Sources, Channels and Strategies of Disinformation in the 2020 US Election: Social Networks, Traditional Media and Political Candidates

Abstract

The dissemination of fake news during the conduct of an electoral campaign can significantly distort the process by which voters form their opinion on candidates and decide their vote. Cases of disinformation have been happening since the rise of social networks and the last presidential election held in 2020 in the United States was not an exception. The present research aims at analyzing the ways in which political disinformation is generated by different types of sources (social networks users, the media and political candidates) through various channels for communication (social and traditional media). Quantitative and qalitative methods were used to analyze a sample of news published during the election and verified by the most important fact-checking organizations in the United States and Europe. The results indicate that users of social networks spread false information on equal terms with presidential candidates, although the channel preferred to spread misleading messages was social networks in 67.4% of cases. The candidates relied on the use of classic disinformation strategies through traditional media, although the greatest degree of disinformation occurred when conspiratorial hoaxes were circulated through social networks.

1. Introduction

After the arrival of the Internet and social networks, the rules governing the implementation of international electoral processes have undergone profound changes. In recent times, political communication techniques and traditional persuasion strategies employed by candidates to obtain the vote of their electorate are no longer the same. In this regard, the efforts have moved to a new scenario in which the candidates directly interact with the voters, although they are not the single players of the game. In the social networks’ universe, other participants can be found such as traditional media, rivals of different political hues, lobbies and other interest groups, in addition to social media users who sometimes communicate in an open and personalized way and on other occasions, anonymously.

The presence of this high number of participants inevitably generates a volume of information not always relevant or necessary that makes, on too many occasions, only noise and misinformation. Other times, the dissemination of fake or inaccurate news in a partisan way during the conduct of an electoral campaign can significantly distort the process by which voters form their opinion on the candidates and decide their vote. For this reason, a few years ago, some media started acting in a way that goes beyond merely verifying sources and data—a core and inherent function to journalism—and perform according to a series of principles and fact-checking practices proposed by the International Fact-Checking Network (IFCN), a unit of the Poynter Institute dedicated to bringing together fact-checkers worldwide. Nowadays, the number of fact-checking organizations is growing throughout the world and specialized fact-checkers have become so necessary that we no longer conceive their absence in any electoral process underway within the context of democratic countries (Hameleers and Van der Meer 2019; Wood and Porter 2018; Wintersieck 2017).

Cases of disinformation have been happening for about a decade, when the 2012 United States (US) presidential election took place and primarily four years later, in 2016, when Republican candidate Donald Trump won in a clearly polarized climate of opinion. The last election held in 2020 has not been an exception either. The accusations of electoral fraud levelled from the outgoing president’s entourage that resulted in the storming of the Capitol by a group of Republican supporters is possibly the most visible example of disinformation that emerged during the electoral season, but it was not the only one.

This is the context of the research that is now being introduced and whose main goal is to analyze the ways in which political disinformation is generated by different types of sources in a case particularly influential on international public opinion, such as the 2020 US presidential election. To do this, a selected sample of news published during the electoral season by the most relevant fact-checking organizations around the world was compiled and reviewed. The research aims at providing new knowledge, as well as verifying and updating the findings of previous research on the most common types of sources that produce disinformation in a political context such as the one described above, as well as on the different kinds of instruments, strategies and channels for communication that the sources use to spread their messages today.

In that vein, the present research analyzed both the media and social networks as the two channels most widely used to spread false information during the 2020 US election. The results showed that social networks outperformed the media by a wide margin of difference, regardless of the type of source of disinformation, although a few exceptions in the use of some disinformation strategies by political candidates were noticed.

The results of the research carried out on the occasion of the 2020 US presidential election partly overlap those announced by the experts (Paniagua et al. 2020), mainly regarding the use of techniques of disinformation at specific moments of the campaign, such as the accusations of electoral fraud made by the Republican candidate. Although the level of disinformation reported during the period analyzed remained constant in general terms, remarkable differences were found with respect to the source that generated the disinformation (Republican or Democratic candidate).

2. Theoretical Framework

2.1. Sources of Disinformation

In relation to the sources of disinformation, it is usual that the amount of fake news grow exponentially during electoral seasons (Waisbord 2018). As Shin et al. (2016) recall, during the 2012 US election, false information was widely disseminated via Twitter, especially among politically polarized voters. The 2016 US election was also another clear example of misinformation derived from social media, but in that case, it was also largely orchestrated by foreign powers that managed to unwantedly influence the electoral campaign (Hall Jamieson 2018). However, in the 2020 election, the sources of disinformation that most attracted the attention of fact-checkers were those represented by users of social networks, the candidates themselves and traditional media. Therefore, in this case, no foreign power following a planned and sustained over time disinformation strategy was involved, according to the concept of “organized disinformation” used in international relations (Volkoff 1986). In the 2020 election, the only messages analyzed by international fact-checkers that came from an institutional source were those issued by the White House itself.

A large part of the false or inaccurate messages that were disseminated during the 2020 electoral campaign, as well as during the weeks before and after, were detected on social networks according to a trend already observed in the 2016 US election, when, as reported by Allcott and Gentzkow (2017), the majority of Twitter users read at least one fake news item per day. Although some authors consider that, in that election, the idea was only to promote the use of social networks (Carlson 2020) and that Twitter interactivity rates are traditionally low (Kwak et al. 2010; Chadwick and Stanyer 2010; Verweij 2012), it is not surprising that social media users still rely on that source of disinformation, especially if we take into account how easily social networks allow sharing reworked information that is frequently published without going through an editorial or verification process (Spohr 2017). As Molina and Magallón (2021) proved during the analysis of the 2019 presidential election in Uruguay—which was equally polarized—the principal source of disinformation was represented by unknown users of social networks who spread fake news on WhatsApp or by means of false Twitter and Facebook accounts.

Although experts do not agree on the prevalence of Facebook (Williams and Gulati 2013) or Twitter (Jungherr 2016) use among candidates during electoral campaigns, it is a fact that certain users of social networks can exert a strong influence on others, regardless of the social network. In that sense, some authors speak of the existence of “fake news spreaders” (Duan et al. 2020), a term used to refer to individuals who disseminate false information on a regular basis, a fact also observed throughout the present research. As stated by Silverman (2016), during the 2016 US election, the public’s engagement with fake news through Facebook was higher than through traditional media, a finding supported by Allcott and Gentzkow (2017), who affirm that an individual user without a great reputation can reach, in some cases, as similar an audience as to that accounted by networks such as Fox News or CNN or even The New York Times. In addition, Vosoughi et al. (2018) claim that even the least connected user can be significantly more efficient at generating false information than the media when they publish real and fact-checked information, although other experts consider that this practice is very unusual (Guess et al. 2019).

On the other hand, Allcott and Gentzkow (2017) warned that political ideology could influence the permeability of voters to fake news, after proving that false information about Donald Trump disseminated during the 2016 US election was shared on social networks thirty million times while that spread about Hillary Clinton, the Democratic candidate, was only 7.6 million times. Peter and Koch (2019), for their part, assure that every source is related to a certain degree of credibility, something especially important when speaking of social networks where, on many occasions, information conveyed by friends and family is more trusted than that of traditional media. Perhaps for this reason, a great number of sources from social networks has been included in the news published by the media (Benaissa Pedriza 2018; Hedman and Djerf-Pierre 2013; Lasorsa et al. 2012), although the introduction of this type of source into political journalism is considered by some experts as a negative issue, since it encourages an excessive presence of “infotainment” in this kind of information (Owen 2018) and increases the risk of spreading false or inaccurate messages, especially when the source from which they come cannot be identified or sufficiently verified. In any case, the relevance of media exposure when forming an opinion (Gerber and Green 2000) or when affecting political beliefs (Nyhan et al. 2013) is a fact sufficiently proven by experts.

Surely, for those reasons, the media have been and are frequently used as a channel for information that do not always conform to reality. It is not unusual that some broadcasters made attempts to use them as a means to achieve their goals (García Avilés 2009), breaching thereby the fundamental principle of media independence. Doshi et al. (2018) demonstrated that just publishing ten fake news a week increased a website’s reader traffic by 3%, a circumstance that has encouraged the proliferation of media dedicated exclusively to disseminate this type of information. However, these media are not the only ones who are currently spreading fake news, since disinformation is also being disseminated through some media corporations who are more prone to defend economic or political interests than to report objectively (Chomsky and Herman 1995; Lee 2019).

According to Guo and Vargo (2018), this phenomenon could be observed during the 2016 US election, when the media that covered the agenda of topics discussed by Donald Trump were the ones that misinformed their audience the most. In the same way, notable differences between the media have been observed in the present research, although it was possible to detect that disinformation occurred both in trusted media and in untrusted ones.

2.2. Channels for Disinformation

What cannot be denied is that, at the moment, news produced by journalists coexists with those produced by individual users (Van-Dijck 2009) and that the sources of disinformation can now spread their messages through a wide range of channels for communication such as the one formed by social networks (Rodríguez Andrés 2018).

According to a study by the Pew Research Center (2018), social networks are the channel preferred to become informed for the majority of Americans in a percentage of 20% compared to 16% of citizens who turn to print media. A situation that was used during the 2016 US general election to turn social networks into channels for the massive distribution of fake news and to transform them into a powerful propaganda instrument (Journell 2017). According to a study carried out by Paniagua et al. (2020) on the disinformation reported during the 2019 general election in Spain, the main hoaxes detected by fact-checkers came mostly from social networks (Twitter, Facebook and WhatsApp). Only a small number came from websites identified as well-known disinformation sites, while the rest came from partisan or satirical websites. Molina and Magallón (2021) also found in their study on the 2019 presidential election in Uruguay that the channel through which the greatest volume of disinformation was distributed was social networks (Facebook reached 44% above Twitter (2.9%) and WhatsApp (19.6%); the three of them represented 86.6% of the total disinformation).

2.3. Strategies of Disinformation

Finally, and with regard to the strategies used by the sources of disinformation, the research took into account the most recent works on the analysis of political discourse and the personalization of candidates (Cardenas et al. 2017; Magallón 2019; Marcos et al. 2020; Paniagua et al. 2020; Rossini et al. 2021), both on social networks and in the media (Gallardo and Enguix 2016; Milner and Phillips 2016). Thus, the research focused on analyzing two types of classic tactics that the candidates and the members of their political entourage resorted to during the electoral campaign of the 2020 US election: the praise of the candidate’s virtues and the dissemination of false claims on the political opponent. This typology was also applied to the study of other sources of disinformation (social networks users and the media).

Magallón (2019) recalls the importance of each candidate when it comes to encouraging a climate of disinformation that generates uncertainty and a lack of confidence during an electoral process. For this, it is essential that at least one of the candidates seeks polarization as a political strategy, presenting himself outside the political establishment. For Rodríguez Andrés (2018), in these cases, the essence of disinformation is not positive (consisting of extolling the candidate’s own virtues) but negative (discrediting the adversary for the benefit of the candidate who circulates the fake news). However, Emmerich (2015) believes that the fundamental condition for disinformation to occur is intentionality, similar to Wardle (2018), for whom disinformation is understood as “any false informational content that has been created and disseminated in a deliberated way”. Therefore, and based on the above, this research focused on the analysis of both the messages intended to damage the adversary’s public image and those that praised the achievements of one of the candidates, as long as these messages were manifestly false or inaccurate and intentionally disseminated to create a climate of disinformation. The research thus aligns with the studies carried out on the different uses that politicians make of social networks within a political communication strategy (Parmelee and Bichard 2011; Magin et al. 2017) and on the way in which candidates disseminate false information as a strategy to redirect public opinion in their favor (Rossini et al. 2021) during the conduct of electoral campaigns.

When regional elections in Valencia (Spain) took place in 2019, Marcos et al. (2020) decided to analyze a series of messages posted on Facebook by several political candidates and came to the conclusion that the followers of the government candidate showed a greater interest in the information that praised the government’s actions and management, while those who followed the opposition candidate preferred posts that criticized the adversary. In addition, in the framework of the general election held in Spain in 2019, Paniagua et al. (2020) discovered that although the hoaxes published during the campaign were addressed to all candidates, the government party and the one that later would be his coalition partner were the most attacked by political opponents. The analysis carried out on the sample of information verified by 10 international fact-checking organizations during the 2020 US election revealed practices similar to those described in the studies referred to, with the particularity that, in terms of disinformation, the behavior of the Republican candidate was closer to that of a candidate who is in the opposition rather than in the government.

Although the use of digital resources by political actors has become something usual (Stromer-Galley 2014; Lilleker et al. 2015) since former President Barack Obama introduced them in his campaign (Caldevilla 2009), the truth is that not all the resources are used in the same way and at the same moment as part of a political strategy of disinformation. Regarding the instruments used by political candidates during the 2020 US election, different types of false or inaccurate information were analyzed, as well as the moment in which they were disseminated—before, during and after the election was held—in line with key research carried out by the experts. These include projects developed by Uscinski et al. (2016) on the identical permeability of left- and right-wing voters to conspiracy theories, as well as by Pyrhönen and Bauvois (2020) on the effectiveness of conspiracy theories circulated on social networks and the one published by Paniagua et al. (2020), who analyzed various types of hoaxes (false attribution of actions and false attribution of statements). The work of Molina and Magallón (2021) is also relevant, who examined the level of disinformation spilled by candidates during political elections, discovering that the latter increased as the electoral campaign and the holding of the election approached, as well as during the broadcasting of electoral debates between candidates. Finally, the study by Bozarth et al. (2020) should be mentioned here, according to which the number of fake news disseminated during a general election season increased regardless of the topics discussed.

3. Materials and Methods

The research, taking as a reference the evolution of the literature and the results of previous research on the implementation of polarized electoral processes, posed the following research questions on the 2020 US presidential election:

Q1. What is the origin of the fake messages disseminated during the electoral season?

Q2. Can a specific typology of disinformation sources be determined?

Q3. In what ways are false, inaccurate or misleading messages mainly spread?

Q4. What kind of disinformation strategies do the sources employ today?

In relation to the research questions, the following hypotheses were formulated:

Hypothesis 1 (H1).

The disinformation generated during the 2020 US presidential election came primarily from social networks sources when compared to the media and the political candidates.

Hypothesis 2 (H2).

Social networks were the channel for communication most used to disseminate fake or misleading information above traditional media.

Hypothesis 3 (H3).

The sources of disinformation play similar role models when using classic and new disinformation strategies.

Hypothesis 4 (H4).

The convergence of misleading communication strategies increased the level of disinformation generated by political candidates.

The factors analyzed were the following:

• Sources of disinformation: social networks, political candidates and traditional media;

• Channels for disinformation: social networks and traditional media;

• Disinformation strategies: praise of the candidate’s virtues based on false data, false claims on the political opponent, dissemination of conspiratorial hoaxes during the electoral process.

The research design was multifactorial: 1 × 3 for the analysis of the disinformation sources, 1 × 2 for the observation of the channels for disinformation and 1 × 3 for the examination of the different strategies of disinformation.

The methods used were both quantitative (collection of statistical data) and qualitative. Direct observation and content analysis techniques were applied to a series of news items that were included in different categories of analysis. As for the sources of disinformation, these ones were “identified or anonymous users”, “trusted or untrusted media”, “public or private institution” and “Republican candidate or Democratic candidate”. The channels of disinformation were included in the categories “social networks”, “digital media”, “television networks” and “news agencies”. The strategies of disinformation were categorized in association with the sources of disinformation: “social networks users”, “media” and “political candidates”. All the variables were encoded manually and individually taking into account the size of the sample. The inter-coder reliability coefficients ranged from 1 (Pearson’s formula in test-retest) to 0.97–0.99 (Spearman-Brown’s formula in split-halves) depending on the factors analyzed (sources of disinformation, channels for disinformation and disinformation strategies).

The news items were published by 10 international fact-checking organizations on their respective websites, excluding from the analysis the news published by these same media on their social media accounts. This made it possible to obtain a more general overview in terms of audiences compared to that constituted exclusively by users of social networks.

Primary and secondary sources of information were analyzed, in particular the statements made by the political candidates during the election through different channels for communication, as well as the media, public institutions such as the White House and social media users.

The 10 fact-checking organizations from Spain, France, the United Kingdom and the United States published each a minimum of 5 news items on the 2020 US presidential election. Every piece of information verified by these media was analyzed during the period of study of the research.

The 10 fact-checking organizations were members of the International Fact-Checking Network (IFCN) and were selected on the basis of their relevance while trying to maintain a balanced geographical representation at the same time. The initial idea was to choose media from the United States, the country where the election was going to be held, from Europe, where the election was expected to be closely monitored, and from Latin America, the most relevant neighboring area geostrategically speaking. Finally, only media from the United States and Europe were included as Chequeado, the most important fact-checking organization of Argentina, relied on Maldita.es (a Spanish media previously selected for the sample) to verify the news published on the US election.

On the other hand, publicly and privately owned media were chosen, as well as digital and audiovisual organizations. Therefore, a total of seven privately owned media and three publicly owned ones were chosen (AFP Fact Check, BBC Reality Check and EFE Verifica). Eight digital native media and two media at the service of television networks were brought together (BBC Reality Check and Les observateurs de France 24).

The fact-checking organizations analyzed were as follows (Table 1):

A total of 166 news stories were analyzed during a 5-month period between the end of the Republican Convention (28 August 2020) and the days immediately after the new president’s inauguration (28 January 2021). It was decided to observe the fact-checking organizations’ production for a longer period than the one delimited by the electoral campaign in order to examine the nature and characteristics of the disinformation generated by different types of sources at times other than the traditional speeches and electoral debates held between political candidates. This made it possible to expand the content analysis to other especially relevant topics that emerged throughout the period of study.

The results of the research provided revealing data on the sources, channels and strategies of disinformation reported in electoral processes that take place in an international context. These are presented below.

4. Results

4.1. Sources of Disinformation

The disinformation spread during the 2020 US election came from multiple sources. The observation of 166 news items published on 10 fact-checking websites from the United States and Europe resulted in the classification of the following sources of disinformation (Table 2):

It was discovered that the least reliable sources of information were those from social networks (40.9% of all sources) at the same level as the two candidates running for president of the United States (40.9%), although notable differences between them were revealed (the statements of Joe Biden, the Democratic candidate, only accounted for 9% of the disinformation reported during the election, while Donald Trump, the Republican candidate, and his political entourage accounted for 31.9%). The third most important source of disinformation was formed by the media (15.6% of all sources) and the fourth by public institutions (2.4%), represented exclusively by the White House.

Sources from social networks were divided into two types: identified or anonymous user’s accounts. The fact-checking organizations only managed to identify nominal accounts of social media users in a minority of cases—14.7%—compared to 85.3% of anonymous users. Regarding the identified users, 60% were pro-Trump voters, 30% were well-known conspirators and the remaining 10% were members of an NGO with a conservative ideology (Turning Point USA).

A typology of disinformation sources can be described as follows (Figure 1):

The third most important source of disinformation was constituted by the media (Figure 2), both trusted media (newspapers such as The Washington Post and conservative television networks such as Fox News, Blaze Tv and OAN, among others) and untrusted media (Before it’s News, BLes Mundo and others known for regularly spreading false or misleading content on their websites) in an identical percentage (7.8%). Trusted media published fake or misleading news in the following percentages: center/center-left ideology media: 23%; conservative ideology media: 30.7%; media inclined to the Republican candidate Donald Trump: 15.3%; media without known orientation: 30.7%. Of all the trusted media that published fake or inaccurate news, only 15% were non-US media (Spanish and French). Untrusted media were represented by conservative media in 69.2% of cases, by pro-Trump media in 15.3% of cases and by tabloid media with unknown political orientation in another 15.3% of cases. Only 23% of the untrusted media were non-US (Latin American, Spanish and Canadian).

Last in the line of disinformation sources was the White House (2.4%). The disinformation was expressed through statements made in the framework of public appearances, press conferences, briefing sessions or working documents provided to the media.

The results are interpreted as meaning that 70% of the identified social media users who contributed to spreading fake or inaccurate news were openly pro-Trump or conservative voters. As regards traditional media, 65.3% of both trusted and untrusted media that disinformed during the election were of conservative ideology or openly supported the Republican candidate. To this percentage should be added the disinformation disseminated from the White House during the election season (2.4%). In global terms, it could be estimated that the highest percentage of disinformation was generated from government institutions, pro-Trump social media users, media favorable to the Republican candidate or by Donald Trump himself and his political environment in 48.7% of the cases, while the percentage of disinformation coming from the center/center-left media or the Democratic candidate Joe Biden was 10.8%. In other words, the sources of disinformation ideologically linked to the Republican candidate were 4.5 times higher than those related to the Democratic candidate.

4.2. Channels for Disinformation

The two main channels for communication through which fake news were spread during the 2020 US presidential election were social networks and traditional media.

Social networks (Figure 3) represented the most used way to convey fake or misleading information (67.4%) compared to the media (32.5%). Twitter was the most used social network (39.2% of all cases), followed by Facebook (14.2%), YouTube (4.4%), Instagram (1.7%) and TikTok (1.7%). In a considerable 38.3% of cases, the fact-checking organizations did not specify the social network that echoed the disinformation. On these occasions, only generic references to the circulation of false content on “social networks” were included in the news.

The formats used by social media users to disinform were posts, understood as text publications that contained false, erroneous or inaccurate data (46.4% of all social media formats analyzed), followed by videos (26.7%), pictures or photographs (19.6%) and electoral graphics and maps (7.1%).

Regarding traditional media (Figure 4), disinformation was disseminated mainly by digital media (57.6%), private television networks (38.4% of cases) and an international news agency (AFP) (3.8%). A large part of the digital media that spread fake news were conservative (66.6% of cases) and digital tabloids (13.3%) compared to 20% of media with a center and center-left political orientations. The television networks that broadcasted fake or inaccurate information during the time of analysis of the research were prone to the Republican candidate Donald Trump (40%) or conservative networks (30%) compared to the 30% whose political orientation was not specified by the fact-checkers. It can be assumed that at least 70% of the television networks that broadcasted false messages had an ideology close to that of the Republican candidate.

The vast majority of the media that attempted to disinform during the election were US nationals, although 19.2% of the media that disseminated false or erroneous information were foreigners (French news agency AFP; a Latin American media outlet—the conservative website Bles Mundo; two Spanish media—digital newspapers Libertad Digital and El Diestro, both on the right; and a Canadian media—the website Conservative Beaver).

The results showed that more than two-thirds of the disinformation sources preferred to use social networks to spread their messages instead of traditional media. The formats that originated a greater degree of disinformation were audiovisual—53.4% (videos, photographs, graphics and electoral maps)—compared to text format (posts)—46.4%. With regard to the media, these were a clear channel of support for the Republican candidate (around 70% of cases), both in the case of digital media and television networks.

4.3. Strategies of Disinformation

During the 2020 US presidential election, various types of disinformation strategies were used by the sources (social networks users, the media, the candidates and the members of their political entourage). First, and in line with the studies on political communication that have been recently published, two types of strategies were examined: the praise of the candidate’s virtues through false or inaccurate information and the dissemination of false claims on the political opponent (false statements or non-existent actions). Next, other disinformation strategies that emerged at specific times during the election were analyzed, such as the propagation of hoaxes on the official vote counting and the storming of the Capitol by a group of protesters dissatisfied with the election results.

Social networks users and the media resorted to the strategies of disinformation mentioned above in a similar way: they focused mostly on disseminating hoaxes on the official vote counting and the storming of the Capitol; secondly, they promoted the circulation of false claims on the political opponents; and finally, praised one of the candidates’ virtues through false or inaccurate information.

Social network users disseminated hoaxes on the election results in 58.3% of cases, circulated false claims on the political opponents in 30.5% of cases and misleadingly praised one of the candidate’s virtues in 11.1% of cases. This source of disinformation tended to endorse the Republican candidate’s profile, thesis and statements in a larger proportion of cases (Figure 5) by posting messages and re-disseminating data on social networks (Figure 6).

As an example, a set of pictures of an alleged massive march held in support of the Republican candidate during the 2020 US election was largely shared on social networks. In fact, the images were taken in 2016 when The Cavaliers (an American football team) won the national championship. Donald Trump’s supporters virally retweeted the message, which was first published on a satirical Twitter account [McNeil (@Reflog_18)].

The media, for their part, spread hoaxes on electoral fraud in 70.5% of cases, attributed false claims to the political opponents in 23.5% of cases and untruthfully praised the candidates’ virtues in 5.8% of cases. Similar to social networks users, both trusted and untrusted media principally supported the Republican candidate (Figure 7) by publishing news or posting messages on their own media spaces and social networks (Figure 8).

Some media, such as One America News Network (OAN), strongly sustained the allegations of electoral fraud launched by the outgoing president Donald Trump on his Twitter account. An OAN article published online during the election opened: “President Trump is pointing to the latest evidence of an illegal ballot-dump in Wisconsin. In a tweet Wednesday, the President said Democrat Joe Biden received a major dump of more than 143,000 ballots on the night after the election”. Further on, the text read: “Meanwhile, witnesses of voting fraud in Detroit, Michigan have come forward to detail alleged ballot dumps in favor of Biden. In a video testimony Wednesday, poll worker Kristina Karamo said she personally witnessed spoiled and invalid ballots being awarded to Biden”. Finally, the information was debunked by the fact-checkers of Lead Stories as well as by other national and local American media (The New York Times, Ballotpedia and The Milwaukee Journal Sentinel).

In that particular case, OAN employed a strategy of disinformation commonly used by traditional media. Nevertheless, other media and reporters turned to other strategies of disinformation specific of social media (Figure 9). Elijah Schaffer, journalist of Blaze TV, a conservative television network, spread the rumor on Twitter that more than 1000 mail-in ballots were found in a dumpster in California on September 2020. A few days later, the County of Sonoma (Petaluma, CA, USA) debunked this information, which was shared more than 2700 times. The photographs actually showed old empty vote-by-mail envelopes from the County of Sonoma that were thrown in recycling bins after the November 2018 election. Twitter finally removed Schaffer’s tweet.

The strategy of reinforcing the candidate’s public profile by spreading false or inaccurate information in his favor was used by the Republican candidate himself or by the members of his political entourage in 83.3% of the cases as opposed to the 16.6% of occasions in which this tactic was employed by the Democratic candidate and/or his entourage. The dissemination of fake news against the political opponent or his closest political entourage was used by the Republican candidate in a percentage of 72.4%, while the same tactic was used by the Democratic candidate in 27.5% of occasions. In the case of Joe Biden, the Democratic candidate, the use of false or inaccurate information was exclusively aimed at damaging the public image of Donald Trump, while the latter extended his strategy of disinformation to the whole entourage of Joe Biden (the candidate Vice President Kamala Harris, Joe Biden’s campaign manager, House Speaker Nancy Pelosi, the Democratic candidate’s wife and the candidate’s youngest son) (Figure 10).

The candidates used both social networks (30.8%) and traditional media (69.1%) to spread false information about the opponent or to enhance their own profile. Campaign events broadcasted or published by the media (statements at rallies, meetings with social groups, television advertisements) were those who disinform the most (12% of cases), followed by statements made in interviews published in digital media and television networks (9%) and in electoral debates broadcasted on television (2.4%), leaks to the press (4.8%) and official announcements (4.2%).

Despite its importance when influencing public opinion and determining the direction of the citizen’s vote, the major disinformation strategy that emerged throughout the 2020 US presidential election was neither of the two described previously but the dissemination of conspiratorial hoaxes on electoral fraud and the counting of votes, an issue that alone represented 58.4% of the total news items verified by the fact-checkers. That percentage should be added to the 7.8% of fake news on the storming of the Capitol that circulated afterwards. It is worth noting the high percentage of hoaxes reported on these two issues (66.2%) in relation to other disinformation strategies commonly used in political communication, such as the praise of the candidate’s virtues, which was applied in 3.6% of cases during the 2020 US election, and the dissemination of false claims on the political opponent, which was put into place in 17.4% of occasions.

Possibly, the success of the disinformation strategy based on the allegations of electoral fraud made public in the first place by the outgoing President Donald Trump resides in its ability to be echoed by other sources of disinformation that spread and amplified the fake news through social networks. This disinformation strategy turned out to be particularly effective since not only was it the one that generated the greatest volume of false information in circulation, but it was also capable of giving rise to successive topics of discussion (storming of the Capitol) that later produced its own hoaxes and fake news (Figure 11).

On the one hand, the results show the similarities listed between social networks users and the media when using classic political disinformation strategies against or in favor of a presidential candidate. On the other hand, the results also express the remarkable differences that exist between the two candidates who stood in the 2020 US presidential election in terms of the choice of political communication strategies based on the dissemination of false or misleading messages. Although both agreed on focusing their political criticisms on the adversary rather than praising their own virtues, the truth is that the Republican candidate tripled his efforts to disinform and harm his opponent, directing not only his criticism towards the adversary but also against his closest political and private entourage, which reveals an attitude more typical of an opposition candidate than a government candidate. On the other hand, it is shown that the Republican candidate has a greater knowledge of the effects that certain particularly successful disinformation strategies can produce, such as the dissemination of hoaxes on social networks, a channel that due to its own operating characteristics is more effective to spread fake news than traditional media.

5. Discussion

Most of the studies published in recent years on the prevailing role that social networks have played in the production of fake news during the implementation of a presidential election in the United States made think that this scenario would be reproduced in 2020. However, the results of the research showed that disinformation was distributed equally between social networks sources and the political candidates in an identical percentage of cases (40.9%). In that sense, the research is close to what is argued by Carlson (2020) and moves away from Molina and Magallón’s (2021) study on the 2019 Uruguayan presidential election and from the results of Paniagua et al. (2020) regarding the main sources of disinformation of the 2019 Spanish general election. Consequently, the first hypothesis of the research (“H1: The disinformation generated during the 2020 US presidential election came primarily from social networks sources”) would be refuted by the reported results.

On the other hand, the results showed that social networks were the channel for communication preferred by all kind of sources to disseminate fake news (Twitter in the first place, followed by Facebook and the rest of the social media analyzed). Conservative traditional media were used as a channel to convey false or inaccurate information in favor of the Republican candidate in a greater proportion (66.6% of digital media and 70% of television networks), coinciding with what was stated by Guo and Vargo (2018) in previous research. The research provides new data on how disinformation is disseminated through traditional media and the degree (32.5%) to which the media are used to misinform in the context of a general election.

The prevalence of social networks as a channel for disinformation was reported in 67.4% of cases for all the sources analyzed, except when candidates relied on classic political communication strategies in campaign time. In those cases, the candidates clearly turned to traditional media in a very high percentage of cases (69.1%). In that sense, the second hypothesis of the research (“H2: Social networks were the channel for communication most used to disseminate fake or misleading information”) would be partially verified by the results that were obtained.

With regard to the classic disinformation strategies set up by candidates, the research decided to follow Emmerich (2015) and include in the study not only the techniques that discredited the political opponent but also those that focused on praising the public profile of the candidate by using false or misleading information. However, the results did not show a large volume of disinformation reported in that direction (only 3.6% of cases). The candidates focused more on attacking each other through lies (17.4% of the time) than on praising themselves, although Donald Trump did it more than 70% of the time, whereas Joe Biden did not reach 28%. In that sense, and according to the results of previous research (Marcos et al. 2020; Paniagua et al. 2020), Donald Trump was the politician who employed more disinformation strategies that were typical of an opposition candidate.

The research brings new data on the way a particular typology of sources (social network users, traditional media and political candidates) makes use of equal strategies of disinformation during a polarized electoral process such as the 2020 US election. The disinformation strategies were both typical of political communication and electoral contests (misleading praise of the candidates’ virtues and circulation of false claims on the political opponent) and characteristic of the social media environment (dissemination of hoaxes on social networks). In that sense, the study has brought into light the existence of a series of new actors that play as important a role as the media or the political candidates when disseminating false or inaccurate information in an election campaign. The results show that both identified or anonymous social networks users tend to adopt the same practices and role models than trusted or untrusted media in a similar proportion (more than 85% of social networks users and the media untruthfully acclaimed Donald Trump’s virtues, between 75% and 90.9% spread false claims against Joe Biden and more than 95% circulated hoaxes on vote counting in support of the Republican candidate). Therefore, the third hypothesis (“H3: The sources of disinformation play similar role models when using classic and new disinformation strategies”) would be verified.

The use of disinformation strategies by political candidates generated a uniform level of disinformation throughout the period of study considered, however, this increased significantly in two key moments: when the Republican candidate and his entourage made allegations of electoral fraud and when a group of Donald Trump’s supporters stormed the Capitol. The use of Milner and Phillips’s (2016) personalization, victimhood and spectacularization strategies acted as a disruptive element that opened the door to the appearance of conspiracy theories on electoral fraud, which ultimately managed to increase the degree of disinformation reached so far. In line with Pyrhönen and Bauvois (2020), those strategies had a great echo on the general public and especially among Donald Trump’s followers who, unlike Uscinski et al.’s (2016) claim, seemed to have been much more responsive.

On the other hand, the results only partially coincide with Molina and Magallón’s findings (2021) and are in contradiction with Bozarth et al. (2020) on the progression of the level of disinformation observed during an electoral campaign, since the level of disinformation reported in the 2020 US election did not increase substantially as the electoral campaign approached or when the candidates held electoral debates, but when one of the candidates introduced a substantial change in the use of his disinformation strategies.

The last hypothesis of the research (“H4: The convergence of misleading communication strategies increased the level of disinformation generated by political candidates”) would be verified in as much as the level of disinformation was clearly increased at specific moments of the election season due to the employment of alternative disinformation strategies that outperformed the traditional ones used by the candidates.

As this research work is easily replicable, other researchers are encouraged to delve into the subject and expand the observation of the factors that were analyzed at this time (sources, channels and strategies of disinformation) in other electoral processes in the future. More in-depth studies on the typology of disinformation sources based on a wider sample of news items could be undertaken, as well as how new strategies of disinformation are applied in the context of a presidential election. It would also be particularly interesting to investigate other channels for disinformation such as mobile apps or chatbots and observe what effects fake news would provoke on the voters. In any case, other related lines of research would be welcomed.

6. Conclusions

The results of the research carried out on the 2020 US election showed that sources from social networks (anonymous or identified users) disinformed on equal terms with the political candidates (40.9% in both cases). Regarding the first type of sources, it can be affirmed that the vast majority were made up of anonymous users of social networks who made use of audiovisual resources (manipulated videos, pictures, graphics and electoral maps) to produce a greater degree of disinformation.

For their part, traditional media only disinformed in a limited percentage of cases (15.6%) and those that did so—both trusted and untrusted media—were conservative media or openly pro-Trump media (about 70% of cases). Joe Biden was the candidate least supported by these organizations, made up mostly by digital media and private American television networks. The channel for disinformation most used were social networks (67.4%), although the candidates resorted mostly to traditional media (69.1% of the time) to enforce classic disinformation strategies such as direct attacks on the adversary.

Regarding the use of disinformation strategies, it was noted that social networks users, the media and the political candidates generally used the same kind of techniques. Donald Trump was the candidate who most discredited his political opponent (72.4% of cases) and the one who best knew how to direct the timing and the strategies of disinformation. In that sense, he was able to generate a climate of controversy in which hoaxes could be rapidly spread at sensitive moments of the electoral race and be replicated by other sources of disinformation on alternative channels such as social networks. Likewise, the Republican candidate was able to effectively combine different disinformation techniques that he used extensively, although, in the end, these techniques were not useful to make him win the election.

Funding

This research received no external funding.

Data Availability Statement

Data supporting reported results (primary and secondary sources) can be found in the websites of the 10 fact-checking organizations analyzed. Three screenshots from a private Twitter account [McNeil (@Reflog_18)], OAN and France 24 websites were included for research purposes under a “Fair use” authorization.

Conflicts of Interest

The author declares no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures and Tables

Figure 1. Typology of disinformation sources in the 2020 US election. Source: Own formulation.

Figure 2. Media political orientation. (a) Trusted media; (b) Untrusted media. Source: Own formulation.

Figure 3. Channels for disinformation: social networks in the 2020 US election. Source: Own formulation.

Figure 4. Disinformation disseminated through traditional media in the 2020 US election. Source: Own formulation.

Figure 5. Strategies of disinformation disseminated by social networks users. Source: Own formulation.

Figure 6. False information on a massive march in support of Donald Trump. Source: Twitter [McNeil (@Reflog_18)]. Available online: https://bit.ly/3m1KLqg (accessed on 24 September 2021). “Fair use” screenshot.

Figure 7. Strategies of disinformation disseminated by the media. Source: Own formulation.

Figure 8. Article published by OAN, a conservative digital media, in support of Donald Trump’s electoral fraud allegations. Source: OAN website. Available online: https://bit.ly/3zE4Rf3 (accessed on 24 September 2021). “Fair use” screenshot.

Figure 9. Tweet shared by Blaze TV host Elijah Schaffer spreading rumors of electoral fraud. Source: France 24 website. Available online: https://bit.ly/39Agd9d (accessed on 24 September 2021). “Fair use” screenshot.

Figure 10. Disinformation disseminated by the Republican candidate against Joe Biden and his political entourage. Source: Own formulation.

Figure 11. Level of disinformation reported during the 2020 US election. Source: Own formulation.

Table 1

Fact-checking organizations that published verified information on their websites during the 2020 US presidential election.

Country	Organization	Area	Ownership
United States	PolitiFact	Digital	Private
	Snopes	Digital	Private
	Check Your Fact	Digital	Private
	Lead Stories	Digital	Private
United Kingdom	BBC Reality Check	Broadcasting	Public
France	AFP Fact Check	Digital	Public
	Les Observateurs de France 24	Broadcasting	Private
Spain	EFE Verifica	Digital	Public
	Maldita.es	Digital	Private
	Newtral	Digital	Private

Source: Own formulation.

Table 2

Sources of disinformation in the 2020 US election.

Source	Type
Traditional media	Trusted media
	Untrusted media
Public institution	The White House
Social media users	Identified users
	Anonymous users
Political candidates	Republican candidate and his entourage
	Democratic candidate and his entourage

Source: Own formulation.

References

Allcott, Hunt; Gentzkow, Matthew. Social media and fake news in the 2016 election. Journal of Economic Perspectives; 2017; 31, pp. 211-36. [DOI: https://dx.doi.org/10.1257/jep.31.2.211]

Benaissa Pedriza, Samia. Social media as news sources in Spanish digital media (“El País”, “El Mundo”, “La Vanguardia” and “ABC”). Index Comunicación; 2018; 8, pp. 13-42.

Bozarth, Lia; Saraf, Aparajita; Budak, Ceren. Higher Ground? How Groundtruth Labeling Impacts Our Understanding of Fake News about the 2016 U.S. Presidential Nominees. Paper presented at International AAAI Conference on Web and Social Media; Atlanta, GA, USA, June 8–11; 2020; vol. 14, pp. 48-59.

Caldevilla, David Domínguez. Democracia 2.0: La política se introduce en las redes sociales. Pensar la Publicidad; 2009; 3, pp. 31-48.

Cardenas, Alejandro; Ballesteros, Carlos; Jara, René. Social networks and electoral campaigns in Latin America. A comparative analysis of the cases of Spain, Mexico and Chile. Cuadernos Info; 2017; 41, pp. 19-40.

Carlson, Matt. Fake news as an informational moral panic: The symbolic deviancy of social media during the 2016 US presidential election. Information, Communication & Society; 2020; 23, pp. 374-88. [DOI: https://dx.doi.org/10.1080/1369118X.2018.1505934]

Chadwick, Andrew; Stanyer, James. Political Communication in Transition: Mediated Politics in Britain’s New Media Environment. Paper presented at Political Studies Association Annual Conference; Edinburgh, UK, March 29–April 1; 2010.

Chomsky, Noam; Herman, Edward S. Los Guardianes de la Libertad: Propaganda, Desinformación y Consenso en los Medios de Comunicación de Masas; Grijalbo Mondadori: Barcelona, 1995; ISBN 84-253-2820-9

Doshi, Anil R.; Raghavan, S.; Weiss, R.; Petitt, Eric. How the Supply of Fake News Affected Consumer Behavior during the 2016 US Election. Social Science Research Network (SSRN); 2018; 2020, pp. 1-79. [DOI: https://dx.doi.org/10.2139/ssrn.3093397]

Duan, Xinhuan Elham Naghizade; Spina, Damiano; Zhang, Xiuzhen. Profiling Fake News Spreaders on Twitter. Paper presented at CLEF 2020 Labs and Workshops; Thessaloniki, Greece, September 22–25; 2020.

Emmerich, N. Campaña de desinformación. Diccionario Enciclopédico de Comunicación Política; Martínez, Ismael Crespo; D’Adamo, Orlando; Beaudoux, Virginia García; Rodríguez, Alberto Mora. ALICE and Centro de Estudios Políticos y Constitucionales: Madrid, 2015; pp. 44-47.

Gallardo, Beatriz; Enguix, Salvador. Pseudopolítica: El Discurso Político en las Redes Sociales; Departamento del Lenguaje y Ciencias de la Comunicación, Universidad de Valencia: Valencia, 2016.

García Avilés, José Alberto. La desinformación. De Teoría de la Información y de la Comunicación; Herrero, Julio César. Universitas: Madrid, 2009; pp. 327-46. ISBN 978-84-7991-252-9

Gerber, Alan S.; Green, Donald P. The Effects of Canvassing, Telephone Calls, and Direct Mail on Voter Turnout: A Field Experiment. American Political Science Review; 2000; 94, pp. 653-63. [DOI: https://dx.doi.org/10.2307/2585837]

Guess, Andrew; Nagler, Jonathan; Tucker, Joshua. Less than you think: Prevalence and predictors of fake news dissemination on Facebook. Science Advances; 2019; 5, pp. 1-8. [DOI: https://dx.doi.org/10.1126/sciadv.aau4586]

Guo, Lei; Vargo, Chris. “Fake News” and Emerging Online Media Ecosystem: An Integrated Intermedia Agenda-Setting Analysis of the 2016 U.S. Presidential Election. Communication Research; 2018; 45, pp. 1-23. [DOI: https://dx.doi.org/10.1177/0093650218777177]

Hall Jamieson, Kathleen. Cyberwar: How Russian Hackers and Trolls Helped Elect a President: What We Don’t, Can’t, and Do Know; Oxford University Press: Oxford, 2018; ISBN 13: 9780190058838

Hameleers, Michael; Van der Meer, Toni G. L. A. Misinformation and polarization in a high-choice media environment: How effective are political fact-checkers?. Communication Research; 2019; 47, pp. 227-50. [DOI: https://dx.doi.org/10.1177/0093650218819671]

Hedman, Urlika; Djerf-Pierre, Monika. The Social Journalist. Embracing the social media life or creating a new digital divide?. Digital Journalism; 2013; 1, pp. 368-85. [DOI: https://dx.doi.org/10.1080/21670811.2013.776804]

Journell, Wayne. Fake news, alternative facts, and Trump: Teaching social studies in a post truth era. Social Studies Journal; 2017; 37, pp. 8-21.

Jungherr, Andreas. Twitter use in election campaigns: A systematic literature review. Journal of Information Technology & Politics; 2016; 13, pp. 72-91. [DOI: https://dx.doi.org/10.1080/19331681.2015.1132401]

Kwak, Haewoon; Lee, Changhyun; Park, Hosung; Moon, Sue. What is Twitter, a social network or a news media?. Paper presented at 19th International Conference on World Wide Web; Raleigh, NC, USA, April 26–30; 2010; pp. 591-600.

Lasorsa, Dominic L.; Lewis, Seth C.; Holton, Avery E. Normalizing Twitter: Journalism Practice in an Emerging Communication Space. Journalism Studies; 2012; 13, pp. 19-36. [DOI: https://dx.doi.org/10.1080/1461670X.2011.571825]

Lee, Terry. The global rise of “fake news” and the threat to democratic elections in the USA. Public Administration and Policy; 2019; 22, pp. 15-24. [DOI: https://dx.doi.org/10.1108/PAP-04-2019-0008]

Lilleker, Darren G.; Tenscher, Jens; Štětka, Václav. Towards Hypermedia Campaigning? Perceptions of New Media’s Importance for Campaigning by Party Strategists in Comparative Perspective. Information, Communication & Society; 2015; 18, pp. 747-65. [DOI: https://dx.doi.org/10.1080/1369118X.2014.993679]

Magallón, Raúl. Unfaking News. Cómo combatir la desinformación; Ediciones Pirámide: Madrid, 2019; ISBN 978-84-368-4105-3

Magin, Melanie; Podschuweit, Nicole; Haßler, Jörg; Russmann, Uta. Campaigning in the Fourth Age of Political Communication. A Multi-method Study on the Use of Facebook by German and Austrian Parties in the 2013 National Election Campaigns. Information, Communication & Society; 2017; 20, pp. 1698-719. [DOI: https://dx.doi.org/10.1080/1369118X.2016.1254269]

Marcos, Silvia; Viounnikoff-Benet, Nadia; Casero-Ripollés, Andreu. ¿Qué hay en un like? Contenidos políticos en Facebook e Instagram en las elecciones autonómicas valencianas de 2019. Debats; 2020; 134, pp. 91-116. [DOI: https://dx.doi.org/10.28939/iam.debats.134-1.6]

Milner, Ryan; Phillips, Whitney. Dark Magic: The memes that made Donald Trump’s victory. US Election Analysis 2016: Media, Voters and the Campaign; 1st ed. Lilleker, Darren; Jackson, Daniel; Thorsen, Einar; Veneti, Anastasia. The Centre for the Study of Journalism, Culture and Community, Bournemouth University: Poole, 2016; pp. 84-85. ISBN 978-1-910042-11-3

Molina, Juan Pedro; Magallón, Raúl. Desinformación y fact-checking en las elecciones uruguayas de 2019. El caso de Verificado Uruguay. Perspectivas de la Comunicación; 2021; 14, pp. 89-112. [DOI: https://dx.doi.org/10.4067/S0718-48672021000100089]

Nyhan, Brendan; Reifler, Jason; Ubel, Peter A. The Hazards of Correcting Myths about Health Care Reform. Medical Care; 2013; 51, pp. 127-32. [DOI: https://dx.doi.org/10.1097/MLR.0b013e318279486b]

Owen, Diana. El papel de los nuevos medios en la política. La Era de la Perplejidad; Taurus: Madrid, 2018.

Paniagua, Francisco; Pérez, Francisco Seoane; Magallón, Raúl. An anatomy of the electoral hoax: Political disinformation in Spain’s 2019 general election campaign. CIDOB d’Afers Internacionals; 2020; 124, pp. 123-45. [DOI: https://dx.doi.org/10.24241/rcai.2020.124.1.123]

Parmelee, John H.; Bichard, Shannon L. Politics and the Twitter Revolution: How Tweets Influence the Relationship between Political Leaders and the Public; Lexington Books: Lanham, 2011; ISBN 978-0-7391-6500-3

Peter, Christina; Koch, Thomas. Countering misinformation: Strategies, challenges, and uncertainties. Studies in Communication and Media; 2019; 8, pp. 431-45. [DOI: https://dx.doi.org/10.5771/2192-4007-2019-4-431]

Pew Research Center. Social Media Outpaces Print Newspapers in the U.S. as a News Source. 2018; Available online: https://pewrsr.ch/2UvWPSe (accessed on 4 August 2021).

Pyrhönen, Niko; Bauvois, Gwenaëlle. Conspiracies beyond Fake News. Producing Reinformation on Presidential Elections in the Transnational Hybrid Media System. Sociological Inquiry; 2020; 90, pp. 705-31. [DOI: https://dx.doi.org/10.1111/soin.12339]

Rodríguez Andrés, Roberto. Fundamentos del concepto de desinformación como práctica manipuladora en la comunicación política y las relaciones internacionales. Historia y Comunicación Social; 2018; 23, pp. 231-44. [DOI: https://dx.doi.org/10.5209/HICS.59843]

Rossini, Patrícia; Stromer-Galley, Jennifer; Korsunska, Ania. More than “Fake News”? The media as a malicious gatekeeper and a bully in the discourse of candidates in the 2020 U.S presidential election. Journal of Language and Politics; 2021; 20, pp. 1-20. [DOI: https://dx.doi.org/10.1075/jlp.21033.ros]

Shin, Jieun; Jian, Lian; Driscoll, Kevin; Bar, François. Political rumoring on Twitter during the 2012 US presidential election: Rumor diffusion and correction. New Media & Society; 2016; 19, pp. 1214-35. [DOI: https://dx.doi.org/10.1177/1461444816634054]

Silverman, Craig. This analysis shows how viral fake election news stories outperformed real news on Facebook. BuzzFeed.; 2016; Available online: https://www.buzzfeednews.com/article/craigsilverman/viral-fake-election-news-outperformed-real-news-on-facebook (accessed on 4 August 2021).

Spohr, Dominic. Fake news and ideological polarization: Filter bubbles and selective exposure on social media. Business Information Review; 2017; 34, pp. 150-60. [DOI: https://dx.doi.org/10.1177/0266382117722446]

Stromer-Galley, Jennifer. Presidential Campaigning in the Internet Age; Oxford University Press: New York, 2014; ISBN 13: 9780199731930

Uscinski, Joseph; Klofstad, Casey; Atkinson, Matthew D. What Drives Conspiratorial Beliefs? The Role of Informational Cues and Predispositions. Political Research Quarterly; 2016; 69, pp. 57-71. [DOI: https://dx.doi.org/10.1177/1065912915621621]

Van-Dijck, José. Users like you? Theorizing agency in user-generated content. Media, Culture & Society; 2009; 31, pp. 41-58. [DOI: https://dx.doi.org/10.1177/0163443708098245]

Verweij, Peter. Twitter Links between Politicians and Journalists. Journalism Practice; 2012; 6, pp. 680-91. [DOI: https://dx.doi.org/10.1080/17512786.2012.667272]

Volkoff, Vladimir. La Désinformation, Arme de Guerre; Julliard: Paris, 1986; ISBN 10: 2260004415

Vosoughi, Soroush; Roy, Deb; Aral, Sinan. The Spread of True and False News Online. Science; 2018; 359, pp. 1146-51. [DOI: https://dx.doi.org/10.1126/science.aap9559] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/29590045]

Waisbord, Silvio. The elective affinity between post-truth communication and populist politics. Communication Research and Practice; 2018; 4, pp. 17-34. [DOI: https://dx.doi.org/10.1080/22041451.2018.1428928]

Wardle, Claire. Information Disorder. Part 3: Useful Graphics. First Draft; 2018; Available online: https://bit.ly/2wjjRAx (accessed on 4 August 2021).

Williams, Christine B.; Gulati, Girish J. Social networks in political campaigns: Facebook and the 2006 congressional elections of 2006 and 2008. New Media & Society; 2013; 15, pp. 52-71. [DOI: https://dx.doi.org/10.1177/1461444812457332]

Wintersieck, Amanda. L. Debating the Truth: The Impact of Fact-Checking During Electoral Debates. American Politics Research; 2017; 45, pp. 304-31. [DOI: https://dx.doi.org/10.1177/1532673X16686555]

Wood, Thomas; Porter, Ethan. The elusive backfire effect: Mass attitudes’ steadfast factual adherence. Political Behavior; 2018; 41, pp. 135-63. [DOI: https://dx.doi.org/10.1007/s11109-018-9443-y]