
• [47]Moran Yarchi, Christian Baden, and Neta Kligler-Vilenchik.Political polarization on the digital sphere: A cross-platform, over-time analysis of interactional, positional, and affective polarization on social media.Political Communication, 38(1-2):98–139, 3 2021.publisher: Routledge.
• [48]Bin Chen, Josephine Lukito, and GyoHyun Koo.Comparing the #stopthesteal movement across multiple platforms: Differentiating discourse on facebook, twitter, and parler.Social Media + Society, 9(3):20563051231196879, 7 2023.publisher: SAGE Publications Ltd.
• [49]DeirdreN. McCloskey.The rhetoric of economics.Rhetoric of the human sciences. University of Wisconsin Press, Madison, Wis, 2nd ed edition, 1998.
• [50]JamesArnt Aune.Selling the free market: the rhetoric of economic correctness.Guilford, New York; London, 2002.OCLC: 49593997.
• [51]RichardHarvey Brown.Global capitalism, national sovereignty, and the decline of democratic space.Rhetoric & Public Affairs, 5(2):347–357, 2002.
• [52]Catherine Chaput.Trumponomics, neoliberal branding, and the rhetorical circulation of affect.Advances in the History of Rhetoric, 21(2):194–209, 5 2018.
• [53]Catherine Chaput and JoshuaS. Hanan.Economic rhetoric as Taxis: Neoliberal governmentality and the dispositif of freakonomics.Journal of Cultural Economy, 8(1):42–61, 1 2015.
• [54]RojhatB. Avsar.Mainstream economic rhetoric, ideology and institutions.Journal of Economic Issues, 45(1):137–158, 3 2011.
• [55]RobertK. Goidel and RonaldE. Langley.Media coverage of the economy and aggregate economic evaluations: Uncovering evidence of indirect media effects.Political Research Quarterly, 48(2):313–328, 1995.publisher: [University of Utah, Sage Publications, Inc.].
• [56]StuartN. Soroka, DominikA. Stecula, and Christopher Wlezien.It’s (change in) the (future) economy, stupid: Economic indicators, the media, and public opinion.American Journal of Political Science, 59(2):457–474, 2015.
• [57]JoshuaS. Hanan.From economic rhetoric to economic imaginaries: A critical genealogy of economic rhetoric in u.s. communication studies.In JoshuaS. Hanan and Mark Hayward, editors, Communication and the economy: history, value, and agency, Frontiers in political communication, pages 67–94. Peter Lang, New York, 2014.
• [58]B.Dan Wood.Presidential rhetoric and economic leadership.Presidential Studies Quarterly, 34(3):573–606, 9 2004.
• [59]G.Thomas Goodnight and Sandy Green.Rhetoric, risk, and markets: The dot-com bubble.Quarterly Journal of Speech, 96(2):115–140, 2010.
• [60]DavisW Houck.Rhetoric as currency: Herbert hoover and the 1929 stock market crash.Rhetoric & Public Affairs, 3(2):155–181, 2000.
• [61]Levasseur and Gring-Pemble.Not all capitalist stories are created equal: Mitt romney’s bain capital narrative and the deep divide in american economic rhetoric.Rhetoric & Public Affairs, 18(1):1, 2015.
• [62]RichardE. Crable and StevenL. Vibbert.Argumentative stance and political faith healing: “the dream will come true”.Quarterly Journal of Speech, 69(3):290–301, 8 1983.
• [63]David Zarefsky.The great society as a rhetorical proposition.Quarterly Journal of Speech, 65(4):364–378, 12 1979.
• [64]Herman Lebovics.Economic positivism as rhetoric.International Review of Social History, 37(2):244–251, 8 1992.
• [65]Liudmila Khalitova, Barbara Myslik, Agnieszka Turska-Kawa, Sofiya Tarasevich, and Spiro Kiousis.He who pays the piper, calls the tune? examining russia’s and poland’s public diplomacy efforts to shape the international coverage of the smolensk crash.Public Relations Review, 46(2):101858, 6 2020.
• [66]Natalia Grincheva and Jiayi Lu.Brics summit diplomacy: Constructing national identities through russian and chinese media coverage of the fifth brics summit in durban, south africa.Global Media and Communication, 12(1):25–47, 4 2016.publisher: SAGE Publications.
• [67]Statista.Number of facebook users in russia from 2018 to 2027 (in millions) [graph], 6 2022.
• [68]RobertS. Fortner.Public Diplomacy and International Politics: The Symbolic Constructs of Summits and International Radio News.Praeger, Westport, Conn, 4 1994.
• [69]Olga Krasnyak.Russian science diplomacy.Diplomatica, 2(1):118–134, 5 2020.publisher: Brill.
• [70]MarkAndreas Kayser and Christopher Wlezien.Performance pressure: Patterns of partisanship and the economic vote.European Journal of Political Research, 50(3):365–394, 2011.
• [71]MichaelS. Lewis-Beck.Economics and the american voter: Past, present, future.Political Behavior, 10(1):5–21, 1988.publisher: Springer.
• [72]MichaelS. Lewis-Beck and Mary Stegmaier.Economic models of voting.In RussellJ. Dalton and Hans-Dieter Klingemann, editors, The Oxford Handbook of Political Behavior, page0. Oxford University Press, 8 2007.DOI: 10.1093/oxfordhb/9780199270125.003.0027.
• [73]MichaelS. Lewis-Beck and Mary Stegmaier.Economic determinants of electoral outcomes.Annual Review of Political Science, 3(1):183–219, 2000.
• [74]Suzanna Linn, Jonathan Nagler, and MarcoA. Morales.Economics, elections, and voting behavior.In JanE. Leighley, editor, The Oxford Handbook of American Elections and Political Behavior, page0. Oxford University Press, 2 2010.DOI: 10.1093/oxfordhb/9780199235476.003.0020.
• [75]Toby Bolsen and FayLomax Cook.The polls—trends: Public opinion on energy policy: 1974–2006.Public Opinion Quarterly, 72(2):364–388, 1 2008.
• [76]BC Farhar, CT Unseld, RVories, and RCrews.Public opinion about energy.Annual Review of Energy, 5(1):141–172, 1980.
• [77]Robert Vidigal and Jennifer Jerit.Issue importance and the correction of misinformation.Political Communication, 39(6):715–736, 11 2022.publisher: Routledge.
• [78]Mustoe.How does brexit affect the pound?BBC News, 10 2019.[Online; accessed 2023-09-22].
• [79]Vladimir Putin.Tucker carlson vladimir putin interview, 2 2024.[Online; accessed 2024-03-25].
• [80]Llewelyn Hughes and PhillipY. Lipscy.The politics of energy.Annual Review of Political Science, 16(1):449–469, 2013.
• [81]Hao Chen, Hua Liao, Bao-Jun Tang, and Yi-Ming Wei.Impacts of opec’s political risk on the international crude oil prices: An empirical analysis based on the svar models.Energy Economics, 57:42–49, 6 2016.
• [82]Pierre-Noël Giraud.The equilibrium price range of oil: Economics, politics and uncertainty in the formation of oil prices.Energy Policy, 23(1):35–49, 1 1995.
• [83]Maarten Grootendorst.Bertopic, 2022.original-date: 2020-09-22T14:19:29Z.
• [84]Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, TevenLe Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and AlexanderM. Rush.Huggingface’s transformers: State-of-the-art natural language processing.2019.publisher: arXiv version: 5.
• [85]The International MonetaryFund (IMF).Exchange rate report wizard, 4 2023.[Online; accessed 2023-04-11].
• [86]TedrosAdhanom Gehebreyesus.Who director-general’s opening remarks at the media briefing on covid-19, 3 2020.[Online; accessed 2023-05-02].
• [87]Center for PreventiveAction.War in ukraine, 3 2023.[Online; accessed 2023-05-02].
• [88]AyseD. Lokmanoglu, ErikC. Nisbet, MatthewT. Osborne, Joseph Tien, Sam Malloy, Lourdes CuevaChacón, Esteban VillaTurek, and Rod Abhari.Social media sentiment about covid-19 vaccination predicts vaccine acceptance among peruvian social media users the next day.Vaccines, 11(4):817, 4 2023.number: 4 publisher: Multidisciplinary Digital Publishing Institute.
• [89]Josephine Lukito.Coordinating a multi-platform disinformation campaign: Internet research agency activity on three u.s. social media platforms, 2015 to 2017.Political Communication, 37(2):238–255, 3 2020.publisher: Routledge.
• [90]HiroY. Toda and Taku Yamamoto.Statistical inference in vector autoregressions with possibly integrated processes.Journal of Econometrics, 66(1):225–250, 3 1995.
• [91]Yotam Ophir, Dror Walter, Daniel Arnon, AyseD. Lokmanoglu, Michele Tizzoni, Joëlle Carota, Lorenzo D’Antiga, and Emanuele Nicastro.The framing of covid-19 in italian media and its relationship with community mobility: A mixed-method approach.Journal of Health Communication, 26(3):161–173, 3 2021.
• [92]Helmut Lütkepohl.Impulse response function.In StevenN. Durlauf and LawrenceE. Blume, editors, Macroeconometrics and Time Series Analysis, pages 145–150. Palgrave Macmillan UK, London, 2010.
• [93]Søren Johansen.Estimation and hypothesis testing of cointegration vectors in gaussian vector autoregressive models.Econometrica, 59(6):1551–1580, 1991.publisher: [Wiley, Econometric Society].
• [94]G.E.P. Box and DavidA. Pierce.Distribution of residual autocorrelations in autoregressive-integrated moving average time series models.Journal of the American Statistical Association, 65(332):1509–1526, 12 1970.publisher: Taylor & Francis.
• [95]AdamJ. Berinsky.Political Rumors: Why We Accept Misinformation and How to Fight It.Princeton University Press, 8 2023.
• [96]Rina Bhattacharya, Dmitry Vasilyev, and Mauricio Villafuerte.Interest in central bank digital currencies picks up in latin america and the caribbean while crypto use varies, 6 2023.[Online; accessed 2023-12-22].
• [97]Chainalysis Team.Latin america cryptocurrency adoption: Data and analysis, 10 2023.[Online; accessed 2023-12-22].
• [98]Christine Murray.The ‘cult’ of bukele: El salvador’s bitcoin-loving strongman heads for second term, 2 2024.[Online; accessed 2024-02-05].
• [99]Ciro Indolfi and Carmen Spaccarotella.The outbreak of covid-19 in italy: Fighting the pandemic.JACC Case Reports, 2(9):1414, 7 2020.publisher: Elsevier PMID: 32835287.

6 Supplementary Material

S6.2 Supplement B: BERTopic Results

\keepXColumns

Topic Label	Post Count	Top 10 Words	BERTopic Label
Recent News Headlines	20,991	lire; dólares; france; millones; millones; dólares; plus; euros; rejoignez; euro; contre;	0_lire_dólares_france_millones
US-Russia-Ukraine Sanctions	11,056	sanctions; us; rusia; ukraine; sanciones; china; russie; russe; russia; ucrania;	1_sanctions_us_rusia_ukraine
Covid Pandemic and Related Issues	2,671	covid; coronavirus; lire; sanitaire; pass; contre; france; plus; vaccination; pass; sanitaire;	2_covid_coronavirus_lire_sanitaire
Bitcoin Cryptocurrency Value	1,346	dólares; bitcóin; criptomoneda; bitcoin; valor; precio; millones; millones; dólares; musk; cryptocurrency;	3_dólares_bitcóin_criptomoneda_bitcoin
City Crisis Protest and Disaster	1,721	capital; personas; ciudad; menos; policía; manifestantes; país; calles; heridos; centro;	4_capital_personas_ciudad_menos
Middle East Wars and Conflict	400	afghanistan; taliban; kabul; us; afganistán; talibanes; capital; afghan; kaboul;	5_afghanistan_taliban_kabul_us
Note: Outlier Count = 1

S6.3 Supplement C: Vector Autoregressive Analysis (VAR)

S6.3.1 ACF & PACF Post-Differencing Variables

ACF & PACF: RT

ACF & PACF: RT America

ACF & PACF: RT Arabic

ACF & PACF: RT DE

ACF & PACF: RT France

ACF & PACF: RT Spanish

ACF & PACF: RT UK

ACF & PACF: Russian Ruble

ACF & PACF: Ural Oil Prices

S6.3.2 Model: Russian Ruble

ADF Values

\keepXColumns

Page	Topic	P_Value
RT	bitcoin cryptocurrency value	0.010
RT	city crisis protest and disaster	0.010
RT	covid pandemic and related issues	0.010
RT	middle east wars and conflict	0.010
RT	recent news headlines	0.010
RT	us russia ukraine sanctions	0.010
RT America	bitcoin cryptocurrency value	0.010
RT America	city crisis protest and disaster	0.010
RT America	covid pandemic and related issues	0.018
RT America	middle east wars and conflict	0.010
RT America	recent news headlines	0.010
RT America	us russia ukraine sanctions	0.010
RT Arabic	bitcoin cryptocurrency value	0.010
RT Arabic	city crisis protest and disaster	0.010
RT Arabic	covid pandemic and related issues	0.010
RT Arabic	middle east wars and conflict	0.010
RT Arabic	recent news headlines	0.010
RT Arabic	us russia ukraine sanctions	0.010
RT DE	bitcoin cryptocurrency value	0.010
RT DE	city crisis protest and disaster	0.010
RT DE	covid pandemic and related issues	0.010
RT DE	middle east wars and conflict	0.010
RT DE	recent news headlines	0.010
RT DE	us russia ukraine sanctions	0.010
RT France	bitcoin cryptocurrency value	0.010
RT France	city crisis protest and disaster	0.010
RT France	covid pandemic and related issues	0.010
RT France	middle east wars and conflict	0.010
RT France	recent news headlines	0.010
RT France	us russia ukraine sanctions	0.010
RT en Espanol	bitcoin cryptocurrency value	0.010
RT en Espanol	city crisis protest and disaster	0.010
RT en Espanol	covid pandemic and related issues	0.010
RT en Espanol	middle east wars and conflict	0.010
RT en Espanol	recent news headlines	0.010
RT en Espanol	us russia ukraine sanctions	0.010
RT UK	bitcoin cryptocurrency value	0.010
RT UK	city crisis protest and disaster	0.010
RT UK	covid pandemic and related issues	0.010
RT UK	middle east wars and conflict	0.010
RT UK	recent news headlines	0.010
RT UK	us russia ukraine sanctions	0.010

SC Lag Values

\keepXColumns

Page	Topic	SC_Value
RT	bitcoin cryptocurrency value	1
RT	city crisis protest and disaster	1
RT	covid pandemic and related issues	1
RT	middle east wars and conflict	1
RT	recent news headlines	1
RT	us russia ukraine sanctions	1
RT America	bitcoin cryptocurrency value	2
RT America	city crisis protest and disaster	2
RT America	covid pandemic and related issues	2
RT America	middle east wars and conflict	2
RT America	recent news headlines	2
RT America	us russia ukraine sanctions	2
RT Arabic	bitcoin cryptocurrency value	1
RT Arabic	city crisis protest and disaster	1
RT Arabic	covid pandemic and related issues	1
RT Arabic	middle east wars and conflict	1
RT Arabic	recent news headlines	1
RT Arabic	us russia ukraine sanctions	1
RT DE	bitcoin cryptocurrency value	1
RT DE	city crisis protest and disaster	1
RT DE	covid pandemic and related issues	1
RT DE	middle east wars and conflict	1
RT DE	recent news headlines	1
RT DE	us russia ukraine sanctions	1
RT France	bitcoin cryptocurrency value	1
RT France	city crisis protest and disaster	1
RT France	covid pandemic and related issues	1
RT France	middle east wars and conflict	1
RT France	recent news headlines	1
RT France	us russia ukraine sanctions	1
RT en Espanol	bitcoin cryptocurrency value	1
RT en Espanol	city crisis protest and disaster	1
RT en Espanol	covid pandemic and related issues	1
RT en Espanol	middle east wars and conflict	1
RT en Espanol	recent news headlines	1
RT en Espanol	us russia ukraine sanctions	1
RT UK	bitcoin cryptocurrency value	1
RT UK	city crisis protest and disaster	1
RT UK	covid pandemic and related issues	1
RT UK	middle east wars and conflict	1
RT UK	recent news headlines	1
RT UK	us russia ukraine sanctions	1

VAR Results

	RT bitcoin cryptocurrency value	RT city crisis protest and disaster	RT covid pandemic and related issues	RT middle east wars and conflict	RT recent news headlines	RT us russia ukraine sanctions
Ruble (-1)	$164.868$ $(413.429)$	$-217.355$ $(944.555)$	$-421.848$ $(565.995)$	$-356.851$ $(1194.054)$	$155.024$ $(1794.439)$	$-3755.434^{*}$ $(1791.887)$
Interruption 1 (Covid-19)	$0.164$ $(0.895)$	$0.083$ $(2.077)$	$-0.768$ $(1.232)$	$-0.252$ $(2.614)$	$4.840$ $(3.902)$	$9.476^{*}$ $(3.782)$
Interruption 2 (Russia-Ukraine)	$0.187$ $(1.634)$	$-0.444$ $(3.779)$	$-1.661$ $(2.248)$	$-0.411$ $(4.766)$	$10.553$ $(7.122)$	$16.765^{*}$ $(6.899)$
Constant	$0.072$ $(0.873)$	$0.038$ $(2.015)$	$0.172$ $(1.201)$	$0.252$ $(2.550)$	$3.059$ $(3.807)$	$2.325$ $(3.594)$
Trend	$-0.007$ $(0.044)$	$0.015$ $(0.101)$	$0.024$ $(0.060)$	$0.000$ $(0.128)$	$-0.282$ $(0.192)$	$-0.390^{*}$ $(0.184)$
Num.Obs.	58	58	58	58	58	58
$R^{2}$	0.030	0.286	0.038	0.188	0.143	0.179
$R^{2}$ Adj.	$-0.063$	0.217	$-0.055$	0.110	0.061	0.100
${}^{+}p<0.10$, * $p<0.05$, ** $p<0.01$, *** $p<0.001$

	RT Arabic bitcoin cryptocurrency value	RT Arabic city crisis protest and disaster	RT Arabic covid pandemic and related issues	RT Arabic middle east wars and conflict	RT Arabic recent news headlines	RT Arabic us russia ukraine sanctions
Ruble (-1)	$183.672$ $(143.648)$	$21.261$ $(59.302)$	$-108.234^{+}$ $(62.151)$	$-47.387$ $(48.379)$	$-743.153$ $(1416.287)$	$-1372.261$ $(3916.704)$
Interruption 1 (Covid-19)	$0.006$ $(0.312)$	$0.008$ $(0.130)$	$0.015$ $(0.136)$	$0.032$ $(0.106)$	$-1.301$ $(3.102)$	$-3.116$ $(8.573)$
Interruption 2 (Russia-Ukraine)	$0.134$ $(0.568)$	$0.032$ $(0.237)$	$0.075$ $(0.247)$	$0.078$ $(0.193)$	$1.645$ $(5.641)$	$1.855$ $(15.547)$
Constant	$-0.245$ $(0.305)$	$0.005$ $(0.128)$	$0.022$ $(0.132)$	$0.032$ $(0.103)$	$-1.183$ $(3.028)$	$-0.468$ $(8.332)$
Trend	$0.010$ $(0.015)$	$-0.001$ $(0.006)$	$-0.002$ $(0.007)$	$-0.002$ $(0.005)$	$0.077$ $(0.152)$	$0.105$ $(0.420)$
Num.Obs.	58	58	58	58	58	58
$R^{2}$	0.188	0.019	0.389	0.129	0.071	0.154
$R^{2}$ Adj.	0.110	$-0.076$	0.330	0.045	$-0.018$	0.073
${}^{+}p<0.10$, * $p<0.05$, ** $p<0.01$, *** $p<0.001$

	RT America bitcoin cryptocurrency value	RT America city crisis protest and disaster	RT America covid pandemic and related issues	RT America middle east wars and conflict	RT Arabic recent news headlines	RT America us russia ukraine sanctions
Ruble (-1)	$688.200$ $(467.755)$	$226.141$ $(210.095)$	$926.738$ $(1738.873)$	$-92.343$ $(323.263)$	$2114.651$ $(1643.863)$	$2211.312$ $(1527.198)$
Ruble (-2)	$358.703$ $(467.507)$	$-185.709$ $(194.163)$	$3182.236^{+}$ $(1665.129)$	$178.482$ $(329.766)$	$363.159$ $(1689.415)$	$1118.256$ $(1433.435)$
Interruption 1 (Covid-19)	$0.554$ $(0.865)$	$0.288$ $(0.359)$	$2.128$ $(2.587)$	$0.544$ $(0.603)$	$3.333$ $(3.095)$	$4.755^{+}$ $(2.614)$
Interruption 2 (Russia-Ukraine)	$0.127$ $(1.348)$	$0.654$ $(0.532)$	$1.621$ $(3.796)$	$0.529$ $(0.904)$	$-0.271$ $(4.603)$	$4.880$ $(3.897)$
Constant	$0.203$ $(0.532)$	$0.058$ $(0.220)$	$0.988$ $(1.528)$	$0.057$ $(0.375)$	$-1.843$ $(1.915)$	$0.453$ $(1.620)$
Trend	$-0.026$ $(0.040)$	$-0.013$ $(0.017)$	$-0.105$ $(0.117)$	$-0.021$ $(0.028)$	$-0.057$ $(0.143)$	$-0.193$ $(0.121)$
Num.Obs.	40	40	40	40	40	40
$R^{2}$	0.353	0.578	0.305	0.395	0.513	0.236
$R^{2}$ Adj.	0.211	0.485	0.153	0.263	0.406	0.069
${}^{+}p<0.10$, * $p<0.05$, ** $p<0.01$, *** $p<0.001$

	RT DE bitcoin cryptocurrency value	RT DE city crisis protest and disaster	RT DE covid pandemic and related issues	RT DE middle east wars and conflict	RT DE recent news headlines	RT DE US Russia Ukraine sanctions
Ruble (-1)	$-3.292$ $(114.048)$	$0.042$ $(102.869)$	$84.102$ $(399.035)$	$141.502$ $(255.404)$	$4506.965^{**}$ $(1551.461)$	$-1167.060$ $(1254.928)$
Interruption 1 (Covid-19)	$0.036$ $(0.246)$	$-0.100$ $(0.225)$	$-1.188$ $(0.870)$	$-0.266$ $(0.558)$	$2.231$ $(3.040)$	$5.223^{+}$ $(2.829)$
Interruption 2 (Russia-Ukraine)	$-0.280$ $(0.447)$	$-0.344$ $(0.411)$	$-4.364^{**}$ $(1.597)$	$-0.765$ $(1.018)$	$-1.308$ $(5.549)$	$7.302$ $(5.064)$
Constant	$-0.068$ $(0.238)$	$-0.069$ $(0.219)$	$-0.736$ $(0.849)$	$-0.093$ $(0.545)$	$-0.965$ $(2.965)$	$0.621$ $(2.644)$
Trend	$0.005$ $(0.012)$	$0.007$ $(0.011)$	$0.091^{*}$ $(0.043)$	$0.016$ $(0.027)$	$0.030$ $(0.149)$	$-0.165$ $(0.136)$
Num.Obs.	58	58	58	58	58	58
$R^{2}$	0.184	0.161	0.220	0.147	0.320	0.202
$R^{2}$ Adj.	0.106	0.080	0.145	0.065	0.254	0.126
${}^{+}p<0.10$, * $p<0.05$, ** $p<0.01$, *** $p<0.001$

	RT France bitcoin cryptocurrency value	RT France city crisis protest and disaster	RT France covid pandemic and related issues	RT France middle east wars and conflict	RT France recent news headlines	RT France US Russia Ukraine sanctions
Ruble (-1)	$38.442$ $(182.501)$	$231.923$ $(370.050)$	$2886.726$ $(3358.811)$	$-329.245$ $(994.870)$	$7303.599$ $(7821.946)$	$6336.360$ $(3912.482)$
Interruption 1 (Covid-19)	$-0.264$ $(0.399)$	$-0.331$ $(0.825)$	$-12.435$ $(7.496)$	$0.065$ $(2.178)$	$-13.073$ $(16.196)$	$1.827$ $(8.302)$
Interruption 2 (Russia-Ukraine)	$-0.792$ $(0.728)$	$-0.055$ $(1.492)$	$-35.160^{*}$ $(14.168)$	$0.253$ $(3.972)$	$-21.459$ $(29.437)$	$-0.891$ $(15.148)$
Constant	$-0.110$ $(0.389)$	$0.346$ $(0.788)$	$-5.089$ $(7.201)$	$0.327$ $(2.124)$	$8.274$ $(15.673)$	$0.831$ $(8.089)$
Trend	$0.016$ $(0.020)$	$-0.004$ $(0.040)$	$0.747^{*}$ $(0.372)$	$-0.015$ $(0.107)$	$0.161$ $(0.787)$	$-0.026$ $(0.407)$
Num.Obs.	58	58	58	58	58	58
$R^{2}$	0.287	0.233	0.127	0.005	0.090	0.194
$R^{2}$ Adj.	0.218	0.160	0.043	$-0.091$	0.002	0.117
${}^{+}p<0.10$, * $p<0.05$, ** $p<0.01$, *** $p<0.001$

	RT SP bitcoin cryptocurrency value	RT SP city crisis protest and disaster	RT SP covid pandemic and related issues	RT SP middle east wars and conflict	RT SP recent news headlines	RT SP US Russia Ukraine sanctions
Ruble (-1)	$128.040$ $(1631.263)$	$865.049$ $(1728.603)$	$-84.237$ $(2205.711)$	$-723.796$ $(1360.909)$	$-877.210$ $(5468.023)$	$-4051.556$ $(6617.212)$
Interruption 1 (Covid-19)	$-1.414$ $(3.445)$	$-2.864$ $(3.791)$	$-0.827$ $(4.604)$	$0.314$ $(2.979)$	$-10.634$ $(11.594)$	$7.743$ $(13.487)$
Interruption 2 (Russia-Ukraine)	$-7.334$ $(6.374)$	$-0.302$ $(6.880)$	$0.405$ $(8.406)$	$1.003$ $(5.431)$	$-1.952$ $(21.091)$	$17.383$ $(24.632)$
Constant	$-0.995$ $(3.361)$	$1.657$ $(3.685)$	$1.516$ $(4.494)$	$0.514$ $(2.906)$	$7.165$ $(11.307)$	$3.778$ $(13.050)$
Trend	$0.140$ $(0.170)$	$0.017$ $(0.185)$	$-0.040$ $(0.226)$	$-0.033$ $(0.146)$	$0.045$ $(0.566)$	$-0.371$ $(0.661)$
Num.Obs.	58	58	58	58	58	58
$R^{2}$	0.085	0.225	0.014	0.191	0.239	0.058
$R^{2}$ Adj.	$-0.003$	0.151	$-0.081$	0.113	0.165	$-0.032$
${}^{+}p<0.10$, * $p<0.05$, ** $p<0.01$, *** $p<0.001$

	RT UK bitcoin cryptocurrency value	RT UK city crisis protest and disaster	RT UK covid pandemic and related issues	RT UK middle east wars and conflict	RT UK recent news headlines	RT UK US Russia Ukraine sanctions
Ruble (-1)	$-10.927$ $(103.197)$	$25.920$ $(117.098)$	$-156.450$ $(211.156)$	$-17.965$ $(104.176)$	$40.092$ $(592.129)$	$-29.105$ $(1072.489)$
Interruption 1 (Covid-19)	$-0.441$ $(0.383)$	$0.182$ $(0.430)$	$-0.282$ $(0.766)$	$-0.010$ $(0.386)$	$0.770$ $(2.180)$	$2.047$ $(2.509)$
Interruption 2 (Russia-Ukraine)	$-1.149^{+}$ $(0.635)$	$0.356$ $(0.713)$	$-0.264$ $(1.272)$	$-0.029$ $(0.642)$	$2.362$ $(3.639)$	$2.249$ $(4.140)$
Constant	$-0.263$ $(0.309)$	$0.137$ $(0.346)$	$0.180$ $(0.619)$	$0.031$ $(0.312)$	$1.252$ $(1.768)$	$0.379$ $(1.963)$
Trend	$0.027$ $(0.018)$	$-0.012$ $(0.020)$	$0.001$ $(0.036)$	$-0.001$ $(0.018)$	$-0.099$ $(0.104)$	$-0.074$ $(0.118)$
Num.Obs.	51	51	51	51	51	51
$R^{2}$	0.236	0.131	0.049	0.172	0.259	0.104
$R^{2}$ Adj.	0.152	0.034	$-0.056$	0.080	0.177	0.004
${}^{+}p<0.10$, * $p<0.05$, ** $p<0.01$, *** $p<0.001$

Granger Causality Results

\keepXColumns

Page	Topic	GC.P.Value	Significance
RT	bitcoin cryptocurrency value	0.6909	ns
RT	city crisis protest and disaster	0.8185	ns
RT	covid pandemic and related issues	0.4578	ns
RT	middle east wars and conflict	0.7656	ns
RT	recent news headlines	0.9313	ns
RT	us russia ukraine sanctions	0.0385	p<0.05*
RT America	bitcoin cryptocurrency value	0.2901	ns
RT America	city crisis protest and disaster	0.3477	ns
RT America	covid pandemic and related issues	0.1691	ns
RT America	middle east wars and conflict	0.8136	ns
RT America	recent news headlines	0.4404	ns
RT America	us russia ukraine sanctions	0.2740	ns
RT Arabic	bitcoin cryptocurrency value	0.2039	ns
RT Arabic	city crisis protest and disaster	0.7207	ns
RT Arabic	covid pandemic and related issues	0.0846	ns
RT Arabic	middle east wars and conflict	0.3296	ns
RT Arabic	recent news headlines	0.6009	ns
RT Arabic	us russia ukraine sanctions	0.7268	ns
RT DE	bitcoin cryptocurrency value	0.9770	ns
RT DE	city crisis protest and disaster	0.9997	ns
RT DE	covid pandemic and related issues	0.8335	ns
RT DE	middle east wars and conflict	0.5807	ns
RT DE	recent news headlines	0.0045	p<0.01**
RT DE	us russia ukraine sanctions	0.3545	ns
RT France	bitcoin cryptocurrency value	0.8336	ns
RT France	city crisis protest and disaster	0.5322	ns
RT France	covid pandemic and related issues	0.3921	ns
RT France	middle east wars and conflict	0.7414	ns
RT France	recent news headlines	0.3526	ns
RT France	us russia ukraine sanctions	0.1084	ns
RT en Espanol	bitcoin cryptocurrency value	0.9376	ns
RT en Espanol	city crisis protest and disaster	0.6178	ns
RT en Espanol	covid pandemic and related issues	0.9696	ns
RT en Espanol	middle east wars and conflict	0.5960	ns
RT en Espanol	recent news headlines	0.8729	ns
RT en Espanol	us russia ukraine sanctions	0.5417	ns
RT UK	bitcoin cryptocurrency value	0.9159	ns
RT UK	city crisis protest and disaster	0.8253	ns
RT UK	covid pandemic and related issues	0.4607	ns
RT UK	middle east wars and conflict	0.8635	ns
RT UK	recent news headlines	0.9462	ns
RT UK	us russia ukraine sanctions	0.9784	ns

PostHoc TestsJohansen test for co-integration

\keepXColumns

Page	Topic	P Value
RT	bitcoin cryptocurrency value	0.01000000
RT	city crisis protest and disaster	0.01000000
RT	covid pandemic and related issues	0.01000000
RT	middle east wars and conflict	0.01000000
RT	recent news headlines	0.01000000
RT	us russia ukraine sanctions	0.01000000
RT America	bitcoin cryptocurrency value	0.01000000
RT America	city crisis protest and disaster	0.01000000
RT America	covid pandemic and related issues	0.08886854
RT America	middle east wars and conflict	0.01000000
RT America	recent news headlines	0.01000000
RT America	us russia ukraine sanctions	0.01000000
RT Arabic	bitcoin cryptocurrency value	0.01000000
RT Arabic	city crisis protest and disaster	0.01000000
RT Arabic	covid pandemic and related issues	0.01000000
RT Arabic	middle east wars and conflict	0.01000000
RT Arabic	recent news headlines	0.01000000
RT Arabic	us russia ukraine sanctions	0.01000000
RT DE	bitcoin cryptocurrency value	0.01000000
RT DE	city crisis protest and disaster	0.01000000
RT DE	covid pandemic and related issues	0.01000000
RT DE	middle east wars and conflict	0.01000000
RT DE	recent news headlines	0.01000000
RT DE	us russia ukraine sanctions	0.01000000
RT France	bitcoin cryptocurrency value	0.01000000
RT France	city crisis protest and disaster	0.01000000
RT France	covid pandemic and related issues	0.01000000
RT France	middle east wars and conflict	0.01000000
RT France	recent news headlines	0.01000000
RT France	us russia ukraine sanctions	0.01000000
RT en Espanol	bitcoin cryptocurrency value	0.01000000
RT en Espanol	city crisis protest and disaster	0.01000000
RT en Espanol	covid pandemic and related issues	0.01000000
RT en Espanol	middle east wars and conflict	0.01000000
RT en Espanol	recent news headlines	0.01000000
RT en Espanol	us russia ukraine sanctions	0.01000000
RT UK	bitcoin cryptocurrency value	0.01000000
RT UK	city crisis protest and disaster	0.01000000
RT UK	covid pandemic and related issues	0.01000000
RT UK	middle east wars and conflict	0.01000000
RT UK	recent news headlines	0.01000000
RT UK	us russia ukraine sanctions	0.01000000
Note: p-value (rejection criteria $p<0.05$

Ljung-Box Test

\keepXColumns

Page	Topic	P Value DV	P Value Ruble
RT	bitcoin cryptocurrency value	0.510	0.898
RT	city crisis protest and disaster	0.106	0.945
RT	covid pandemic and related issues	0.875	0.903
RT	middle east wars and conflict	0.228	0.956
RT	recent news headlines	0.469	0.983
RT	us russia ukraine sanctions	0.595	0.913
RT America	bitcoin cryptocurrency value	0.206	0.918
RT America	city crisis protest and disaster	0.793	0.859
RT America	covid pandemic and related issues	0.764	0.416
RT America	middle east wars and conflict	0.768	0.780
RT America	recent news headlines	0.444	0.721
RT America	us russia ukraine sanctions	0.970	0.927
RT Arabic	bitcoin cryptocurrency value	0.468	0.985
RT Arabic	city crisis protest and disaster	0.702	0.911
RT Arabic	covid pandemic and related issues	0.221	0.960
RT Arabic	middle east wars and conflict	0.754	0.953
RT Arabic	recent news headlines	0.898	0.998
RT Arabic	us russia ukraine sanctions	0.273	0.926
RT DE	bitcoin cryptocurrency value	0.342	0.972
RT DE	city crisis protest and disaster	0.660	0.945
RT DE	covid pandemic and related issues	0.944	0.622
RT DE	middle east wars and conflict	0.266	0.974
RT DE	recent news headlines	0.035	0.883
RT DE	us russia ukraine sanctions	0.080	0.856
RT France	bitcoin cryptocurrency value	0.048	0.953
RT France	city crisis protest and disaster	0.081	0.993
RT France	covid pandemic and related issues	0.706	0.753
RT France	middle east wars and conflict	0.908	0.949
RT France	recent news headlines	0.614	0.826
RT France	us russia ukraine sanctions	0.442	0.577
RT en Espanol	bitcoin cryptocurrency value	0.451	0.986
RT en Espanol	city crisis protest and disaster	0.277	0.996
RT en Espanol	covid pandemic and related issues	0.969	0.959
RT en Espanol	middle east wars and conflict	0.347	0.964
RT en Espanol	recent news headlines	0.353	0.994
RT en Espanol	us russia ukraine sanctions	0.623	0.952
RT UK	bitcoin cryptocurrency value	0.508	0.621
RT UK	city crisis protest and disaster	0.590	0.837
RT UK	covid pandemic and related issues	0.659	0.622
RT UK	middle east wars and conflict	0.431	0.625
RT UK	recent news headlines	0.158	0.322
RT UK	us russia ukraine sanctions	0.520	0.381

S6.3.3 Model: Ural Oil Prices

ADF Values

Page	Topic	P_Value
RT	bitcoin cryptocurrency value	0.010
RT	city crisis protest and disaster	0.010
RT	covid pandemic and related issues	0.010
RT	middle east wars and conflict	0.010
RT	recent news headlines	0.010
RT	us russia ukraine sanctions	0.010
RT America	bitcoin cryptocurrency value	0.010
RT America	city crisis protest and disaster	0.010
RT America	covid pandemic and related issues	0.018
RT America	middle east wars and conflict	0.010
RT America	recent news headlines	0.010
RT America	us russia ukraine sanctions	0.010
RT Arabic	bitcoin cryptocurrency value	0.010
RT Arabic	city crisis protest and disaster	0.010
RT Arabic	covid pandemic and related issues	0.010
RT Arabic	middle east wars and conflict	0.010
RT Arabic	recent news headlines	0.010
RT Arabic	us russia ukraine sanctions	0.010
RT DE	bitcoin cryptocurrency value	0.010
RT DE	city crisis protest and disaster	0.010
RT DE	covid pandemic and related issues	0.010
RT DE	middle east wars and conflict	0.010
RT DE	recent news headlines	0.010
RT DE	us russia ukraine sanctions	0.010
RT France	bitcoin cryptocurrency value	0.010
RT France	city crisis protest and disaster	0.010
RT France	covid pandemic and related issues	0.010
RT France	middle east wars and conflict	0.010
RT France	recent news headlines	0.010
RT France	us russia ukraine sanctions	0.010
RT en Espanol	bitcoin cryptocurrency value	0.010
RT en Espanol	city crisis protest and disaster	0.010
RT en Espanol	covid pandemic and related issues	0.010
RT en Espanol	middle east wars and conflict	0.010
RT en Espanol	recent news headlines	0.010
RT en Espanol	us russia ukraine sanctions	0.010
RT UK	bitcoin cryptocurrency value	0.010
RT UK	city crisis protest and disaster	0.010
RT UK	covid pandemic and related issues	0.010
RT UK	middle east wars and conflict	0.010
RT UK	recent news headlines	0.010
RT UK	us russia ukraine sanctions	0.010

SC Lag Values

Page	Topic	SC_Value
RT	bitcoin cryptocurrency value	1
RT	city crisis protest and disaster	1
RT	covid pandemic and related issues	1
RT	middle east wars and conflict	1
RT	recent news headlines	1
RT	us russia ukraine sanctions	1
RT America	bitcoin cryptocurrency value	2
RT America	city crisis protest and disaster	2
RT America	covid pandemic and related issues	2
RT America	middle east wars and conflict	2
RT America	recent news headlines	2
RT America	us russia ukraine sanctions	2
RT Arabic	bitcoin cryptocurrency value	1
RT Arabic	city crisis protest and disaster	1
RT Arabic	covid pandemic and related issues	1
RT Arabic	middle east wars and conflict	1
RT Arabic	recent news headlines	1
RT Arabic	us russia ukraine sanctions	1
RT DE	bitcoin cryptocurrency value	1
RT DE	city crisis protest and disaster	1
RT DE	covid pandemic and related issues	1
RT DE	middle east wars and conflict	1
RT DE	recent news headlines	1
RT DE	us russia ukraine sanctions	1
RT France	bitcoin cryptocurrency value	1
RT France	city crisis protest and disaster	1
RT France	covid pandemic and related issues	1
RT France	middle east wars and conflict	1
RT France	recent news headlines	1
RT France	us russia ukraine sanctions	1
RT en Espanol	bitcoin cryptocurrency value	1
RT en Espanol	city crisis protest and disaster	1
RT en Espanol	covid pandemic and related issues	1
RT en Espanol	middle east wars and conflict	1
RT en Espanol	recent news headlines	1
RT en Espanol	us russia ukraine sanctions	1
RT UK	bitcoin cryptocurrency value	1
RT UK	city crisis protest and disaster	1
RT UK	covid pandemic and related issues	1
RT UK	middle east wars and conflict	1
RT UK	recent news headlines	1
RT UK	us russia ukraine sanctions	1

VAR Results

	RT bitcoin cryptocurrency value	RT city crisis protest and disaster	RT covid pandemic and related issues	RT middle east wars and conflict	RT recent news headlines	RT us russia ukraine sanctions
Ural Oil Price (-1)	$0.001$ $(0.045)$	$-0.054$ $(0.104)$	$-0.163^{*}$ $(0.063)$	$0.014$ $(0.133)$	$-0.006$ $(0.199)$	$0.383^{*}$ $(0.186)$
Interruption 1 (Covid-19)	$0.207$ $(0.891)$	$0.070$ $(2.061)$	$-0.807$ $(1.158)$	$-0.356$ $(2.599)$	$4.882$ $(3.885)$	$7.716^{*}$ $(3.719)$
Interruption 2 (Russia-Ukraine)	$0.263$ $(1.630)$	$-0.679$ $(3.762)$	$-2.413$ $(2.127)$	$-0.526$ $(4.755)$	$10.598$ $(7.105)$	$15.260^{*}$ $(6.815)$
Constant	$0.097$ $(0.880)$	$-0.127$ $(2.024)$	$-0.284$ $(1.144)$	$0.239$ $(2.568)$	$3.063$ $(3.829)$	$2.660$ $(3.617)$
Trend	$-0.010$ $(0.044)$	$0.023$ $(0.101)$	$0.047$ $(0.057)$	$0.004$ $(0.127)$	$-0.284$ $(0.191)$	$-0.348^{+}$ $(0.181)$
Num.Obs.	58	58	58	58	58	58
$R^{2}$	0.027	0.288	0.139	0.187	0.143	0.177
$R^{2}$ Adj.	$-0.066$	0.220	0.056	0.108	0.061	0.098
${}^{+}p<0.10$, * $p<0.05$, ** $p<0.01$, *** $p<0.001$

	RT Arabic bitcoin cryptocurrency value	RT Arabic city crisis protest and disaster	RT Arabic covid pandemic and related issues	RT Arabic middle east wars and conflict	RT Arabic recent news headlines	RT Arabic US Russia Ukraine sanctions
Ural Oil Price (-1)	$-0.016$ $(0.016)$	$-0.004$ $(0.007)$	$-0.014^{*}$ $(0.007)$	$0.001$ $(0.005)$	$0.144$ $(0.155)$	$-0.310$ $(0.431)$
Interruption 1 (Covid-19)	$0.065$ $(0.311)$	$0.016$ $(0.129)$	$-0.004$ $(0.133)$	$0.019$ $(0.106)$	$-1.600$ $(3.063)$	$-3.146$ $(8.501)$
Interruption 2 (Russia-Ukraine)	$0.164$ $(0.570)$	$0.031$ $(0.236)$	$-0.012$ $(0.243)$	$0.060$ $(0.194)$	$1.722$ $(5.593)$	$0.442$ $(15.444)$
Constant	$-0.255$ $(0.308)$	$-0.001$ $(0.128)$	$-0.030$ $(0.132)$	$0.028$ $(0.105)$	$-0.918$ $(3.031)$	$-1.391$ $(8.352)$
Trend	$0.009$ $(0.015)$	$-0.001$ $(0.006)$	$0.001$ $(0.007)$	$-0.002$ $(0.005)$	$0.075$ $(0.151)$	$0.150$ $(0.416)$
Num.Obs.	58	58	58	58	58	58
$R^{2}$	0.179	0.022	0.404	0.114	0.082	0.160
$R^{2}$ Adj.	0.100	$-0.072$	0.346	0.029	$-0.007$	0.080
${}^{+}p<0.10$, * $p<0.05$, ** $p<0.01$, *** $p<0.001$

	RT America bitcoin cryptocurrency value	RT America city crisis protest and disaster	RT America covid pandemic and related issues	RT America middle east wars and conflict	RT America recent news headlines	RT America US Russia Ukraine sanctions
Ural Oil Price (-1)	$0.028$ $(0.024)$	$0.006$ $(0.010)$	$-0.034$ $(0.082)$	$-0.001$ $(0.017)$	$0.006$ $(0.086)$	$0.094$ $(0.074)$
Ural Oil Price (-2)	$0.019$ $(0.024)$	$0.009$ $(0.010)$	$0.036$ $(0.076)$	$0.002$ $(0.017)$	$0.011$ $(0.087)$	$-0.008$ $(0.075)$
Interruption 1 (Covid-19)	$-0.008$ $(0.791)$	$0.258$ $(0.320)$	$0.481$ $(2.321)$	$0.516$ $(0.542)$	$1.837$ $(2.849)$	$2.357$ $(2.369)$
Interruption 2 (Russia-Ukraine)	$0.094$ $(1.360)$	$0.738$ $(0.531)$	$0.359$ $(3.828)$	$0.528$ $(0.902)$	$-1.570$ $(4.711)$	$3.053$ $(3.914)$
Constant	$0.151$ $(0.532)$	$0.079$ $(0.221)$	$0.685$ $(1.589)$	$0.047$ $(0.375)$	$-2.086$ $(1.954)$	$-0.009$ $(1.632)$
Trend	$-0.009$ $(0.038)$	$-0.014$ $(0.015)$	$-0.045$ $(0.112)$	$-0.020$ $(0.026)$	$-0.004$ $(0.138)$	$-0.104$ $(0.114)$
Num.Obs.	40	40	40	40	40	40
$R^{2}$	0.344	0.568	0.236	0.388	0.488	0.213
$R^{2}$ Adj.	0.201	0.473	0.069	0.254	0.376	0.041
${}^{+}p<0.10$, * $p<0.05$, ** $p<0.01$, *** $p<0.001$

	RT DE bitcoin cryptocurrency value	RT DE city crisis protest and disaster	RT DE covid pandemic and related issues	RT DE middle east wars and conflict	RT DE recent news headlines	RT DE US Russia Ukraine sanctions
Ural Oil Price (-1)	$-0.026^{*}$ $(0.012)$	$-0.006$ $(0.012)$	$-0.153^{***}$ $(0.040)$	$0.008$ $(0.028)$	$0.176$ $(0.164)$	$0.042$ $(0.140)$
Interruption 1 (Covid-19)	$0.052$ $(0.234)$	$-0.097$ $(0.223)$	$-1.074$ $(0.763)$	$-0.235$ $(0.556)$	$3.133$ $(3.221)$	$4.729$ $(2.823)$
Interruption 2 (Russia-Ukraine)	$-0.356$ $(0.428)$	$-0.366$ $(0.409)$	$-4.913^{**}$ $(1.411)$	$-0.680$ $(1.017)$	$1.121$ $(5.891)$	$6.701$ $(5.055)$
Constant	$-0.134$ $(0.229)$	$-0.087$ $(0.221)$	$-1.134$ $(0.755)$	$-0.052$ $(0.549)$	$0.047$ $(3.182)$	$0.551$ $(2.678)$
Trend	$0.007$ $(0.011)$	$0.008$ $(0.011)$	$0.107^{**}$ $(0.038)$	$0.013$ $(0.027)$	$-0.053$ $(0.158)$	$-0.146$ $(0.135)$
Num.Obs.	58	58	58	58	58	58
$R^{2}$	0.252	0.166	0.392	0.143	0.227	0.190
$R^{2}$ Adj.	0.180	0.086	0.334	0.061	0.152	0.113
${}^{+}p<0.10$, * $p<0.05$, ** $p<0.01$, *** $p<0.001$

	RT FR bitcoin cryptocurrency value	RT FR city crisis protest and disaster	RT FR covid pandemic and related issues	RT FR middle east wars and conflict	RT FR recent news headlines	RT FR US Russia Ukraine sanctions
Ural Oil Price (-1)	$-0.021$ $(0.020)$	$0.028$ $(0.041)$	$-0.459$ $(0.386)$	$0.028$ $(0.112)$	$-1.226$ $(0.802)$	$0.551$ $(0.422)$
Interruption 1 (Covid-19)	$-0.239$ $(0.393)$	$-0.288$ $(0.818)$	$-11.932$ $(7.404)$	$-0.039$ $(2.165)$	$-9.582$ $(15.790)$	$3.135$ $(8.310)$
Interruption 2 (Russia-Ukraine)	$-0.835$ $(0.719)$	$0.127$ $(1.485)$	$-36.996^{*}$ $(14.239)$	$0.195$ $(3.965)$	$-20.719$ $(28.823)$	$3.556$ $(15.210)$
Constant	$-0.158$ $(0.388)$	$0.449$ $(0.793)$	$-6.120$ $(7.241)$	$0.352$ $(2.139)$	$5.613$ $(15.594)$	$3.107$ $(8.210)$
Trend	$0.018$ $(0.019)$	$-0.011$ $(0.040)$	$0.783^{*}$ $(0.372)$	$-0.013$ $(0.106)$	$0.161$ $(0.770)$	$-0.179$ $(0.407)$
Num.Obs.	58	58	58	58	58	58
$R^{2}$	0.301	0.234	0.138	0.004	0.114	0.181
$R^{2}$ Adj.	0.233	0.161	0.056	$-0.092$	0.029	0.102
${}^{+}p<0.10$, * $p<0.05$, ** $p<0.01$, *** $p<0.001$

	RT SP bitcoin cryptocurrency value	RT SP city crisis protest and disaster	RT SP covid pandemic and related issues	RT SP middle east wars and conflict	RT SP recent news headlines	RT SP US Russia Ukraine sanctions
Ural Oil Price (-1)	$-0.169$ $(0.172)$	$0.111$ $(0.193)$	$-0.168$ $(0.257)$	$0.019$ $(0.152)$	$-0.789$ $(0.578)$	$1.512^{*}$ $(0.654)$
Interruption 1 (Covid-19)	$-1.253$ $(3.386)$	$-2.741$ $(3.764)$	$-0.678$ $(4.550)$	$0.111$ $(2.967)$	$-10.371$ $(11.300)$	$5.734$ $(12.716)$
Interruption 2 (Russia-Ukraine)	$-7.724$ $(6.261)$	$0.373$ $(6.853)$	$0.040$ $(8.315)$	$0.742$ $(5.429)$	$-4.468$ $(20.663)$	$20.141$ $(23.347)$
Constant	$-1.402$ $(3.348)$	$2.071$ $(3.712)$	$1.156$ $(4.489)$	$0.461$ $(2.932)$	$5.232$ $(11.184)$	$7.117$ $(12.546)$
Trend	$0.153$ $(0.167)$	$-0.006$ $(0.184)$	$-0.028$ $(0.223)$	$-0.024$ $(0.145)$	$0.128$ $(0.553)$	$-0.458$ $(0.624)$
Num.Obs.	58	58	58	58	58	58
$R^{2}$	0.102	0.227	0.022	0.187	0.265	0.140
$R^{2}$ Adj.	0.015	0.152	$-0.072$	0.108	0.194	0.057
${}^{+}p<0.10$, * $p<0.05$, ** $p<0.01$, *** $p<0.001$

	RT UK bitcoin cryptocurrency value	RT UK city crisis protest and disaster	RT UK covid pandemic and related issues	RT UK middle east wars and conflict	RT UK recent news headlines	RT UK US Russia Ukraine sanctions
Ural Oil Price (-1)	$-0.028$ $(0.018)$	$0.014$ $(0.020)$	$-0.061$ $(0.038)$	$-0.004$ $(0.018)$	$-0.031$ $(0.101)$	$0.193^{+}$ $(0.108)$
Interruption 1 (Covid-19)	$-0.337$ $(0.369)$	$0.108$ $(0.422)$	$0.074$ $(0.747)$	$0.018$ $(0.382)$	$0.844$ $(2.150)$	$1.430$ $(2.439)$
Interruption 2 (Russia-Ukraine)	$-1.144^{+}$ $(0.613)$	$0.331$ $(0.702)$	$-0.129$ $(1.234)$	$-0.016$ $(0.637)$	$2.321$ $(3.596)$	$2.303$ $(3.969)$
Constant	$-0.316$ $(0.303)$	$0.162$ $(0.346)$	$0.085$ $(0.609)$	$0.024$ $(0.313)$	$1.188$ $(1.777)$	$0.731$ $(1.899)$
Trend	$0.027$ $(0.017)$	$-0.011$ $(0.020)$	$-0.005$ $(0.035)$	$-0.001$ $(0.018)$	$-0.098$ $(0.103)$	$-0.072$ $(0.113)$
Num.Obs.	51	51	51	51	51	51
$R^{2}$	0.276	0.140	0.089	0.172	0.261	0.163
$R^{2}$ Adj.	0.196	0.044	$-0.012$	0.080	0.179	0.069
${}^{+}p<0.10$, * $p<0.05$, ** $p<0.01$, *** $p<0.001$

Granger Causality Results

\keepXColumns

Page	Topic	GC.P.Value	Significance
RT	bitcoin cryptocurrency value	0.9851	ns
RT	city crisis protest and disaster	0.6083	ns
RT	covid pandemic and related issues	0.0107	p<0.05*
RT	middle east wars and conflict	0.9136	ns
RT	recent news headlines	0.9768	ns
RT	us russia ukraine sanctions	0.0418	p<0.05*
RT America	bitcoin cryptocurrency value	0.3634	ns
RT America	city crisis protest and disaster	0.5109	ns
RT America	covid pandemic and related issues	0.8058	ns
RT America	middle east wars and conflict	0.9924	ns
RT America	recent news headlines	0.9883	ns
RT America	us russia ukraine sanctions	0.4451	ns
RT Arabic	bitcoin cryptocurrency value	0.3084	ns
RT Arabic	city crisis protest and disaster	0.5873	ns
RT Arabic	covid pandemic and related issues	0.0383	p<0.05*
RT Arabic	middle east wars and conflict	0.8399	ns
RT Arabic	recent news headlines	0.3549	ns
RT Arabic	us russia ukraine sanctions	0.4731	ns
RT DE	bitcoin cryptocurrency value	0.0318	p<0.05*
RT DE	city crisis protest and disaster	0.5845	ns
RT DE	covid pandemic and related issues	0.0002	p<0.001***
RT DE	middle east wars and conflict	0.7667	ns
RT DE	recent news headlines	0.2845	ns
RT DE	us russia ukraine sanctions	0.7621	ns
RT France	bitcoin cryptocurrency value	0.3012	ns
RT France	city crisis protest and disaster	0.4957	ns
RT France	covid pandemic and related issues	0.2375	ns
RT France	middle east wars and conflict	0.8043	ns
RT France	recent news headlines	0.1294	ns
RT France	us russia ukraine sanctions	0.1949	ns
RT en Espanol	bitcoin cryptocurrency value	0.3274	ns
RT en Espanol	city crisis protest and disaster	0.5670	ns
RT en Espanol	covid pandemic and related issues	0.5137	ns
RT en Espanol	middle east wars and conflict	0.9020	ns
RT en Espanol	recent news headlines	0.1751	ns
RT en Espanol	us russia ukraine sanctions	0.0228	p<0.05*
RT UK	bitcoin cryptocurrency value	0.1177	ns
RT UK	city crisis protest and disaster	0.4664	ns
RT UK	covid pandemic and related issues	0.1155	ns
RT UK	middle east wars and conflict	0.8324	ns
RT UK	recent news headlines	0.7618	ns
RT UK	us russia ukraine sanctions	0.0789	ns

PostHoc TestsJohansen test for co-integration

\keepXColumns

Page	Topic	P Value
RT	bitcoin cryptocurrency value	0.01000000
RT	city crisis protest and disaster	0.01000000
RT	covid pandemic and related issues	0.01000000
RT	middle east wars and conflict	0.01000000
RT	recent news headlines	0.01000000
RT	us russia ukraine sanctions	0.01000000
RT America	bitcoin cryptocurrency value	0.01000000
RT America	city crisis protest and disaster	0.01000000
RT America	covid pandemic and related issues	0.01517434
RT America	middle east wars and conflict	0.01000000
RT America	recent news headlines	0.01000000
RT America	us russia ukraine sanctions	0.01113057
RT Arabic	bitcoin cryptocurrency value	0.01000000
RT Arabic	city crisis protest and disaster	0.01000000
RT Arabic	covid pandemic and related issues	0.01000000
RT Arabic	middle east wars and conflict	0.01000000
RT Arabic	recent news headlines	0.01000000
RT Arabic	us russia ukraine sanctions	0.01000000
RT DE	bitcoin cryptocurrency value	0.01000000
RT DE	city crisis protest and disaster	0.01000000
RT DE	covid pandemic and related issues	0.01000000
RT DE	middle east wars and conflict	0.01000000
RT DE	recent news headlines	0.01000000
RT DE	us russia ukraine sanctions	0.01000000
RT France	bitcoin cryptocurrency value	0.01000000
RT France	city crisis protest and disaster	0.01000000
RT France	covid pandemic and related issues	0.01000000
RT France	middle east wars and conflict	0.01000000
RT France	recent news headlines	0.01000000
RT France	us russia ukraine sanctions	0.01000000
RT en Espanol	bitcoin cryptocurrency value	0.01000000
RT en Espanol	city crisis protest and disaster	0.01000000
RT en Espanol	covid pandemic and related issues	0.01000000
RT en Espanol	middle east wars and conflict	0.01000000
RT en Espanol	recent news headlines	0.01000000
RT en Espanol	us russia ukraine sanctions	0.01000000
RT UK	bitcoin cryptocurrency value	0.01000000
RT UK	city crisis protest and disaster	0.01000000
RT UK	covid pandemic and related issues	0.01000000
RT UK	middle east wars and conflict	0.01000000
RT UK	recent news headlines	0.01000000
RT UK	us russia ukraine sanctions	0.01000000
Note: p-value (rejection criteria $p<0.05$

Ljung-Box Test

\keepXColumns

Page	Topic	P Value DV	P Value IV Ural Oil Prices
RT	bitcoin cryptocurrency value	0.525	0.487
RT	city crisis protest and disaster	0.148	0.492
RT	covid pandemic and related issues	0.770	0.515
RT	middle east wars and conflict	0.222	0.502
RT	recent news headlines	0.463	0.495
RT	us russia ukraine sanctions	0.813	0.455
RT America	bitcoin cryptocurrency value	0.561	0.883
RT America	city crisis protest and disaster	0.635	0.625
RT America	covid pandemic and related issues	0.662	0.621
RT America	middle east wars and conflict	0.703	0.581
RT America	recent news headlines	0.305	0.596
RT America	us russia ukraine sanctions	0.877	0.729
RT Arabic	bitcoin cryptocurrency value	0.321	0.576
RT Arabic	city crisis protest and disaster	0.728	0.801
RT Arabic	covid pandemic and related issues	0.193	0.576
RT Arabic	middle east wars and conflict	0.731	0.454
RT Arabic	recent news headlines	0.999	0.513
RT Arabic	us russia ukraine sanctions	0.225	0.516
RT DE	bitcoin cryptocurrency value	0.233	0.708
RT DE	city crisis protest and disaster	0.609	0.514
RT DE	covid pandemic and related issues	0.351	0.697
RT DE	middle east wars and conflict	0.322	0.455
RT DE	recent news headlines	0.343	0.474
RT DE	us russia ukraine sanctions	0.144	0.477
RT France	bitcoin cryptocurrency value	0.054	0.592
RT France	city crisis protest and disaster	0.083	0.457
RT France	covid pandemic and related issues	0.626	0.402
RT France	middle east wars and conflict	0.876	0.525
RT France	recent news headlines	0.372	0.436
RT France	us russia ukraine sanctions	0.444	0.342
RT en Espanol	bitcoin cryptocurrency value	0.393	0.519
RT en Espanol	city crisis protest and disaster	0.274	0.518
RT en Espanol	covid pandemic and related issues	0.917	0.460
RT en Espanol	middle east wars and conflict	0.339	0.508
RT en Espanol	recent news headlines	0.305	0.601
RT en Espanol	us russia ukraine sanctions	0.827	0.493
RT UK	bitcoin cryptocurrency value	0.409	0.409
RT UK	city crisis protest and disaster	0.708	0.422
RT UK	covid pandemic and related issues	0.657	0.430
RT UK	middle east wars and conflict	0.438	0.468
RT UK	recent news headlines	0.143	0.489
RT UK	us russia ukraine sanctions	0.520	0.413