Research Articles

Understanding Viral Communism: A Thematic Analysis of Twitter During Brazil’s 2018 Elections

Authors: Helton Levy (John Cabot University) , Claudia Sarmento (University of Westminster)

  • Understanding Viral Communism: A Thematic Analysis of Twitter During Brazil’s 2018 Elections

    Research Articles

    Understanding Viral Communism: A Thematic Analysis of Twitter During Brazil’s 2018 Elections

    Authors: ,

Abstract

This research performs a thematic analysis on tweets published during Brazil’s 2018 elections that mentioned communism. The idea was to identify the linkages to other underlying themes that emerged during what we saw as the Twitter ‘virality of communism’ and interpret them considering the backdrop of anti-communist discourses in the country. The results show that political polarisation, distrust of democracy, criticism of the left and praise of militarism and religion are the most recurrent themes. We conclude by situating the virality of the term ‘communism’ as a process that follows a context of disinformation and hopelessness, but which also relates to the legitimate concerns of Brazilian voters.

Keywords: right-wing, anti-communism, elections, Brazil, Twitter, virality

How to Cite:

Levy, H. & Sarmento, C., (2020) “Understanding Viral Communism: A Thematic Analysis of Twitter During Brazil’s 2018 Elections”, Westminster Papers in Communication and Culture 15(1), 19–36. doi: https://doi.org/10.16997/wpcc.322

3787 Views

756 Downloads

2Citations

Published on
17 Mar 2020
Peer Reviewed

Introduction

During Brazil’s 2018 presidential elections, the campaign of the right-wing candidate Jair Bolsonaro invested in social media posts, apocryphal messages sent to WhatsApp groups and direct attacks on other political runners (Oliveira, 2018; Machado et al., 2018). His campaign raised awareness of the supposed ‘menace’ that communism posed to the country (Charleaux and Corsalette, 2018). This anti-communist rhetoric later became viral on social media. In one of these cases, an online montage included Che Guevara with red lips. The right-wing commentator Olavo de Carvalho had used the clip in one of his internet lectures, on the theme of ‘being gay and communist’. During a TV debate, the evangelical candidate Cabo Daciolo had mentioned the possibility of Brazil joining the URSAL, a mythical union of socialist republics, that led to many ‘tweetstorms’ (Chagas et al., 2019). A video denouncing a communist plot to corrupt the elections reached 1.3 million views on YouTube (Mota, Couta and Rocha, 2018).

These series of viral memes and absurdity on social media have obfuscated the broader and continuous use of anti-communist discourse since long before these elections. By proposing a thematic analysis, our aim was to explore the possibility that sub-themes attached to these mentions of communism could reveal more about the intent that helped to promote the topic to internet virality. To that end, we have departed from a well-known anti-communist backdrop that has permeated the politics of the country since the early days of the republic and resurfaced on different occasions. First, we situate our notion of virality by examining several cases in contemporary politics.

Viral content in politics

Viral content on the internet is a controversial concept, but in which one can see the potential to influence politics in multiple ways. ‘Viral’ is understood as a kind of spreadable media content that has its impact increased as individuals or communities eagerly share it (Postill, 2014; Jenkins et al., 2018) over a short period of time (Nahon et al., 2011). Content virality is a product of new technological innovations, which made unpredictable images possible and the political impact inevitable (Gerbaudo, 2019). The repetition of social media messages, which could suggest support for populist candidates, makes it challenging to tackle and avoid so-called ‘fake news’ (Groshek and Koc-Michalska, 2017). In the face of the limited coverage of journalistic fact-checking, a vast amount of disinformation can go viral at any time without proper investigation and testing for accuracy (Al-Rawi, 2017; Tucker et al., 2018).

The spread of viral content has already stirred contentious issues that have garnered much publicity from all sides of the political spectrum. In the United States, the case of the #occupy movement has echoed over the years to inspire other social justice movements protesting against inequality. The shooting of an unarmed black man triggered the #Ferguson hashtag, which has sparked broader protests for civil rights and exposed the dangers faced by ethnic minorities. In this research, what is meant by the virality of communism or anti-communism does not only depend on the quantification of social media shares – as communism spreads through a variety of expressions and terms – but on its horizontal transmission, either via memes, humour, junk content or fake news, to a range of other users and media platforms (Cebrian, Rahwan and Pentland, 2016).

The design of viral messages in politics, in the shape of memes, can also serve propaganda purposes, campaigns against mainstream candidates and alternative dissent groups (Denisova, 2019). Beyond the use of sensationalist language in politics, nowadays campaigns are more thoughtfully structured to appear highly ranked in search queries – thanks to big data manipulations (Shao et al., 2018; Venturini, 2019). The complexity that stems from the virality of communism lies in the extent to which it sensationalises fictional ‘dangers’, while hiding other agendas. For example, many YouTube videos have seriously debated the ‘implementation of communism’ as an imminent possibility in Brazil, but only to link it to society’s decay, the crisis of morality and ‘patriotic’ conspiracies (Ribeiro, Lasaitis and Gurgel, 2016; Melo, 2019). However, the promotion of viral communism could also unearth superficial and opportunist mentions of communism, as social media networks can still harbour old debates and revive political stereotypes.

The fear of communism in Brazil

The spread of anti-communist ideology on mass media is a well-known component of Herman and Chomsky’s propaganda model (Herman and Chomsky, 2011: 29). According to them, Western ideology has mobilised public opinion against a communist enemy as a mechanism of political control. We would like to discuss a similar situation, but in the context of the peculiar course of Brazil’s political history. The country has never managed to establish a communist regime (to the degree of Cuba or China, for example). The first Communist Party emerged in the mid-1920s. It owed much to the many waves of European immigrants moving to Brazil. The first communist groups consisted of small gatherings, in which Trotskyists and Stalinists never convened in full alliance (Dulles, 1985). In fact, fundamental difficulties prevented communist parties from flourishing. The lack of translated Marxist literature, for instance, and the high number of illiterate workers, limited membership of these associations to a few dozen, while the notion of ‘class consciousness’ seemed elusive to some of them (Rosa, 2017: 406).

Contrariwise, existing anti-communist rhetoric was fortified during the first government of Getúlio Vargas (1930–1945). In 1935 a failed communist-inspired uprising to oust him provoked a wave of official repression and censorship of communist ideas (Konder, 1980). Communism then represented the Soviet Union. Vargas’ dictatorship dismantled the Communist Party of Brazil (PC do B), which remained illegal for most of the twentieth century. The ‘Soviets’ embodied enemies who could also be infiltrating agents. They could come to ‘destroy the motherland and its basic values: religion, family, speech, and freedom’ (Motta, 2007: 234). While the origins of this ideological statement remain uncertain, the ‘pragmatic’ alignment with the United States on foreign affairs has come up as one of the hypotheses. Brazil’s automatic buy-in to US policy might have prevented any further advance of communist ideas until the 1960s (Steffens, 2011).

During the military regime that ruled Brazil after 1964, further references to communism in the political discourse sought inspiration in the Cuban Revolution and the growing tensions in Vietnam. The Truman Doctrine stated that the US Army ‘had to act against the communist enemy’. At the same time, France was trying to maintain control over its North African colonies, which rebelled by leaning left. These developments contributed, to some degree, to the strong criticism of the so-called communist ideas in Brazil, many of which had branched into Maoism, Trotskyism, and French-inspired movements (Arruda, 2017). The modern Communist Party of Brazil (PC do B) personified these European-inspired groups of dissidents. Founded in 1962, it has been diverse in its ideas and debates, but has never achieved a high number of affiliates (Giannotti, 2007: 165).

The 1964 military coup made the survival of any leftist opposition even harder. The military dictatorship stirred old fears of an existing communist plot within Brazilian society, accentuating its unhealed divisions. The local communist leadership remained confined to unionist action until the re-democratisation in 1984 (Santana, 1999). Napolitano (2014) points to the pivotal moment that guides much of the modern anti-communism, a discourse that lies in the anti-reformism of the 1964’s military coup’s ‘architects’, to whom communism equalled ‘subversion’. Coming from the top level of government, different types of guidance on how to act toward ‘communists’ have influenced political parties, unions, newspapers and opinion polls (Motta, 2007). During the overthrown government President João Goulart, which preceded the 1964 military coup d’état, conservative values had gained ground based on platforms such as the defence of private property and a national ‘morality’.

In the late 1970s and early 1980s, the anti-communist right invited Catholics to ‘crusade’ against Marxist ideals that supposedly threatened religious freedom (Mendes, 2004, 83). As a result, fear of a ‘red menace’ became established among Brazil’s elites (Motta, 2007). In the face of the growth of the unionist movement in the 1980s (Antunes, 1991), the fragmentation of a single ideal of what communism meant among the leftists might have caused the appropriation of the concept by right-wing groups. Lately, the Communist Party of Brazil (PC do B) has allied itself more closely with the moderate Workers’ Party (PT) than with the old Soviet-style communist ideals. In brief, anti-communism has become a more ventilated concept than even communism itself. More recently, the leader of the country’s biggest left-wing party has showcased close ties to communist parties elsewhere (Gazeta do Povo, 2019). As traditional leftists are discredited amid corruption charges, the so-called antipetismo has carried undertones of the old anti-communism (Davis and Straubhaar, 2019).

It is not possible to stress the whole range of shifts observed in communist and anti-communist discourses in Brazil, but this short background is sufficient to show how mentions to communism intersperses with values of militarism and conservatism. As seen, left-wing groups have, somehow, bought into it, but right-wing supporters were the ones to employ it against their enemies in modern times. The possibility of an elected right-wing candidate has made it more likely that links from different topics related to communism could surge on social media. We aim to detail ‘viral communism’ by dedicating research efforts to identify and analyse the mentions to this motto articulated in brief, but popular, social media posts. Whatever Twitter users were contending about communism, they might also have introduced other themes, as we shall discuss next.

Twitter, elections, and viral communism

Since the 2010 presidential elections, there have been profound changes in the way electoral campaigns run content online (Jamil and Sampaio, 2011). On the one hand, the diversity of users publishing messages has laid out a fresh universe of political affinities; on the other, it has become more difficult to identify the sources and mechanisms of dissemination. Despite not all Brazilian candidates having active accounts on popular social networks, the 2014 presidential debate saw growing online hostility between right- and left-wing militants on social media. Research conducted on WhatsApp in 2018 attests that audio, video and emojis made up the majority of messages in groups said to be strictly about politics (Caetano et al., 2018). On both Twitter and Facebook, users supporting the right are more likely to post politically polarising content, even though similar analysis regarding the left is still missing in the literature (Chaia and Brugnano, 2015; Penteado and Lerner, 2018).

Twitter is not the most popular network among Brazilians by the number of users (Chaffey, 2019). Nonetheless, this platform has turned out to become a critical forum because of politicians’ intense posting and the news media that it triggers. The use of Twitter had steered candidate endorsement on other platforms during the 2014 presidential elections (Ortiz et al., 2017). A new feature of the social media activities of users identified with the ‘new’ right relates to the assemblage of unrelated concepts and images, the mechanised spread of memes and extensive use of photo montages (Ribeiro et al., 2016). In 2019, President Jair Bolsonaro caused a series of controversies after posting offensive and provocative tweets (O Dia, 2019).

The extent to which the virality of communism on Twitter springs from this context of amalgamation of resources and evolves into other themes is the main interest of this research. We have pursued two main goals: first, as said, to map textual cues that could indicate other themes in posts related to ‘communism’ in the context of the 2018 elections; second, to qualify the source of these themes seen in viral stories. To that goal, we have sought a link between Brazil’s current affairs and its documented history of anti-communist episodes. This study has coded these linkages using a reflexive method, as we shall see.

Thematic analysis, coding and interpretation

Many studies have drawn on Twitter to engage with the criticality of user-generated content. This informs how individuals can understand complex events, for example the intricacy of popular interpretations of the Zika virus epidemics (Fu et al., 2016). Regarding political campaigns, Recuero et al. (2015) found that Twitter hashtags were relatively important to candidates’ engagement with users during the 2014 presidential run-up. But since then, the growth in the number of so-called ‘influencers’ has also played a crucial role in the spread of highly politicised content, like the images disseminated during former president Dilma Rousseff’s impeachment proceedings, in 2016 (Sandim et al., 2016). A black-and-white depiction of a young Rousseff showed a woman sitting in front of a military court for being a member of a Marxist organisation. Subsequently, populist candidates such as Bolsonaro, started to build a stronger presence on Twitter (Soares, Recuero and Zago, 2018).

Previous thematic analyses have based many studies on sociological health research (Reutter et al., 2009). Scholars have especially examined the subjectivity of perceptions on social media (Caton and Chapman, 2016). At least on an exploratory basis, this method has helped scholars to understand the linkages promoted by text cues such as slang, political jargon, localisms and connections to other broader subjects, such as mentions of race, religion and extremist propaganda (MacNair and Frank, 2017). The present study followed a similar path, but worked with a relatively small sample of tweets (n = 530), which was suited to cover a crucial period of Brazil’s recent political developments: the six months before the electoral run-up (April to October 2018).

Considering a theme as ‘an attribute, descriptor, element, and concept’ that ‘organises a group of repeating ideas,’ we followed detailed orientations from past studies before setting up the analysis (Vaismoradi et al., 2016: 101). Even if robotised resources or artificial intelligence produced some of the sample posts included here, this fact would not compromise our main aim of classifying the tweets and the linkages they establish. This type of ‘relationship code’ (Vaismoradi et al., 2016: 103) would not be possible via API research, for example, a method that depends on taxonomic repositories but does not capture random associations with a theme, such as rumours and non-objective language (Wilson et al., 2017). The same limitation exists in the Advanced Search resource, which extracts data from a repository that can be modified or curated over time (Driscoll and Walker, 2014). Conversely, this factor has not compromised our quest for qualifying selected tweets, as we have not sought to obtain the total breadth of tweets at the moment of their publication.

Our procedure was first to harvest results from a Twitter search query using the following keywords: ‘Brasil, comunismo and eleições’ in different orders. We limited our search to tweets published between the 7th of April – six months before the first round (when legal campaigning started) – and the 28th of October 2018 – the date of the second-round voting. Faced with limited methodological choices for starting the theme identification, we resorted to text mining with Nvivo software, from which we obtained the one hundred most repeated terms in the sample of tweets. After filtering the list to exclude repetition and clutter words, we observed how the fifty most repeated words appeared in fifty-three tweets (10% of the sample), before examining these terms’ relationship with the word communism. We relied on the repetition of these terms to determine meaning unities through which we could classify, label and translate into broader themes. After testing each other’s descriptions, we compared them to ensure accuracy among coders. Then we nominated these assumptions as working themes and developed our storyline.

We are aware of the critique that has warned against the potential subjectivity of this method (Vaismoradi et al., 2016). Hence, the coding followed a strict three-stage process of (i) origination, (ii) verification, and (iii) nomination (Table 1). In the face of a lack of paradigms that could inform us regarding acceptable sample sizes, we decided to use 50% of the total sample (245 tweets), which was a number that could sufficiently represent the total amount of tweets published in the period (530 posts). This amount also made for a realistic workload. Each coder considered the same set of 35 tweets per month from the last to the first tweet published.

Table 1

Example of intercoder categorisation.

Original tweet Origination Verification Nomination
‘Brazil is completely divided between 50% for the right and 50% for the left. Nobody will be completely pleased after the elections. Brazil could split in Right/Left, and each one lives with each one’s ideologies. We need to find a way to be happy. I do not like communism.’ ‘Brazil could split in Right/Left and then each one might live with each one’s ideologies. We need to find a way to be happy’ Coder 1– Brazil’s political system Democracy vs communism/militarism
Coder 2– Polarisation (Brazil vs communism) And
Polarisation (Fraud accusations and conspiracy theories)
‘Besides everything [which is] at stake in these elections, that guy tells me he/she will not vote for PT because he/she does not want to be excommunicated for supporting communism! What have they done to my Brazil, folks?’ ‘The guy tells me he/she will not vote for PT because he/she does not want to be excommunicated for supporting communism!’ Coder 1 – Mentions morals and religion Religious and moral observations
Coder 2 – Religion

As part of the procedure, each coder transcribed the content of each analysed tweet and recorded their decisions on a spreadsheet, adding reflexive notes when necessary (see Table 2). The analysis was performed twice to ensure consistency. A few categories were subjected to an intercoder reliability check (Cohen’s kappa). This revealed a 0.741 measure for the ‘democracy vs communism’ category, which appears as a reliable index in content analysis and for such a subjective analysis (Riffe et al., 2019). Below we discuss the main themes identified and their significance for this research. For privacy reasons, we have limited our mention of user information to their handles. By doing so, we have followed other research (e.g. Cavazos-Rehg et al., 2014) that has seen no problem in publishing users’ handles, as this mention – alone – cannot lead to the identification or harm of individuals whose content is already available to the public. Below we discuss the main themes identified and their significance for this research.

Table 2

Example of tweet coding (emphases in italics).

Tweet Meaning unities (linked terms in Italics)
‘Elections – Brazil 2nd round 28/10/2018 – Supreme Court Judge – A communist man who freed Lula from jail appears to be in favour of communism and hunger in Brazil: Joaquim Barbosa declares vote in Haddad. We will be free from the communist slavery until 2030. UN’s agenda.’ (27 October 2018)
  • communist man who freed Lula

  • communist and hunger

  • communist slavery

Findings and discussion

We describe how these themes have manifested, from the most recurrent to the least recurrent. We dwell on five main themes, while giving a brief theoretical grounding of these themes presented alongside respective examples from the sample. We have chosen to translate the content of each tweet from the Portuguese, as the English version better illustrates our explanation and eases context comprehension.

Political polarisation (fraud accusations and conspiracy theories)

The term polarisation refers here to the intent of provoking political quarrels regarding the upcoming election (Cioccari, 2018). Even though many Twitter discussions were aimed at attacking leftists in general, some did not draw only on the upcoming election. This set of tweets seemed intended to direct the sense of polarisation generated by the word communism into an attack on political adversaries. The word specifically targeted weaknesses in the opponents’ discourse. Adversarial mentions of communism emerged every time an argument broke in the sense of reminding the opponent of the economic legacy left by Brazil’s largest left-wing party, the Workers’ Party. ‘Communist’ was also used to level accusations of administrative inefficiency. Overall, we found these themes related to three main strategies:

  1. Suggesting an association between communism and ballot fraud and the possibility of escalating conflict:

    Without ballot fraud, Bolsonaro wins this election, whether at the first or second round. With ballot fraud, unfortunately, only a civil war could free Brazil from the socialist communism (30 Sep 2018)

  2. Linking communism to a moral failue or a rising corruption risk, insults and personal issues. Users associated the news from the Bolsonaro campaign as a promising alleviation of these same issues:

    Finally, the true scoundrels of the Social #communism in Portugal show their faces: ‘The option is between a civilised man and a scoundrel’ (22 October 2018)

    Brazil is almost entirely committed to communism. Elections are coming, I hope Bolsonaro wins; [he is] a republican, a conservative, like you, Trump’ (29 July 2018)

  3. Linking communism to popular conspiracy theories of global alignment between the members of masonry or other ‘secret’ orgaisations:

    Elections: The final gamble before the final installation of communism in Brazil. Do your research about the masonry and the new world order (11 August 2018)

In all these examples, as in many others, the mention of communism as a menace echoes the 1950s’ way of targeting opponents, which was similar to the American fear of spying in the context of the Cold War, in which potential infiltrators were by and large the Soviet enemy (Motta, 2007). However, these tweets also sought to associate communism with other social and political affiliations. In 2018’s pre-electoral Twitter, communists were identified with real or imagined partisan frameworks such that communism ended up being coupled with unrelated subjects, e.g. the so-called hidden presence of Masonry or the influence of Iran (which was not in conflict with Brazil). Below we discuss in more detail how these linkages appear to be getting in the way of democratic transparency, and, contradictorily pointing towards the probability of military intervention either way.

Democracy vs communism and militarism

Twitter users employed the term communism to show scepticism about Brazilian democracy as a whole. They discouraged voting, which they considered a useless act at high risk of fraud. Regarding militarism, users demanded that the Brazilian Army intervene to avoid the ‘communist contamination’ of the upcoming electoral process.

The PT [Workers’ Party] and every party which defends its ideologies… need to be annihilated, destroyed and erased in the next elections!!! We have to proceed in the next elections with the final burial of communism in Brazil! There shall not be left here one stone above the other (30 April 2018)

Elections in Brazil means to legitimise communism. #interventionnow (16 April 2018)

‘Communism’ turns out to assume the role of an ideological trap, but which differs from the above objective fears of spies or partisans. In this theme, users pitched conspiracy theories to suggest that the ballot would be hijacked by undercover communists, in which case the Brazilian Army should intervene:

What the left deserves is still to come. Socialism and communism will not take Brazil from the Brazilians. That is why the Army will guarantee law and order in this country in case there is fraud in this election. I trust in God who gives me the strength under the [Duque de] Caxias’ army. #elesimno1turno (25 September 2018)

Many contradictory statements contrasted the state of a failed democracy to the possibility of successful militarism. For example, the repeated use of ‘Duque de Caxias’, the patron of the Brazilian Army, led to the revival of the historical character of a Brazilian hero. In fact, Caxias has long served the right-wing ideology of tradition, order and control (e.g. Pierucci, 1987). Here, Caxias fulfils a discourse of containment of society’s most obvious evils (such as violence and corruption). As in the 1960s and 1970s, the country’s moral shield belongs to the Army, which acts as a moral beacon to protect a morally bankrupt country. The virality of a set of hashtags mentioning communism (nãoaocomunismo, tchaucomunista) depended on remixing old-fashioned or anachronic images of the military defence of society. It also depicted this society according to the archetype of the traditional white heterosexual family. The anti-communist standard therefore prefigures the strong anti-corruption ‘idiom’ which was expected from all candidates in this election (Ansell, 2018).

According to a considerable number of users, the October 2018 election was a decisive opportunity to prevent communism from being fully established in Brazil. ‘Fighting communists’ meant accepting the detachment of the military from public life, but replacing it with a powerful judiciary, personified in the figure of Sérgio Moro, a former judge who would later become one of Bolsonaro’s ministers, as this series of tweets shows:

We do not need only to win the elections as we need to brush this gross communism away, which has spread over Brazil (20 October 2018)

What an excellent news! Public prosecutors and Judge Moro are letting the people know who the people [candidates] are in this election; [who are] the characters and on which side they are. We are witnessing communism trying all the ways of taking power in Brazil. #communismneveragain #ptneveragain #haddadout #bolsonaroforpresident (20 October 2018)

These hashtags reveal the process of ‘finding’ the enemy through judicial investigations that have convicted a number of people for crimes such as money laundering or misuse of public office. This collection of tweets shows the ambiguity that stems from the attempt to establish a straightforward link between a corrupt Brazil and a communist Brazil. It mirrors stances in which the country’s democratic institutions are pitted against the ‘red threat’, as others have expressed trust in the Supreme Court ‘punishment’ of communists and their collaborators. Next, we highlight another theme, in which communism is linked with other countries and their relationship with Brazilian politics.

Mention of communist countries

Twitter users mentioned or attacked countries deemed communist, such as Venezuela, North Korea and Cuba, and compared them with Brazil. The severe economic crisis and political turmoil in neighbouring Venezuela helped to forge a stream of news stories on the ‘consequences of communism’. The mainstream media’s approach of framing Venezuela as a communist state, despite its self-defined Bolivarian and Socialist regime (Labio-Bernal, 2018; MacLeod, 2018), supported a scenario in which poverty, hunger and political imprisonment were represented as extreme consequences of Brazil ‘turning communist’:

Brazil is going to be the new Venezuela after the elections. Your vote is going to legitimise the communism in Brazil (13 September 2018)

In Cuba there are no presidential elections since 1948. #Brazil take care of democracy this Sunday. Communism doesn’t allow a step back (25 October 2018)

Smartmatic, [company] owner of electronic voting ballots in Venezuela, and Brazil have frauded the elections in Venezuela, thus establishing communism in the country (26 October 2018)

In response to the left-wing Vice-Presidential candidate Manuela D’Ávila, herself a member of the Communist Party of Brazil (PC do B), one user posted:

I would like to know what this congress woman has to say about an election that allows no opposition [as it is the case] in communist countries such as Cuba and North Korea. Is that what you want for Brazil? How can an assumedly educated person like you support communism in the 21st century? Are you a retarded? (25 April 2018)

Based on news stories and interpretations of this kind, social media users insulted politicians and whoever they saw as representing communist bodies. Looking at the literature, one sees that abuse of communists also happened in other moments of history. Gramsci (1971: 179) described it as a particular aspect of the formation of the Communist Party in Italy. The Brazilian left has, somehow, acknowledged this reality of offences and incorporated it into its political discourse. In the early 1990s, the future President Luiz Inácio Lula da Silva praised being called a communist because ‘Jesus would be called a communist (…) he wanted to be respected by the poor: Equality and bread for all. That is why they murdered him’ (Gabeira et al., 1994).

We cannot dwell more on these dynamics of naming and shaming ‘communists’, which is an aspect resulting from the recent virality of this topic and concurrent themes. We note, however, a departure from attacking communism by making general reference to a political system and its assumed ideological characteristics, and a move towards blaming specific actors for being ‘communist’ based on personal traits. By doing so, Twitter users have reminded other actors, especially left-wing ones, of ethical issues and corruption scandals surrounding their reputations, as we discuss in the next section.

The criticism of the left

The rise and fall of the leftist Workers’ Party (PT) has become a cornerstone of a recent stereotype of being ‘a communist’ on Twitter. Users have employed this term to produce tweets that criticise left-wing parties in general. However, the PT’s recent record of corruption, and the continuing influence of the former President Lula da Silva’s base, mean that it has been the main target of messages attacking communism and communists. Users have universalised this criticism in such a way that conspiracy theories abound. Tweets trade in stories supposedly extracted from other communist societies to sustain their users’ theses against the Workers’ Party, as shown below:

#Lula wins the elections;

#PT starts to implement, finally, communism in the country;

#Brazil becomes similar to Venezuela;

#Finally the leftist dictatorship is established, like the Brazilian left wing parties (19 June 2018)

There is communism, there is socialism, and Brazil has created petism. It is such a disgusting, manipulative thing that is inexplicable how we can get along with people without any character (25 October 2018)

While describing the rise of antipetismo (the movement or sentiment against the party), Davis and Straubhaar (2019) examined the role of social media networks in spreading allegations and conspiracies of this kind. They see the role of liberal movements such as the Movimento Brasil Livre, which has outlived the recent right-wing surge. Our analysis of tweets suggests that criticism of alleged communist influence in Brazil has broadened from attacks on the Workers’ Party to insinuate a range of more nebulous associations, the net effect of which is to imply that the modus operandi of the whole political system is tarnished by leftist influence. The Workers’ Party may be the most egregious example, but the ‘stain’ of communism, extends over other actors as well. During the election, funding was a controversial topic due to illegal and undeclared donations. Conspiracy theories dragged other international players into the argument, as shown below:

The Chinese Communist Party is one of the greatest funders of the PT’s campaign in these elections. Brazil [once it is] in communism will be like China, Venezuela and Cuba according to the PT’s plan of government. Vote for Jair Bolsonaro 17 (12 October 2018)

Besides this and other types of conspiracy theories and accusations, Twitter users also spread bizarre communist-related ‘news’ and memes, often alleging a communist threat to religion and morality. This is the least recurrent pattern, but it is equally important to to understand other kinds of loose references to communism.

Religious and moral observations

Users campaigning against the left-wing candidate Fernando Haddad hinted at the need to pray to ‘avoid the risk of communism’. We insist that these tweets were less about the leftist candidates and more about the deep-seated relationship in political discourse between communism, God and the Devil:

One President [who] puts God above everything. Haddad can sell his soul to the devil so that he can win the elections. There are two ways, salvation and perdition. Brazil or communism. You decide. (22 October 2018)

[The 2018] Elections are coming, so there comes a suggestion: Marching for Jesus to set us free from communism. The Venezuelan church is persecuted; in Nicaragua, there is hunger and misery; in Brazil, the unemployment rate predicts destruction and antichrist activists; our children abandoned children is [something] considered normal…#letuspray. (9 August 2018)

Religious and moral conservatism in Brazil’s politics is a well-documented phenomenon (Machado, 2018). The ‘communist/atheist’ character has largely meant a threatening agent in Brazilian society. These tweets revealed much about the necessary action expected from believers, particularly because an evangelical right-wing candidate was on the cusp of becoming president for the first time. As the above tweet states, ‘There are two ways, salvation or perdition. Brazil or communism.’ Communism is either seen as potential damnation or the ultimate end to religious freedom.

This theme not only recycles the old communist anti-religion thesis, but makes clear the responsibility of the perfect candidate to re-establish freedom in the right-wing sense of restoring morality. This approximation to the Christian repertoire needs further study, but the evidence here suffices to suggest a link between anti-communism, evangelism and ‘freedom’, which are the causes championed by the ‘new right’ in Brazil since earlier in the decade (Cowan, 2014).

Summary and other themes

While we are not working on quantitative premises in this thematic analysis, we looked briefly at how some tweets mentioning communism alongside other themes have performed on Twitter. This demonstration has more value as a general illustration than as evidence of the real figures, as current API configurations and algorithmic set-ups limit a more accurate view for research purposes, as discussed earlier. In any case, Figure 1 shows the number of tweets that mention communism, based on the themes discussed above.

Figure 1
Figure 1
Figure 1

Number of tweets per theme.

We also examined the number of replies that these tweets received, as a way of assessing the possible reactions garnered when one mentions communism. The dates on which tweets received more replies (Figure 2) suggest a trend of ‘communism’ being used for scaremongering purposes, as they surge right after electoral opinion polls were released.

Figure 2
Figure 2
Figure 2

Number of replies to tweets per date (October–April 2018).

This impression is supported by the figures showing which of these themes were more recurrent (Figure 3), as the election approached. By October 2018, polarisation and the democracy vs communism themes peak consistently. Hypothetically, the mention of communism could also have been an element of targeted publicity stunts by right-wing candidates. By comparison, the intensity of these popular tweets citing communism and associated themes had fallen sharply by October. By then, Jair Bolsonaro had established a clear lead, according to the polls after September (Bramatti, 2018).

Figure 3
Figure 3
Figure 3

Occurrence of themes per month (April–October 2018).

Among the active users (Figure 4) that attracted most replies to their mentions of communism are those that bear empty profiles. Many of them have made their profiles private since then.

Figure 4
Figure 4
Figure 4

Number of tweets replied to per handle.

On the list of the most replied-to tweets, we found messages that carry in their texts a mix of irony, catch-phrases and patriotism. The most replied-to messages were:

The right: We need to unite to finish with the left’s plans of destroying the traditional family and establishing communism in Brazil. The left: Bolsonaro won the elections and the third photo of your mobile is your reaction when the dictatorship starts 04 October 2018. By @matopzera

The women will make the difference in these elections. As mothers, they know that we need to win against communism in Brazil. Now it’s the fight for the life of our next generations 29 September 2018 by @luciano_hang

Following the same kind of content, other popular tweets (Figure 5) suggested electoral fraud, recommended prayer against the communists, or simply addressed Brazilians who were undecided on how to vote.

Figure 5
Figure 5
Figure 5

Number of replied-to messages according to content.

Messages challenging these impressions of communism were less frequent, yet some dissonant voices did express their disbelief in or their will to dismantle conspiracy theories:

Brazil is a ‘communist’ country in which one has luxurious cars, consumption, advertisement, freedom of expression, investment markets, elections, private property and wealth concentration etc. Is this really communism? #elections2018 (17 October 2018)

In these presidential elections, fewer arguments are more naive than neutralising the communism and Bolivarianism. The communists of Brazil are in their pyjamas, besides the old generals of 1964. Bolivarian politics does not exist even in Venezuela. It ended with Chávez (27 September 2018)

This article ends with a short discussion about the embedding of communism in viral content and how this process has served to communicate deeper aspects of Brazil’s political discourse.

Conclusion

This thematic analysis has revealed that Twitter posts mentioning communism were mostly associated with suspicion of electronic ballot boxes, distrust of public institutions, corruption, and perceived threats to religion and morality. Regarding the anti-communist background, Communism remains a useful topic to boost other controversial statements, catch-phrases, montages and personal insults. ‘Viral communism’ emerges mainly from the replicability of well-known images, hashtags, images and humour, which are well-known affective devices for viral content (Miller, 2008). The principal source of our information was the textual element of tweets, but the relevance of visual and interactive material was also acknowledged (Stalcup, 2016). Given the enormous political crisis that loomed during this period in Brazil, the virality of communism, even when rooted in memes and entertainment, should not be misinterpreted as accidental or harmless.

In fact, the extent that hopelessness and disinformation have fed ‘viral communism’ have leveraged real everyday experiences of insecurity and poverty; isolation and hopelessness. These are far from being unfounded concerns – even though they are here associated with unreal factors. The mechanisms which the right has exploited to transfer these concrete issues to the elusiveness of communism in a time of voters’ insecurity deserves a better development in future research. In the case of the Brazilian election examined in this study, users might have acted under the influence of the impeachment of Dilma Rousseff, an ex-communist militant, or simply succumbed to political polarisation brokered by the internet. Whatever the cause, the way that the word communism was used shows that it evidently retains many of its negative moral, economic and cultural stereotypes. This research also reveals that social media design and algorithmic power can accommodate intangible and outdated arguments so that these topics can recur at the expense of relevant political debate.

Competing Interests

The authors have no competing interests to declare.

Author Information

Dr Helton Levy is a journalist and Lecturer in Communications at John Cabot University, Rome. He is the author of The Internet, Politics and Inequality in Contemporary Brazil: Peripheral Media (Rowman & Littlefield, 2018).

Dr Claudia Sarmento is a journalist and holds a PhD in Media and Communications from the University of Westminster.

References

1 Al-Rawi, A. (2017). Viral news on social media. Digital Journalism, 1–17. DOI:  http://doi.org/10.1080/21670811.2017.1387062

2 Ansell, A. (2018). Impeaching Dilma Rousseff: The double life of corruption allegations on Brazil’s political right. Culture, Theory and Critique, 59(4), 312–331. DOI:  http://doi.org/10.1080/14735784.2018.1499432

3 Antunes, R. (1991). O novo sindicalismo. São Paulo: Brasil Urgente.

4 Arruda, P. F. (2017). Partidos políticos e disputa eleitoral no Brasil. São Paulo: PUC.

5 Bramatti, D. (2018). Bolsonaro mantém liderança isolada em São Paulo nas eleições. Terra. 25 September 2018.

6 Caetano, J. A., et al. (2018). Characterizing the public perception of WhatsApp through the lens of media. arXiv preprint arXiv:1808.05927.

7 Caton, S., & Chapman, M. (2016). The use of social media and people with intellectual disability: A systematic review and thematic analysis. Journal of Intellectual and Developmental Disability, 41(2), 125–139. DOI:  http://doi.org/10.3109/13668250.2016.1153052

8 Cavazos-Rehg, P., Krauss, M., Grucza, R., & Bierut, L. (2014). Characterizing the followers and tweets of a marijuana-focused Twitter handle. Journal of Medical Internet Research, 16(6), e157. DOI:  http://doi.org/10.2196/jmir.3247

9 Cebrian, M., Rahwan, I., & Pentland, A. S. (2016). Beyond viral. Communications of the ACM, 59(4), 36–39. DOI:  http://doi.org/10.1145/2818992

10 Chaffey, D. (2019). Global social media research summary. Smart Insights. Available at: https://www.smartinsights.com/social-media-marketing/social-media-strategy/new-global-social-media-research/ (last accessed 31 March 2019).

11 Chagas, V., Modesto, M., & Magalhães, D. (2019). O Brasil vai virar Venezuela: medo, memes e enquadramentos emocionais no WhatsApp pró-Bolsonaro. Esferas, 14, 1–17. DOI:  http://doi.org/10.31501/esf.v0i14.10374

12 Chaia, V. L. M., & Brugnago, F. (2015). A nova polarização política nas eleições de 2014: radicalização ideológica da direita no mundo contemporâneo do Facebook. Aurora. Revista de Arte, Mídia e Política, 7(21), 99–129.

13 Charleaux, J. P., & Corsalette, C. (2018). Por que a ameaça comunista ainda é usada na eleição? Nexo Jornal. Accessed 26 October 2018.

14 Cioccari, D. (2018). O atentado contra Jair Bolsonaro: imagem e violência nas eleições de 2018. Líbero, 21(42), 128–142.

15 Cowan, B. A. (2014). ‘Nosso Terreno’ crise moral, política evangélica e a formação da ‘Nova Direita’ brasileira. Varia História, 30(52), 101–125. DOI:  http://doi.org/10.1590/S0104-87752014000100006

16 Davis, S., & Straubhaar, J. (2019). Producing Antipetismo: Media activism and the rise of the radical, nationalist right in contemporary Brazil. International Communication Gazette, 82(1), 82–100. DOI:  http://doi.org/10.1177/1748048519880731

17 Denisova, A. (2019). Internet Memes and Society: Social, Cultural, and Political Contexts. New York: Routledge. DOI:  http://doi.org/10.4324/9780429469404

18 Driscoll, K., & Walker, S. (2014). Big data, big questions|working within a black box: Transparency in the collection and production of big twitter data. International Journal of Communication, 8, 1745–1764.

19 Dulles, J. (1985). O Comunismo no Brasil, 1935–1945: Repressão em meio ao cataclismo mundial. Brasília. São Paulo: Nova Fronteira.

20 Fu, K. W., et al. (2016). How people react to Zika virus outbreaks on Twitter? A computational content analysis. American Journal of Infection Control, 44(12), 1700–1702. DOI:  http://doi.org/10.1016/j.ajic.2016.04.253

21 Gabeira, F. (1994). Viagem ao Coração do Brasil. Florianópolis: Página Aberta.

22 Gazeta do Povo. (2019). Gleisi Hoffmann participa de evento do Partido Comunista Chinês. Gazeta do Povo [online]. Accessed 17 November 2019.

23 Gerbaudo, P. (2019). The Digital Party: Political Organisation and Online Democracy. London: Pluto Press. DOI:  http://doi.org/10.2307/j.ctv86dg2g

24 Giannotti, V. (2007). História das lutas dos trabalhadores no Brasil. Mauad Editora Ltda.

25 Gramsci, A. (1971). La costruzione del partito comunista: 1923–1926 (Vol. 12). Giulio Einaudi.

26 Groshek, J., & Koc-Michalska, K. (2017). Helping populism win? Social media use, filter bubbles, and support for populist presidential candidates in the 2016 US election campaign. Information, Communication & Society, 20(9), 1389–1407. DOI:  http://doi.org/10.1080/1369118X.2017.1329334

27 Herman, E., & Chomsky, N. (2011). Manufacturing Consent: The Political Economy of the Mass Media. New York: Knopf Doubleday.

28 Jamil, F. P., & Sampaio, R. (2011). Internet e eleições 2010 no Brasil: rupturas e continuidades nos padroões midiáticos das campanhas online. Revista Galáxia, São Paulo, 22, 208–221.

29 Jenkins, H., Ford, S., & Green, J. (2018). Spreadable Media: Creating Value and Meaning in a Networked Culture. New York: NYU Press.

30 Konder, L. (1980). A democracia e os comunistas no Brasil. São Paulo: Graal.

31 Labio-Bernal, A. (2018). Anti-communism and the mainstream online press in Spain: Criticism of Podemos as a strategy of a two-party system in crisis. In J. Pedro-Carañana, et al. (Ed.), The Propaganda Model Today: Filtering Perceptions and Awareness. London: University of Westminster Press. DOI:  http://doi.org/10.16997/book27.i

32 Machado, C., et al. (2018). News and political information consumption in Brazil: Mapping the first round of the 2018 Brazilian presidential election on Twitter. Oxford: The Computational Propaganda Project.

33 Machado, M. D. C. (2018). Religion and Moral Conservatism in Brazilian Politics. Politics and Religion Journal, 12(1), 55–74.

34 MacLeod, A. (2018). Bad News from Venezuela: Twenty Years of Fake News and Misreporting. Abingdon: Routledge. DOI:  http://doi.org/10.4324/9781351038263

35 MacNair, L., & Frank, R. (2017). ‘To my brothers in the west’: A thematic analysis of videos produced by the Islamic State’s al-Hayat Media Center. Journal of Contemporary Criminal Justice, 33(3), 234–253. DOI:  http://doi.org/10.1177/1043986217699313

36 Melo, T. M. (2019). Pistas para uma Cartografia Performativa da ‘Nova Direita’ (2015-2019). Revista Brasileira de Estudos da Presença, 9(4), 1–32. DOI:  http://doi.org/10.1590/2237-266091005

37 Mendes, R. A. S. (2004). As direitas e o anti-comunismo no Brasil: 1961–1965. Niteroi, UFF (pp. 80–97).

38 Miller, V. (2008). New media, networking and phatic culture. Convergence, 14(4), 387–400. DOI:  http://doi.org/10.1177/1354856508094659

39 Mota, M., Couto, M., & Rocha, G. (2018). ‘Mensagens com conteúdo #FAKE sobre fraude em urnas eletrônicas se espalham nas redes’. G1 (last accessed 16 November 2019).

40 Motta, R. P. S. (2007). O perigo é vermelho e vem de for a: o Brasil e a URSS. Locus: Revista de História, Juiz de Fora, 13(2), 227–246.

41 Nahon, K., Hemsley, J., Walker, S., & Hussain, M. (2011). Fifteen minutes of fame: The power of blogs in the lifecycle of viral political information. Policy & Internet, 3, 1–28. DOI:  http://doi.org/10.2202/1944-2866.1108

42 Napolitano, M. (2014). História do Regime Militar Brasileiro. São Paulo: Contexto.

43 O Dia. (2019). Internautas ironizam publicação de Jair Bolsonaro no Twitter. O Dia [online]. 6 March 2019 (last accessed 16 November 2019).

44 Oliveira, L. P. D. (2018). Redes Sociais e influência na Política Brasileira: Análise da formação de aspectos da opinião política de jovens eleitores do Presidente Eleito, Jair Bolsonaro. UFSM.

45 Ortiz, J., Hamrin, S., Aggio, C., & Dalmonte, E. (2017). Television experience and political discussion on Twitter: Exploring online conversations during the 2014 Brazilian presidential elections. Galáxia (São Paulo), 36, 45–58. DOI:  http://doi.org/10.1590/1982-2554230952

46 Penteado, C. L. C., & Lerner, C. (2018). A direita na rede: mobilização online no impeachment de Dilma Rousseff. Em Debate: Periódico de Opinião Pública e Conjuntura Política, Belo Horizonte, 10(1), 12–24.

47 Pierucci, A. F. (1987). As bases da nova direita. Novos Estudos Cebrap, 19, 26–45.

48 Postill, J. (2014). Democracy in an age of viral reality: A media epidemiography of Spain’s indignados movement. Ethnography, 15(1), 51–69. DOI:  http://doi.org/10.1177/1466138113502513

49 Recuero, R., Zago, G., Bastos, M. T., & Araújo, R. (2015). Hashtags functions in the protests across Brazil. SAGE Open, 5(2). DOI:  http://doi.org/10.1177/2158244015586000

50 Reutter, L. I., et al. (2009). ‘Who do they think we are, anyway?’: Perceptions of and responses to poverty stigma. Qualitative Health Research, 19(3), 297–311. DOI:  http://doi.org/10.1177/1049732308330246

51 Ribeiro, L. G. M., Lasaitis, C., & Gurgel, L. (2016). Bolsonaro Zuero 3.0: Um estudo sobre as novas articulações do discurso da direita brasileira através das redes sociais. Anagrama, 10(2).

52 Riffe, D., Lacy, S., Fico, F., & Watson, B. (2019). Analyzing Media Messages: Using Quantitative Content Analysis in Research. New York: Routledge. DOI:  http://doi.org/10.4324/9780429464287

53 Rosa, L. R. O. (2017). Comunistas em Ribeirão Preto: uma análise das raízes do PCB no interior paulista. Ribeirão Preto: USP (last accessed 3 February 2019).

54 Sandim, H., Azevedo, D., da Silva, A. P. C., & Moro, M. M. (2016). The role of social capital in information diffusion over Twitter: A study case over Brazilian Posts. In BiDu-Posters@ VLDB.

55 Santana, M. A. (1999). Entre a ruptura e a continuidade: visões da história do movimento sindical brasileiro. Revista Brasileira de Ciências Sociais, 14(41), 103–120. DOI:  http://doi.org/10.1590/S0102-69091999000300007

56 Shao, C., et al. (2018). The spread of low-credibility content by social bots. Nature Communications, 9(1), 4787. DOI:  http://doi.org/10.1038/s41467-018-06930-7

57 Soares, F. B., Recuero, R., & Zago, G. (2018). Influencers in Polarized Political Networks on Twitter. In Proceedings of the 9th International Conference on Social Media and Society (pp. 168–177). DOI:  http://doi.org/10.1145/3217804.3217909

58 Stalcup, M. (2016). The aesthetic politics of unfinished media: New media activism in Brazil. Visual Anthropology Review, 32(2), 144–156. DOI:  http://doi.org/10.1111/var.12106

59 Steffens, M. H. (2011). O pragmatismo brasilianista na produção biográfica: Getúlio Vargas por John W.F. Dulles. Anais do XXVI Simpósio Nacional de História – ANPUH. São Paulo: ANPUH.

60 Tucker, J., et al. (2018). Social Media, Political Polarization, and Political Disinformation: A Review of the Scientific Literature. Available at: https://core.ac.uk/download/pdf/154423139.pdf Accessed 3 February 2019. DOI:  http://doi.org/10.2139/ssrn.3144139

61 Vaismoradi, M., Turunen, H., Jones, J., & Snelgrove, S. (2016). Theme development in qualitative content analysis and thematic analysis. Journal of Nursing Education and Practice, 6(5), 100–110. DOI:  http://doi.org/10.5430/jnep.v6n5p100

62 Venturini, T. (2019). From Fake to Junk News, the Data Politics of Online Virality. In: Data Politics: Worlds, Subjects, Rights. London: Routledge. DOI:  http://doi.org/10.4324/9781315167305-7

63 Wilson, T., Stanek, S. A., Spiro, E. S., & Starbird, K. (2017). Language limitations in rumor research? Comparing French and English tweets sent during the 2015 Paris Attacks. Proceedings of the Information Systems for Crisis Response and Management (ISCRAM), 546–553.