Global health crisis

"We have concluded that COVID-19 can be considered a pandemic" (WHO, 2020). With this statement, the World Health Organization announced, on March 11^th, 2020, that the COVID-19 virus was declared a pandemic, after detecting more than 118,000 cases in 114 countries, and 4,291 people dead from this disease.

The viral spread has reached all corners of the world, with great affection in Europe and America. The significance and effects of COVID-19 will be difficult to quantify even in the framework of an advanced society, dominated by algorithms and artificial intelligence ( ; Powers and Kounalakis 2017) (Hansen, Roca-Sales, Keegan, & King, 2017; Xifra, 2020) since the situation of social, health, political, and economic crisis has put scientific production systems to the test (Kupferschmidt, 2020).

The political context of the presidents selected for the study describes different actions against the pandemic. The initiation of treatment for the disease in the UK and the measures taken by Boris Johnson to reduce mortality and the scope of COVID-19 were questioned by the scientific community, in the 'Report: Impact of non-pharmaceutical interventions (NPIs)' ² . The prime minister maintained, at the beginning of the pandemic, that, in the absence of a vaccine, public health measures should be evaluated, known as non-pharmaceutical interventions (NPIs) that combine home isolation, quarantine, and social distancing, mainly of the elderly and people at risk, complemented with the closure of schools and universities.

In the United States, on March 13^th, two days after the WHO classified the COVID-19 outbreak as a pandemic, President Donald Trump proclaims a national emergency throughout the country, although he is committed to maintaining the economy in the face of the spread of the disease.

Communication in alarm period of COVID-19

During the spread of the COVID-19 pandemic, we witnessed an overexposure of political information (Castillo-Esparcia, Fernández-Souto, & Puentes-Rivera, 2020) derived from the multiple public appearances of the leaders, given the need to explain to the public what is happening. This self-advertising implies risks for the image of the lead representatives, caused by the ignorance of this situation and the consequences of the implemented strategy. In this sense, communication becomes an important ally of political, social, institutional, and health management (Costa-Sánchez & López-García, 2020).

At a time when government agencies focus their efforts on fighting the disease, information professionals must play a relevant role to stop the spread of misinformation related to the pandemic (Tandoc, 2020), producing, according to the experts, massive growth of fact-checks ³ due to COVID-19 (Brennen, Simón, Howard, & Nielsen, 2020), using these communication channels as sources of information about the pandemic (Ramírez, Travesedo, Rojas, & Martínez, 2020). The implosion of a critical and risky situation for the world population, such as that caused by COVID-19, linked to levels of maximum insecurity and uncertainty, triggers the rates of fake news and hoaxes on the networks (Pérez-Dasilva, Meso-Ayerdi, & Mendiguren-Galdospín, 2020). It even leads to an activation of institutional messages about the coronavirus, often unproven, which become a breeding ground for anonymized users of the network (Pérez-Curiel & Velasco-Molpeceres, 2020).

Populism and political context

The so-called Populism 2.0 (Gerbaudo, 2014) is installed as a communication strategy of some leaders to spread and viralize the message, saving the difficulty of access that they find in conventional media (Groshek & Engelbert, 2013; Shoemaker & Vos, 2009) controlled by the elites (Van-Kessel; Castelein, 2016).

A report published by The Guardian (2019), on a sample of 40 countries, finds that the number of populist leaders has doubled in the 21^st century. Specifically, in Europe, social polarization and the refugee crisis have been a catalyst for right-wing populists and the transformation of non-populist parties into populist parties (Mudde, 2016). The ultra-right populist discourse is installed in the media and social networks and achieves unprecedented electoral results (Alonso-Muñoz and Casero-Ripollés, 2019) (Bosch; Brunet; Rosiñol, 2017). The Guardian's analysis shows how populists tripled in number between 1998 and 2018, garnering enough votes to put their leaders in government positions in 11 countries.

The Republican Party, led by Trump, won the 2016 elections, reaching 47.3% of the votes that represented 60,541,308 voters and 306 seats, surpassing the 232 won by Hillary Clinton. During this campaign, a study by the University of Southern California (Bessi & Ferrara, 2016) analyzed 20 million tweets generated between September 16^th and October 21^st and written by some 2.8 million users. It is found that approximately 400,000 publications were bots (19%) distorting the debate on Twitter, the vast majority in favor of Trump.

This last theory, of the situation that led to Trump's triumph in 2016, is supported by different studies, such as those obtained by researchers from Oxford University, led by Philip Howard, who followed up on more than 19 million tweets between November 1^st and 9^th, as well as by the Center for Journalist Studies, which came to count that 80% of the activity on Twitter, in favor of Trump, was generated by these bots (Hermida, 2016).

Johnson, on the European side, made use of bots, used as a strategy to influence English citizens. The link with the analysis company ‘Cambridge Analytica’ ⁴ , a company accused of stealing data from Facebook users without their consent or knowledge of its use; or the indications of relations with Russia and its interference in the viral Brexit strategy, are elements to be studied and determined, according to the statements of Brittany Kaiser in the documentary 'The Great Hack' ⁵ and in the monitoring committee that was carried out in the English parliament.

The right-wing or conservative parties worldwide are facing ideological shifts towards “the right of their rights”. In recent years, new parties of extreme ideology have appeared (Acha, 2017) to occupy that space based on socioeconomic, psychological, political, or international factors (Ebata, 1997) that are no longer represented by the established parties. They define a charismatic leader, with a simple language, typical of ordinary people, who conveys a message with a strong ideological and emotional charge (Taggart, 2020). The leaders establish a demonstrated demagoguery, which evolves into ochlocracy ⁶ , the concept being understood as the consequence of a demagogic action, which occurs in the worst of political systems and the last iota of degeneration of power. Demagoguery and populism of the crowd represented in a political figure, in front of the people as a power of governance. Leaders who are in charge of establishing themselves as representatives of a whole, when they hardly do so for minorities, without ever actually being the government of a people (Mackintosh, 1791).

Besides the actions that they undertake in their governance, the leaders of the far-right parties focus their attention on the electoral campaign and social networks as an engine of influence (Orozco, 2021) and viralization (Dader & Campos-Domínguez, 2017; López-García, 2016), using policies to delegitimize the electoral process and populist messages (Pérez-Curiel et al., 2021).

Politics influencers Causal factor of misinformation

The digital revolution in the 21^st century has multiplied, in social networks, the degree of influence of politicians, as well as their conscious capacity to produce disinformation, based on professional use of fallacy and propaganda. The politics of post-truth is installed in which the manipulation of ignorance and the feelings or emotions of citizens are worth more than rational argumentation (Boczkowski, 2016; Urmeneta, 2017). In the digital context, the citizen is positioned in the role of receiver who offers immediate feedback, with the risks that this distortion implies for the intention of the speech. On the contrary, this digitization does favor the management of transparency, essential for new information aimed at citizens, through citizen platforms (Alonso-Muñoz & Casero-Ripollés, 2017).

The trend towards disinformation grows like a virus ( ; Román-San Miguel, Sánchez-Gey, & Elías, 2020; Elías, 2018) (Pérez-Curiel & Velasco-Molpeceres, 2020), with a dangerous power for democracy (Coughlan; ) (Valadier, 2017). The influence of populism (Pérez-Curiel & Velasco-Molpeceres, 2020) joins the distrust or apathy of citizens towards political parties or representatives or even towards other scourges such as corruption (Hernández-Santaolalla & Sola-Morales, 2019). In parallel, the digital revolution multiplies in social networks, especially in Twitter, the degree of impact of politicians over users and the configuration of the media agenda (Montoya & Vandehey, 2009; Pérez-Ortega, 2014; Rampersad, 2009). Along these lines,Krane (2010) publishes a work focused on the analysis of the content disseminated on Twitter by three media, The New York Times, CNN, and NPR, which reinforces the theory that there is a direct relationship between the content disseminated by the media and the topics that are most frequently addressed by users on the Internet.

After this analysis, the role of Donald Trump, as a political influencer in social networks, gains strength. The leader demonstrates the ability to mobilize opinions, generate reactions over different concrete elements, increase the audience and levels of participation, through the dynamization of a simple, brief, rhythmic, and almost syllabic language, aspects that disguise a discourse of domination, empowerment, and leadership (Pérez-Curiel and Limón-Naharro, 2019). Likewise, the advance of populism in Europe positions leaders as new digital influencers. We focus on Boris Johnson who, through Twitter, finds a stage for the dissemination, interaction, mobilization, and personalization of the candidate as a strategist, in the selection of topics, and the use of propaganda and fallacy (Bravo, 2020).

In the aforementioned sense, the published events go to the background and the politician is positioned as prominent, besides turning the publication into news, positioning it on social networks, and promoting viralization, using the resources of propaganda in speech ( ; Van Dijck, 2015) (Nocetti, 1990). At present, their activity in social networks is questioned more than their electoral program, their image as a leader, the ideology they represent, or the party they run, due to the polarization that confronts the left and the right in the international arena.

The populist discourse of the leaders on Twitter about COVID-19 generates a relevant amount of misinformation that affects the media agenda and public perception of the pandemic.

Quantification Block

After the prologue of general data on the politicians' accounts, we are going to establish the initial quantitative approach between the relationship of tweets, the interactions of users in the profiles of the analyzed characters, through likes, retweets, and comments, and the comparison between the researched periods.

In the first period, Donald Trump stands out at the head of Twitter publications with 82 posts, 35.36% more posts than the English leader. On the other hand, in the second period, it is observed that it is the English leader, Boris Johnson, who has used the social network more times.

Quantitative Analysis, publication interactivity on COVID-19

Source: self-made

Donal Trump shows the highest number of likes in both periods, with an advantage four times greater than his own retweets and six times greater than the likes obtained by Boris Johnson. This issue of metrics invites us to reflect on the interaction that Trump maintains with his followers since retweets generate visibility and favor the dissemination of the message. Trump is in retweets well below his percentage of likes, with the particularity that the retweet reaches the double value in the network, given the ability to make the original go viral and position itself on the timeline (Polaino, Cirujano, & Fuentes, 2018).

Regarding the number of fallacies detected, the highest percentage of false news is attributed to the American leader with 26.8% (P1) / 26% (P2) compared to the percentages achieved by the British Prime Minister with only 9.4% (P1) / 12.29% (P2).

Source: self-made

To finalize the quantitative analysis, the comparison between the variables of 'tag', a name that reflects the attack of both leaders on the opposition and/or the media, and 'attribution', merits referred to other sources or themselves, is made.

Source: self-made

The comparison in terms of attributions shows a higher number of self-attribution in both periods, mainly related to their ideological position.

Qualification Block

The topic where the greatest number of fallacies is located is the so-called "Actions carried out by the government" with a total of 17 fake news in the first period (14 Trump; 3 Johnson), as in P2 with a total of 13 fake news (12 Trump; 1 Johnson). The difference between Trump and Boris Johnson in this item lies in the high percentage of attacks that the president of the United States dedicates to the opposition and the media to justify his decisions on the pandemic.

Other topics in which fake news also appears, although to a lesser extent, are ‘virus affection’, ‘government statements’, ‘events with citizens’, and ‘proposed measures’.

Source: self-made

Another of the qualitative aspects discussed has to do with the tone of the message. The tone of communication on Twitter is informal. It is important to note that on some occasions the limitation of 280 characters can make it difficult to implement the appropriate communication tone (Mejías-Llanos, 2019).

The influence of the position that the conservative and the republican candidates occupy as leaders of each country, shows the percentage of positive messages that they accumulate in the two periods. In both analyzes, the positive comments outnumber the negative ones by doubling the amount. Trump reaches 61 messages in (P1) / 31 (P2) messages with a positive tone, compared to 21 (P1) / 19 (P2) negative. For his part, Johnson registers 37 (P1) / 36 (P2) positive compared to 16 (P1) / 21 (P2) negative. The need to encourage citizens in times of a pandemic is proven.

Source: self-made

Finally, in the analysis of this approach, the impact that these leaders' tweets have on the media is considered. The number of analyzed tweets that have been news in the media and that have appeared in any format, modifying or marking the agenda-setting, is listed.

The results reveal that the majority of Trump's tweets have been seconded with 67.9 (P1) / 68 (P2) by the media, with a total of 55 (P1) / 34 (P2) tweets published in different communication companies, either in its traditional or digital version.

Source: self-made

Likewise, we evaluate Johnson's influence on the media, in the two studied periods. In this case, 41 publications (P1) / 35 (P2) were projected in the media, exceeding, in the first period, the coverage that the media has dedicated to the American tycoon.

Source: self-made

Discursiveness Block

The discursive approach attends to consider the act of language, on the one hand, as an act of enunciation, of titling, attending to the active role of the subjects who intervene in the discourse, and, on the other hand, as an act of textualization that results in the construction of a text. A discursive approach consists of forming activity of construction of representations between the interlocutors and the referential world (Álvarez, 2006).

The discursive paradigm is resolved in the study attending to the appeals related to emotion, ignorance, and authority, which the messages published by both leaders contain.

Source: self-made

We see in graph P1 that the demand for emotion is, par excellence, the most recurrent appeal of the leaders in social networks. In this first analyzed period, Trump appeals to these feelings in 71.95% of his publications. These data differ with Johnson's interference, which regarding emotion is lighter, with 64.15%, although it continues to exceed half of the issued posts.

Graph 5 .

Source: self-made

In P2, emotion is still one of the most used appeals in publications, although it is positioned behind ‘authority’. The variable 'authority' occupies first place in the ranking. Along with this evolution, it is Boris Johnson who overtakes the American leader to place himself in the main position. He accumulates a total of 45 references attributed to his position as ruler (78.94%) compared to those reached by Trump (72%).

Finally, the appeal to ignorance is a less used resource by the leaders in both periods. In this sense, Trump uses 15.85% (P1) / 18.75% (P2) of his digital interventions to appeal to the ignorance of some users on specific issues. Faced with these data, the British leader gives less prominence to this appeal with 1.89% (P1) / 1.75% (P2) of the published tweets.