The United States presidential elections of 2024: Disinformation denied by Spanish fact-checking platforms 

 

Álvaro López-Martín

University of Malaga. Spain. 

alvarolopezmartin@uma.es

 

How to Cite This Article / Standard Reference:

López-Martín, Álvaro. (2026). The United States presidential elections of 2024: Disinformation denied by Spanish fact-checking platforms. Revista Latina de Comunicación Social, 84, 1-29. https://www.doi.org/10.4185/RLCS-2026-2513

Date of Receipt: May 9, 2025
Date of Acceptance: September 7, 2025
Date of Publication: November 14, 2025

ABSTRACT

Introduction: The 2024 U.S. presidential election has created an environment ripe for disinformation, leaving the public more vulnerable to manipulation when making decisions. This article explores the disinformation landscape concerning the elections. Methodology: The five Spanish fact-checking platforms belonging to the IFCN (Maldita.es, Newtral, EFE Verifica, Infoveritas, and Verificat) published fact-checks on this topic between June 27 and November 12, 2024. A total of 204 fact-checks were analyzed. All pieces of content were subjected to a structured analysis framework divided into four sections. Results: These messages reveal a significant role for audiovisual elements, as well as a growing use of artificial intelligence. While most of these pieces lack an identified source (67.2%), a significant proportion of the false claims are attributed to real sources (19.1%). Disinformation is thus confirmed as a common political tool in Trump's discourse. The reported events are generally entirely fabricated (59.3%) and focus on the candidates' private lives or pasts (19.1%) and the alleged assassination attempt on Trump (13.7%). Discussion and Conclusions: This phenomenon is a widespread and established practice in electoral processes and political discourse, which constantly develop and evolve toward new techniques. In this case, this evolution is marked by the rise of and easy access to AI tools.

Keywords: disinformation, United States, elections, misinformation, Spain, fact-checking, politics.

1. INTRODUCTION

The U.S. presidential election on November 5, 2024, was one of the most significant international political events that year. Even months before the election, it generated remarkable media and public interest. While any electoral process usually attracts attention (Haugsgjerd & Karlsen, 2024), the United States' economic and strategic importance amplifies interest in the country's political developments, while also generating misinformation surrounding them. In this case, a series of circumstances created an atypical electoral process that served as fertile ground for numerous hoaxes and false information. Examples include Biden's withdrawal from the presidential race and the attempted assassination of Donald Trump during a campaign event in July 2024.

These elections were marked by intense political polarization and a transformation of the voter profile for each political party. The contest between Donald Trump and Kamala Harris was politically charged, reflecting tensions and ideological divergences on issues such as the economy, immigration, and civil rights. These issues frequently took center stage in the debate (Al Jazeera, 2024; Marín, 2024). Socially, the electorate underwent a certain reconfiguration, with Trump gaining support from groups typically not associated with the conservative vote, such as young people and minorities. Meanwhile, Harris appealed to progressive voters and the urban electorate (Pipa & Swarzenski, 2024; BBC News, 2024). The elections also represented a significant transformation in media coverage. The strategic use of social media, the influence of social media personalities, and the creation of personalized content largely replaced traditional channels, consolidating fragmented information environments (Brooks & Wellman, 2024; Cahill, 2025). After this tumultuous election, Trump won the presidency with 312 electoral votes, compared to Harris's 226. This victory marked Trump's return to the White House after his first term (2017-2021). His victory can be attributed, in part, to his ability to garner support from diverse social sectors and his effective communication strategy on social media (FitzGerald, 2024).

Numerous studies have highlighted Donald Trump's role as a key player in the phenomenon of disinformation (Diez-Gracia et al., 2023; McKee & Pagel, 2024; Rossetti & Zaman, 2023). These studies reveal several characteristics of the “Trumpist” narrative: intentional use of social media (primarily X) and chatbots (Farkas & Schou, 2020; Rossetti & Zaman, 2023); labeling any information detrimental to his image as “fake” (Ross & Rivers, 2018); and reliance on a network of like-minded sources to reproduce and disseminate his messages, contributing to an “illusory truth” effect (Froehlich, 2020). According to the scientific literature, Trump's victory in the 2016 election could be considered a turning point in the rise and popularization of disinformation (Tandoc et al., 2021). Since then, disinformation has become an omnipresent threat to democratic principles and freedom of expression (Huber et al., 2022; Sádaba & Salaverría, 2023). This situation has been exacerbated by the uncontrolled development of AI (Yan et al., 2025).

Several authors (Lava-Santos et al., 2023; Pérez-Curiel et al., 2022) have warned that disinformation seems to have permeated political discourse in recent years. Although countries such as the United States and several in the European Union have enacted regulations regarding disinformation and electoral advertising (Rodríguez-Virgili et al., 2024), one might infer that political parties have normalized lying by using social media to produce and disseminate propaganda based on virality (Dehlinger & Scala, 2024). This is a form of political dysfunction in which the media are frequently, and sometimes unintentionally, involved (Wardle, 2021). Several key moments can be identified in relation to disinformation in electoral processes. Stachofsky et al. (2023) and González-Bailón et al. (2024) highlight the flow of disinformation generated during election campaigns, especially on election day. Furthermore, although the volume of misleading content decreases after election day, Enders et al. (2021) observed that, after the 2020 U.S. presidential elections, narratives focusing on electoral fraud gained traction in the days following the vote. These narratives aimed to undermine the legitimacy of the electoral process.

This research focuses on disinformation disseminated in Spain regarding the 2024 U.S. presidential elections. Although Spain is not directly involved in these elections, their impact transcends borders, making them a topic of great international relevance. Increasing political polarization and the use of social media as platforms for dissemination have created an environment conducive to disinformation, exposing Spanish citizens to misleading narratives that can influence their perception of global politics. In this context, it is crucial to not only identify and analyze these falsehoods, but also develop strategies to neutralize disinformation and promote clearer understanding of the facts.

2. LITERATURE REVIEW

2.1. The phenomenon of disinformation: characteristics, evolution and credibility

Over the past decade, there has been a growing interest in the phenomenon of disinformation, as evidenced by the abundant scientific literature published on the topic. However, there is a lack of consensus and clear definition regarding its conceptualization (Baptista & Gradim, 2022a; García-Marín & Salvat-Martinrey, 2022). This positions disinformation as a “complex and somewhat controversial” topic of study (Tandoc et al., 2021, p. 111). Nevertheless, an underlying characteristic emerges from nearly all the definitions in the numerous works on this subject: these messages exhibit a clear intention to deceive (Baptista & Gradim, 2022a; García-Marín, 2021). Some semantic confusion is evident when addressing this phenomenon (Baptista & Gradim, 2022a; Tandoc et al., 2021). Initially, the predominant term used for this problem was “fake news” (Farkas & Schou, 2020; Koliska & Assmann, 2021). However, numerous authors reject this term because it has strong political connotations (Freelon & Wells, 2020) and focuses almost exclusively on journalism (Allcott & Gentzkow, 2017; Salaverría-Aliaga, 2021). Consequently, the European Commission and various government reports (European Commission, 2018; Torreblanca et al., 2024) advocate using the terms “disinformation” and “misinformation,” as they are considered more precise and less biased (Wardle & Derakhshan, 2017). In any case, these works all agree that the formats and narratives used to construct fraudulent content are constantly evolving.

Technological advancements and digitalization are making decisive contributions in this regard. They are also enabling the creation of increasingly sophisticated and difficult-to-detect hoaxes (Almansa-Martínez et al., 2022; Michałkiewicz-Kądziela, 2024). The impact of artificial intelligence on image creation, audio editing, and the emergence of new disinformation variants (Yan et al., 2025), such as deepfakes (Weikmann et al., 2024), is noteworthy. Deepfakes are fabricated videos that deliberately show someone doing or saying something that did not actually happen (Ballesteros-Aguayo & Ruiz-del-Olmo, 2024). However, initial studies suggest that the use of AI is not yet widespread (García-Marín & Salvat- Martinrey, 2023). Nonetheless, research on deepfakes indicates that these hoaxes can significantly impact attitudes and behaviors toward the media and politicians (Hameleers et al., 2022). This could be explained by Geise (2017), whose work suggests that visual disinformation is processed differently from textual misinformation.

Psychology plays a leading role in the process of receiving disinformation, especially when the messages are strongly political (Baptista & Gradim, 2022b). Baptista et al. (2021) point out that citizens seek “informative content compatible with their worldview (opinion, values, or beliefs), even if it is false” (p. 25), demonstrating ideological concordance in their information-seeking behavior. Freiling et al. (2023) express similar views, arguing that audiences give greater credibility to messages they want to believe, a tendency exacerbated when the content aligns with their ideologies. The extensive scientific literature on this topic suggests that, in general, individuals with right-wing ideologies —especially those on the far right (Baptista et al., 2021)— would be, a priori, the most vulnerable or prone to giving credibility to and spreading misleading content (Baptista & Gradim, 2022b; Gómez-Calderón et al., 2023). However, its impact is also present, albeit to a lesser extent, across other ideologies and political sensibilities (Faragó et al., 2020).

Baptista (2023) explains this tendency by highlighting the close similarity between the populist narratives of extremist groups and the persuasive narratives that characterize disinformation. Pennycook and Rand (2019) portray citizens as “victims” of disinformation because they are unable to make rational decisions in these situations, which nullifies their critical thinking abilities. Several authors (Pérez-Curiel & Rivas-de-Roca, 2022; Melchior & Oliveira, 2023) argue that fraudulent content is underestimated because it evokes emotions. Faragó et al. (2020) further explore this issue, arguing that emotions play a crucial role when misinformation evokes sympathy or prejudice in the recipient. This could lead to an increased use of social media and the subsequent training or refinement of algorithms.

Regarding the typology of fraudulent content, controversy arises in light of the numerous proposed classifications. One of the most widespread classifications was proposed by Allcott and Gentzkow (2017). It establishes six categories: rumors, false statements by politicians, conspiracy theories, unintentionally erroneous information, misinterpreted satire, and distorted reports. Tandoc et al. (2018) also aim to classify disinformation and propose the following categories: satirical news, manipulated news, parodies, fabricated news, advertising, and propaganda. The inclusion of the last two categories, advertising and propaganda, is perhaps the main element that differentiates this classification from others found in scientific literature. Despite being independent practices or disciplines, these authors consider advertising and propaganda elements of disinformation. This corroborates the “multidimensional” nature of the phenomenon (Valera-Ordaz et al., 2022). For this study, however, the taxonomy of Salaverría et al. (2020) will be used as a basis. These authors developed a more concise categorization structured around four modalities: deception (absolutely fabricated information), decontextualization (real information presented in a false context), exaggeration (real facts that exceed the limits of veracity), and jokes (content with a satirical or mocking purpose).

2.2. Social networks, key channels for the rise of disinformation

The importance of digitalization and technology in spreading disinformation has been emphasized, and social media deserves special mention. The literature consistently identifies social media, and to a lesser extent, websites as one of the main reasons for the growth and popularization of this phenomenon (Batailler et al., 2022; Tandoc et al., 2021; Valera-Ordaz et al., 2022). These channels are ideal for rapidly and widely disseminating messages of unknown origin, free from any control or verification filters. These messages can “go viral” in a short period of time (Strauß et al., 2021), which exacerbates citizens' vulnerability to manipulation (Altay et al., 2023). Dehlinger and Scala (2024) argue that fraudulent content is more likely to be shared while real news generates more comments and reactions.

Due to their peculiar characteristics, social media is a fertile ground for the spread of hoaxes (Montemayor-Rodríguez & García-Jiménez, 2021). These channels disrupt the traditional flow of information, a phenomenon that authors such as Román-San-Miguel et al. (2022) refer to as the “democratization” of information. In other words, the flow of information becomes bidirectional, and any user can produce and disseminate messages (Ruiz-Incertis et al., 2024). However, there is some disparity in the attributed incidence of each application or social network in the dissemination process.

Several studies (Almansa-Martínez et al., 2022; Ruiz-Incertis et al., 2024) identify X as the primary channel for dissemination, while others focus on Facebook (Martín-Neira et al., 2023). Some studies identify WhatsApp as the application with the highest volume of misinformation (Peña-Ascacíbar et al., 2021) and warn about the dangerous potential of other networks, such as TikTok, for disseminating fraudulent content (López-Martín & Córdoba-Cabús, 2024; Sidorenko-Bautista et al., 2021). In any case, the ease with which messages can be created and disseminated on these platforms poses a threat to democracy. This threat is exacerbated by Meta's recent announcement that it will close its fact-checking program in the United States (Scire, 2025).

2.3. Fact-checking to combat disinformation

As Bastick (2021) points out, the effects of disinformation are “small at the individual level,” but they could be “enough to produce large-scale results” (p. 1). This is why there is a unanimous need to combat this problem (Baptista & Gradim, 2022a; Pérez-Escolar et al., 2023). Following the popularization and rise of disinformation, media outlets dedicated to verifying disseminated content have emerged in recent years. These verification or fact-checking platforms (Kloss Medina & Louit Carrasco, 2024) intensify their work during election periods (Rodríguez-Hidalgo et al., 2021). The growth of these entities is so significant that Kyriakidou et al. (2023) consider it a “professional reform.” While some authors distinguish this practice from traditional journalism (Graves, 2016; Herrero-Diz et al., 2022), others consider fact-checking platforms journalism's response to disinformation. These platforms have transformed the internal journalistic procedure of data verification into a business focused on the general public (Esteban-Navarro et al., 2021).

According to Graves's (2017) study, fact-checking platforms can be categorized as follows:

1. civic platforms driven by civil society,
2. act-checking pages linked to media outlets;
3. autonomous entities or media outlets dedicated to fact-checking, such as Maldita.es or Newtral.

In Spain, as López-Pan and Rodríguez-Rodríguez (2020) point out, the first two types play a negligible role. These authors conclude that fact-checking by conventional media is still in an “incipient phase” in Spain because only during electoral processes is a surge in attention paid to it, as observed by López-Pan and Rodríguez-Rodríguez (2020, p. 1060).

Méndez-Muros et al. (2024) define a fact-checker as a journalist responsible for verifying all data in published information. They use primary and reliable sources to verify reported facts (Méndez-Muros et al., 2024). Additionally, they use technological or digital tools (Herrero-Diz et al., 2022; Soo et al., 2023) and collaborate with other fact-checkers (Brookes & Waller, 2022). Notably, Blanco-Alfonso et al. (2021) provide an overview of the work of fact-checkers at Newtral, who predominantly use government and media sources to verify information. Furthermore, the study by López-Martín and Córdoba-Cabús (2024) shows that Spanish fact-checkers notably use digital tools and applications for these tasks.

Although fact-checking and verification platforms originated as a tool for controlling political discourse (Graves & Glaisyer, 2012), these media became popular primarily due to the Covid-19 pandemic (García-Marín et al., 2023). As of April 1, 2025, the Duke Reporters’ Lab had registered 450 fact-checking platforms internationally, 148 of which belong to the International Fact-Checking Network (IFCN). Notable entities belonging to this organization include: Maldita.es, Newtral, Verificat, EFE Verifica, and Infoveritas.

In general, the scientific literature emphasizes the informational and pedagogical benefits of fact-checking platforms (Casero-Ripollés et al., 2023; Lee et al., 2022), though it also identifies areas for improvement. Herrero and Herrera-Damas (2021) and García-Marín et al. (2023) point out that the fact-checking process is sometimes too slow. Therefore, they indicate that one of the main challenges for verification platforms is checking misleading content in real time. Some studies question the usefulness of these platforms, citing their limited impact on audiences (Vinhas & Bastos, 2022) and their potential to amplify fraudulent messages (Tuñón-Navarro & Sánchez-del-Vas, 2022).

3. OBJECTIVES

This research aims to explore the disinformation network surrounding the U.S. presidential election on November 5, 2024. To this end, this study will analyze the characteristics and features of misleading messages about these elections disseminated in Spain. The goal is twofold: first, to enrich the scientific literature on political disinformation; and second, to provide comprehensive and accurate knowledge about the strategies and narratives used to create fraudulent content. This is based on the premise put forth by Magallón-Rosa (2019) that new methods of disinformation and deception emerge after each election period.

To be more specific, five subsidiary objectives were established. The first objective (O1) aimed to determine the communicative codes or formats through which fraudulent content is presented and the temporal sequence of electoral disinformation dissemination, in order to identify key periods subject to disinformation. Objective 2 (O2) aimed to explore the formal characteristics related to the architecture of hoaxes, focusing on their typology and the sources to which the information in the messages is attributed. Linked to the previous objective, the third objective (O3) consisted of examining the topic and the person or group that is the subject of the false claim. The fourth objective (O4) focused on the characteristics of untrue discourse, analyzing issues such as narrative style, vocabulary, presence of statements, and purpose of the message. Finally, based on information from fact-checks published by fact-checking platforms, objective 5 (O5) aimed to determine the channels through which misleading content is disseminated and the media coverage it receives. This objective also aimed to quantify and categorize the information sources used by fact-checking journalists to verify false claims, as well as to compare professionals from the different fact-checking platforms under study.

4. METHODOLOGY

4.1. Method and sample

To achieve the proposed objectives, content analysis was used as a heuristic tool. This quantitative technique was chosen because it is suitable for studying media messages, such as misinformation (Krippendorff, 1990; Lombard et al., 2002), and because of its instrumental flexibility and versatility, which allow it to address the meanings and signifiers of communication (Igartua, 2006).

The focus was on hoaxes related to the 2024 US presidential elections that were disseminated in Spain. To this end, 204 fact-checks on this topic published by five Spanish fact-checking platforms belonging to the International Fact-Checking Network (IFCN) between June 27, 2024 (the date of the first electoral debate between Joe Biden and Donald Trump) and November 12, 2024 (the week after the elections) were selected. This broad time period was considered representative for drawing a reliable and accurate picture of the disinformation generated around the U.S. elections because it covered the pre-election period, the campaign, the voting process, and the initial reactions to the results. The sample was composed as follows: Maldita.es (n=77), Newtral (n=49), EFE Verifica (n=32), Infoveritas (n=41), and Verificat (n=5). Fact-checks about the U.S. elections were considered those hoaxes referring to candidates, government decisions, the electoral process, voting, and/or other diverse matters (social, health, economic, etc.) concerning the United States presented from a political perspective.

Each published fact-check was considered an independent unit of analysis for the composition of the sample, even in cases where different fact-checkers debunked the same content. This decision stems from the nature of objective five (O5), which aims to identify and quantify the information sources that fact-checkers use to verify information. While this criterion may lead to overrepresentation of certain debunked claims, it is appropriate to explore the characteristics of electoral disinformation, understand the information sources consulted by these professionals, and conduct a more comprehensive comparison of the sources used by fact-checkers from different fact-checking platforms.

4.2. Analysis sheet

All hoaxes were analyzed using a form based on previous research on disinformation and the anatomy of hoaxes (Blanco-Alfonso et al., 2021; García-Marín & Salvat-Martinrey, 2023; López-Martín et al., 2021; Salaverría et al., 2020; Sánchez-Duarte & Magallón, 2020). Ad hoc variables related to the study's objectives were added to this form. Before analyzing the sample, a pretest was conducted with 10% of the pieces to refine the variables and categories included in the analysis form. The resulting form was structured into four sections:

1. Registration Information: Composed of the identifying variables of the publication to be analyzed, such as the publication date and verification entity.
2. Formal analysis: Formal Analysis: This section includes nominal and scale variables related to the construction and production of the hoax. These variables include format, theme, the message's protagonist, hypertextuality, and geographical scope. Format refers to the medium or communicative code through which the hoax is presented. It can be used alone or in combination with other formats, such as plain text, video, photographs, audio, infographics, embedded text, etc. Theme refers to the event on which the narrative focuses. Examples include endorsements from public figures, arrests/crimes, debates, government decisions, controversial statements, election results, resignations, immigration, attempted murder, candidates' past or private lives, loss of physical or mental faculties, and campaign promises, among others. The message's protagonist is categorized as personal or impersonal. Finally, it also includes hypertextuality (yes/no), and the geographical scope to which the message refers.
3. Message Analysis: Message Analysis: This section comprises variables related to the linguistic sequence and the intent of the message. It includes nominal variables such as the source of disseminated information, which follows the categorization of Salaverría et al. (2020): real, anonymous, fictitious, or impersonated. It also includes the type of hoax, which uses the same classification as Salaverría et al. (2020): joke, deception, exaggeration, or decontextualization. Other variables include the language used (specialized/technical or everyday/colloquial), the narrative style (informative, interpretive, or opinion-based), the presence of statements or testimonies in the message (yes or no), and the purpose and direction of the falsehood (against the Democratic Party, against the Republican Party, or neutral).
4. Verification: This final section focuses on the work of fact-checkers and analyzes the information available about them in fact-checks published by verification platforms. The following variables are identified: Sources consulted by the fact-checkers to verify the information. For better analysis, the sources are categorized as follows: governmental; non-governmental political; academic; associations, NGOs, or organizations; media and journalists; digital resources, and more. The promoter of the hoax is identified (if, after the verification process, they manage to determine who generated the fraudulent content). The means of dissemination are identified (the channels through which the messages are spread: social networks, messaging applications, websites, emails, media, etc.). Evidence of the use of AI is identified (yes/no).

Subsequently, a data matrix was generated in SPSS (V27.0) using the information extracted from each piece to perform descriptive and inferential statistical analyses and identify possible relationships between the considered variables. The Chi-square (χ²) test was used to detect associations at a 95% confidence level. Multiple linear regressions were also performed at the same confidence level; however, these did not yield statistically significant results. Due to space limitations, the results section only presents the operations that showed significant associations between the examined variables. A single person coded the denials. However, to ensure the reliability of the analysis, 10% of the pieces were reexamined 10 weeks later. This yielded intra-coder reliability scores ranging from 0.90 to 1.00 (Holsti) and from 0.86 to 1.00 (Krippendorff's alpha). These values indicate high reliability and reinforce the validity of the analysis process.

5. RESULTS

5.1. Temporality and communicative code

The analysis revealed that, in the months leading up to the election, the United States presidential elections were the target of continuous disinformation and fraudulent content. Two periods stand out, with slight increases occurring in the second half of July (21.1%) and from the second half of October until Election Day (34.3%). Specifically, these periods were the time following the attempted assassination of Donald Trump in Butler, Pennsylvania, on July 13 and the final stretch of the election campaign and voting.

Based on the architecture of the deceptions, the visual component (whether photograph or video) played a significant role in constructing the message and lending verisimilitude to the narrative. In most cases, the visual component emerges as a complement to a textual narrative, through which the image is contextualized and explained. Specifically, fraudulent content combining text and video (41.7%) or text and photographs (31.4%) predominated (Figure 1).

Figure 1. The Communicative Code of Hoaxes.

Source: Elaborated by the author.

In cases where the duration of the videos can be identified, there is a tendency to use short videos in order to capture and maintain the viewer's attention. The majority of videos (78.4%) are under 40 seconds long.

5.2. Attributed source

Most of the sample (67.2%) lacks an identified source, so the information is not attributed to any person, institution, or media outlet. Around one-fifth of the videos (19.1%) are attributed to real sources who started the hoax. The use of disinformation as a common political tool of the Republican Party is evident in this sense, although falsehoods originating from the Democratic Party are also recorded. Notable among the misinformation created —or at least disseminated— by Republican Donald Trump are three main channels: 1) social media, 2) presidential debates, and 3) campaign rallies. These messages are closely linked to the topic of immigration. For example, Trump claimed that Haitian immigrants in the United States kill and eat neighborhood cats. This claim was spread during the debate and on social media (Infoveritas, 2024b).

Another prominent example of misinformation is Trump's post on Truth Social, his social network, in which he claims that Taylor Swift supports his candidacy. However, the singer herself endorsed Kamala Harris (Infoveritas, 2024a). Other participants in the construction and dissemination of misinformation include political representatives from the Republican Party (such as Congresswoman Marjorie Taylor Greene), associations and entities (such as Blexit, an African-American movement against the Democratic Party), and figures close to candidate Trump (such as Elon Musk, the entrepreneur and owner of Tesla and X). To a lesser extent, the Democratic candidate has constructed disinformation narratives as well; however, her message tone could be considered a differentiating factor. In these cases, fraudulent content originating from Harris focuses almost exclusively on highlighting the Biden administration's and Harris's supposed achievements, such as the false claim of halving fentanyl consumption (Verificat, 2024). Statistical tests revealed a correlation between the type of source supporting the information and the meaning of the message. The majority of anonymous attributions (56.9%) and real attributions (59%) refer to messages against the Democratic Party (χ² (6, N=204)=17.279, p<0.05) (Table 1). In contrast, the participation of satirical digital media and/or bot profiles barely reaches noteworthy levels.

Table 1. Source attributed based on the hoax attacks.

	Neutral	Against the Republican Party	Against the Democratic Party
Anonymous (n=137)	33 (24.1%)	26 (19%)	78 (56.9%)
Fictitious (n=3)	1 (33.3%)	1 (33.3%)	1 (33.3%)
Real (n=39)	15 (38.5%)	1 (2.6%)	23 (59%)
Impersonated (n=25)	8 (32%)	9 (36%)	8 (32%)
Total	57 (27.9%)	37 (18.1%)	110 (53.9%)

Source: Elaborated by the author.

In 12.3% of the cases, the information is attributed to impersonated sources. Three types of impersonation can be distinguished:

1. Forged news articles supposedly published in media outlets, such as Time magazine or Fox News. These impersonations predominantly occur through embedded text, i.e., screenshots.
2. Statements or posts by celebrities showing support for a candidate with the aim of achieving a “voting effect” among their followers. Lady Gaga and Taylor Swift are two of the most frequently used celebrities in these deceptions.
3. The impersonation of politicians, especially candidates, which exhibits similar patterns in forgeries referencing Biden, Harris, and Trump. In these cases, deepfakes are frequently used to recreate controversial statements by White House candidates. Furthermore, these fabrications suggest an increasing use of AI to create hoaxes.

5.3. Type of hoax

Regarding the typology, deceptions predominate (59.3%). These are entirely fabricated stories encompassing various forgeries and messages intended to discredit candidates. Examples include alleged images of Donald Trump fleeing police to avoid arrest (Maldita.es, 2024a) and a slowed-down Kamala Harris speech intended to make her appear intoxicated (Newtral, 2024c). Hoaxes related to the electoral process itself are also prevalent, such as the claim that Trump's ballots were torn up during the mail-in vote count to suggest fraud (Infoveritas, 2024d). Additionally, hoaxes targeting public figures are common. In this regard, there is a lot of fraudulent content surrounding the singer Taylor Swift.

The attempted assassination of the Republican candidate was a unique event that became the target of disinformation on both sides. On the one hand, there were messages suggesting that the shooting and Trump's and the Secret Service agents' reactions were orchestrated to gain votes and popularity. On the other hand, there were messages pointing to the shooter's supposed Democratic and anti-Republican ideology in an attempt to extrapolate these traits as defining characteristics of the Democratic Party and its voters. About a quarter of the sample (24.5%) falls into the decontextualization category. These messages contain real facts or statements but are presented in a false or distorted context. These messages have a significant visual component, as they mostly use photographs or videos to accompany text explaining the narrative. For example, there is a hoax showing Trump playing golf the day after the shooting for which images from previous months were used (Maldita.es, 2024c).

Another 13.7% of the content is exaggerated; that is, real events whose narratives cross the line of truth. One example of this category is the false claim that Harris used a teleprompter during her appearance on a Univision television program. The claim is based on a photograph of the program showing a screen with the script in front of the Democratic candidate. However, the text displayed on the teleprompter corresponded to the program host's script (Maldita.es, 2024b).

Table 2. Type of hoax based on the source.

	Joke	Deception	Exaggeration	Decontextualization
Anonymous (n=137)	-	79 (65.3%)	22 (78.6%)	36 (72%)
Fictitious (n=3)	-	3 (2.5%)	-	-
Real (n=39)	-	23 (19%)	6 (21.4%)	10 (20%)
Impersonated (n=25)	5 (100%)	16 (13.2%)	-	4 (8%)
Total	5 (100%)	121 (100%)	28 (100%)	50 (100%)

Source: Elaborated by the author.

Regarding the source, based on the type of hoax (Table 2), the lack of message attribution appears to be a common feature across all categories, except for the joke category, which has an insufficient number of cases, with an incidence exceeding 65%. Similarly, real sources are prevalent regardless of the message category or type.

5.4. Theme

Considering the message theme (Table 3), electoral disinformation is predominantly structured around the private lives or past of the candidates (19.1%). The chi-square test shows that these hoaxes predominantly target the Democratic Party and its candidate [χ² (2, N=204)=21.772, p<0.05]. Among the fraudulent information found is the allegation that Kamala Harris worked as a prostitute (Infoveritas, 2024c), as well as claims about her relationship with rapper Diddy Combs, who was accused of sex trafficking (Newtral, 2024a). Similar misleading content has also been identified regarding the Democratic vice-presidential candidate, Tim Walz. These messages often rely on audiovisual elements, most of which are created specifically for this purpose, such as photographs (χ² (1, N=204)=20.380, p<0.05) or videos (χ² (1, N=204)=6.856, p<0.05), to bolster the supposed veracity of the narrative.

To a lesser extent, the attempted assassination of Trump (13.7%) and controversial statements and actions taken during the election period (11.8%) also form the basis of these hoaxes. The latter pieces predominantly feature the Democratic candidate [χ² (1, N=204)=16.318, p<0.05]. Furthermore, statistical tests reveal a relationship between the variables of the structure of fraudulent content on these topics. Photographs are commonly used to create falsehoods about the shooting of Trump. As for those referring to controversial statements, they are linked to video formats (χ² (1, N=204)=12.434, p<0.05). These videos typically originate from edited interviews or statements used to create the hoax.

Meanwhile, messages containing alleged information about the candidates' private or past lives primarily targeted Kamala Harris. However, messages about mental decline (11.3%) were usually directed at the Republican candidate. Numerous similar falsehoods regarding Joe Biden were also recorded until he withdrew from the race. These hoaxes tend to be interpretive [χ² (2, N=204)=9.473, p<0.05]. For example, there was disinformation claiming that Trump sat on a black towel during a television appearance due to possible incontinence problems (EFE Verifica, 2024a).

Table 3. The Theme of Hoaxes.

Theme	Number of hoaxes	Percentage (%)
Support	12	5.9
Arrest/Crimes	1	0.5
Debates	6	2.9
Government decisions	6	2.9
Controversial statements	24	11.8
Election developments	19	9.3
Resignation	2	1
Immigration	13	6.4
Attempted murder	28	13.7
Social works	7	3.4
Others	16	7.8
Other candidates	5	2.5
Past or private life	39	19.1
Loss of faculties	23	11.3
Election promises	3	1.5
Total	204	100

Source: Elaborated by the author.

5.5. Protagonist of the message

More than half of the messages feature the presidential candidates —Kamala Harris, 30.9%; Donald Trump, 20.6%— (Figure 2). Numerous hoaxes are also identified concerning Joe Biden (8.4%), although in most cases Biden is mentioned in his role and actions as President of the United States (5.9%), not as a candidate (2.5%). The chi-square test shows a relationship between the following variables: the hoaxes featuring Trump tend to be presented in both text and video —combined— [χ² (1, N=204)=5.212, p<0.05], and those referring to Harris have a greater presence of interpretive features [χ² (2, N=204)=8.692, p<0.05].

In general, there appears to be a tendency towards personalized narratives. Slightly lower is the rate of misinformation involving anonymous individuals (8.8%) and groups —two or more individuals— (9.8%). Examples of these would be misinformation about an alleged Haitian immigrant eating a cat or stories related to attendance at election rallies.

To a lesser extent, there are also hoaxes concerning the origin and identity of the person who shot the Republican candidate (6.4%). The Democratic vice-presidential candidate, Tim Walz, has also been the target of numerous disinformation campaigns (3.4%), which contrasts sharply with the complete absence of messages featuring his Republican counterpart.

Figure 2. Main protagonists of hoaxes.

Source: Elaborated by the author.

5.6. Lexicon and purpose

Based on the linguistic analysis, it is clear that all the pieces use everyday language, without resorting to technical terms or expressions specific to the political sphere. This characteristic facilitates comprehension of the narrative and, therefore, increases its potential audience. Furthermore, the message's credibility is supported by the predominance of informative discourse (67.2%), which lends a false appearance of rigor and truthfulness, compared to interpretive (22.1%) or opinionated (10.8%) narratives. Moreover, the analysis also reveals the complete absence of hypertextual elements in the construction of the hoaxes (99%).

The analysis shows that these messages have a predominantly political and ideological purpose (49%) and, to a lesser extent, a discrediting purpose (38.7%). While the latter also has a clear political connotation, it differs from the former in that hoaxes with a political and ideological aim seek to obtain votes by highlighting the achievements, promises, or qualities of the candidates, whereas messages with a discrediting purpose aim 
—in addition to indirectly convincing the electorate— to undermine the opponent. Fraudulent content with a discrediting purpose would include, for example, those that address negative aspects of the candidates' private lives. The incidence of other purposes, such as alarmism or sowing fear (4%), organizational purposes (3.4%), or economic purposes (2%), does not even exceed 4%.

In more than half of the pieces of content (53.9%), the narrative is constructed against the Democratic Party, which differs from the moderate rate of messages targeting the Republican Party (18.1%). That is, for every three pieces of misinformation against Harris and/or her party, there is one against Trump and/or his party. Meanwhile, 27.9% of the hoaxes present a neutral narrative. For example, the falsehood that claims there are more than 50 registered voters in a Pennsylvania convent but that no one lives there, suggesting that there are fake voters on the rolls (Maldita.es, 2024d). As shown in Figure 3, the predominance of disinformation against the Democrats is a constant throughout the electoral process.

Figure 3. Attack of Hoaxes per Month.

Source: Elaborated by the author.

Note: The period June 27-30 has been included in the July count.

While in July the difference in the direction of the falsehoods was barely 10 percentage points, as the electoral process progressed the gap widened, especially in August, September, and October, when the rates of attacks against the Democratic Party exceeded 66% in all cases. However, in the final stretch of the election campaign (November), the discourse shifted to a more moderate tone, with deception prevailing with a neutral approach (48.1%).

5.7. Dissemination and media impact

Analyzing the fact-checks published by verification platforms and the information available on them, it has been found that X (69.1%) and Facebook (23.5%) are the social networks through which fraudulent content is primarily disseminated. Similarly, TikTok (10.8%) appears to play a significant role in the dissemination process. Meanwhile, only 2.5% of the pieces have received media coverage; however, this presence in the media agenda usually occurs on dubious digital pseudo-media outlets based on clickbait, such as Esspots, Amuse, or KBSF.

5.8. Verification

Fact-checkers overwhelmingly rely on media sources (75.5%) and digital resources (70.1%) for fact-checking (Table 4). Regarding media outlets, fact-checkers consult newspaper and public audiovisual archives of U.S. media to verify reported facts or statements. They also use a variety of digital tools and applications related to image analysis, such as TinEye, InVID, and reverse image search systems; general data and information search engines, such as Yandex and Bing; the Wayback Machine website repository; and deepfake detection tools, such as Hugging Face. These tools have revealed the influence of artificial intelligence (AI) in the creation of at least 12.3% of the pieces of content. Most of these are deepfakes or images of candidates in different situations, such as alleged photographs of Donald Trump fleeing police (Maldita.es, 2024a) and Kamala Harris's birth certificate indicating she is male and from Libya (EFE Verifica, 2024b). One of the most viral deepfakes was a fake Biden speech announcing his withdrawal from the presidential race. In the AI-edited video, he concluded his remarks by saying, “F*ck you” (Newtral, 2024b). This forgery is a paradigmatic example of the procedure typically used to create these hoaxes. Starting with a video of real statements, promoters of fake news clone the voice of the individual and dub the video with a manipulated speech.

Table 4. Verification sources Used According to the Fact-Checking Platform (in %).

	Total	Newtral	Maldita.es	EFE Verifies	Verified	Infoveritas
Media	75.5	87.8	55.8	90.6	40	90.2
Digital resources	70.1	67.3	74	78.1	60	61
Social networks	37.7	38.8	32.5	43.8	20	43.9
Governmental	25	18.4	23.4	40.6	40	22
Association, NGO, union or org .	23	22.4	19.5	31.3	20	24.4
Policy	15.2	20.4	7.8	15.6	-	24.4
Security Force	10.3	18.4	9.1	9.4	-	4.9
Academic	4.9	6.1	2.6	9.4	-	4.9
Business	3.4	4.1	3.9	3.1	-	2.4
Famous	2.9	2	-	3.1	-	9.8
Laws	2	-	1	-	0.5	0.5

Source: Elaborated by the author.

Social media (37.7%) and official sources, mainly press releases or institutional statements (25%), are also common sources of information for journalists, though to a lesser extent. After verification, fact-checkers were only able to identify the authorship or origin of around one-fifth (20.1%) of the pieces. Most of these pieces were created by the candidates themselves (primarily Donald Trump) or individuals associated with them (notably, the falsehoods disseminated by Elon Musk via his X account or by Senator Ted Cruz). To a lesser extent, these pieces were created by social media trolls and digital media outlets driven by clickbait.

According to the sources used by the fact-checking platform (Table 4), certain differences were observed in the methods employed by the fact-checkers. While all five fact-checking organizations primarily rely on media outlets and digital tools for information, Verificat and Infoveritas show lower penetration of technological applications and resources for these tasks. This contrasts with the figures recorded by Maldita.es and EFE Verifica, which are both above average. Additionally, the organizations differ significantly in their use of media sources. While Verificat uses media outlets for 40% of its articles, EFE Verifica and Infoveritas rely heavily on media sources, which account for over 90% of their content. Official sources play a moderate role overall, except for EFE Verifica (40.6%) and Verificat (40%). Specifically, Table 4 reflects Verificat journalists' greater reluctance to use social media as a source (20%), while its penetration rate on the other platforms is remarkably high, ranging from 32.5% to 43.9%.

6. DISCUSSION AND CONCLUSIONS

This research focuses on disinformation disseminated in Spain regarding the 2024 U.S. presidential election. This allows for a deeper exploration of literature on political disinformation. Political disinformation is a growing problem that challenges citizens' political perceptions and threatens the development of democratic processes (Sádaba & Salaverría, 2023). As indicated by most of the literature, the 2016 elections, in which Donald Trump won, marked a turning point for the phenomenon of disinformation (Tandoc et al., 2021). This trend continued in the 2020 elections (Craig & Gainous, 2024), and given the significant volume of falsehoods recorded, it appears to be consolidating.

Examining the communication strategies used to present these falsehoods (O1), it's clear that audiovisual elements, particularly videos, play a significant role. These often appear alongside textual narratives, which bolster the story's plausibility. Recent studies (Colmenero-Ruiz et al., 2023; López-Martín & Córdoba-Cabús, 2024; Weikmann & Lecheler, 2023) suggest a growing prevalence of audiovisual media at the expense of textual hoaxes, likely due to the proliferation of social networks with a strong visual component. The dissemination of fraudulent content has been constant throughout the electoral process, although two key moments stand out with a higher concentration of hoaxes: the attempted assassination of Republican candidate Donald Trump and the voting process itself.

Regarding the formal characteristics of fraudulent content (O2), these messages are structured around two predominant features. First, there is an absence of individuals or institutions to whom the reported information is attributed, meaning the sources are anonymous. Second, there is a prevalence of deceptions in the form of completely fabricated claims. The recorded values regarding anonymous sources are consistent with previous study findings (Gamir-Ríos & Lava-Santos, 2022; Malquín-Robles & Gamir-Ríos, 2023). However, it is notable that one-fifth of the messages are attributed to and disseminated by real individuals, primarily hoaxes initiated by Donald Trump or his associates. This demonstrates a prevalent practice in the design of the Republican electoral campaign. Furthermore, the prevalence of real sources is a characteristic feature of disinformation surrounding US presidential elections. On the other hand, the preponderance of completely fabricated narratives does seem to be common to other disinformation phenomena (cf. Martín-Neira et al., 2023; Ruiz-Incertis et al., 2024), with minor exceptions such as, for example, false reports about armed conflicts (Magallón-Rosa et al., 2023; López-Martín & Córdoba-Cabús, 2024).

According to O3, the narrative primarily consists of stories about the candidates' personal lives and pasts, and, to a lesser extent, the alleged assassination attempt against Trump. Statistical evidence reveals trends in the creation of these hoaxes. Falsehoods related to personal or private matters focus on Kamala Harris, while those mentioning the loss of physical or mental faculties tend to center on the Republican candidate. Similarly, immigration has been a central theme in disinformation (Slocum, 2024). Regarding the subject of the message, there is a clear tendency to personalize the narrative. As expected, most pieces focus on the candidates, particularly the Democratic leader, whose message is slightly more prevalent than those featuring Donald Trump.

Objective 4 (O4) aimed to identify the characteristics of untruthful discourse. A series of characteristics common to the entire disinformation network under study were identified. These characteristics include the use of everyday language to make the narrative comprehensible to all audiences (cf. López-Martín & Córdoba-Cabús, 2024) and the prevalence of informative discourse. The latter aspect reinforces the message's supposed credibility and is supported by an impartial narrative that serves as a guarantee of objectivity. Compared to general disinformation disseminated in the United States, a distinguishing feature is the greater presence of biased elements (cf. Tandoc et al., 2021).

The purpose of these falsehoods is predominantly political and ideological, aligning with most of the scientific literature (cf. Broda & Strömbäck, 2024; Shahzad et al., 2023; Tandoc et al., 2021), while simultaneously seeking to discredit the targeted political adversary (cf. Susska et al., 2022; García-Marín & Salvat-Martinrey, 2023). From this, one can infer an intention to polarize the narrative and public opinion surrounding the U.S. electoral process (cf. Tandoc et al., 2021). Notably, the majority of these pieces target the Democratic Party. In general, for every three pieces of misinformation about Kamala Harris or the Democratic Party, there is one about Donald Trump and/or the Republican Party. Thus, there appears to be a bias or polarization in the construction of this content that disadvantages the Democratic Party.

Finally, objective five (O5) focused on two aspects. First, the available published fact-checks clearly show that X and Facebook are the main channels through which misleading messages are disseminated, as previous studies have suggested (cf. Almansa-Martínez et al., 2022; Ruiz-Incertis et al., 2024). Furthermore, the growing prominence of TikTok in this regard appears to be emerging (cf. Hoai-Lan & Minh-Tung, 2024; Méndez-Muros et al., 2024), likely due to the increasing popularity of audiovisual content. This contrasts with the limited presence of hoaxes in the mainstream media agenda. This media coverage is concentrated in short-lived, clickbait-based digital pseudo-media outlets, demonstrating a greater degree of control and rigor among established media outlets. In light of the scientific literature (cf. Blanco-Alfonso et al., 2021; Almansa-Martinez et al., 2022), this could be interpreted as an improvement in journalistic verification practices or at least greater attention to information published about the U.S. presidential elections.

Furthermore, O5 focused on the work of fact-checkers. To verify disseminated information, these professionals primarily rely on media sources and/or journalists, as well as a variety of digital tools, including image analysis applications, audiovisual resources, search engines, and website repositories. These findings suggest the high level of technological expertise required for the fact-checking journalist profile (cf. López-Martín & Córdoba-Cabús, 2024), which is an increasingly important consideration given the findings of previous studies (cf. Martín-Neira et al., 2023). These findings coincide with previous studies indicating that media and government sources (Blanco-Alfonso et al., 2021) and digital tools (López-Martín & Córdoba-Cabús, 2024) play the most prominent role in these tasks. When comparing fact-checking platforms, the aforementioned two sources —media and digital resources— are the primary means of obtaining information for all five organizations. However, a disparity in the use of technological tools is evident, with EFE Verifica and Maldita.es standing out. There are greater divergences in the incidence rates of media outlets and journalists as information sources. While platforms such as EFE Verifica and Infoveritas use these sources for almost all pieces of content, other fact-checkers, such as Verificat, show greater distrust or reluctance toward these channels. These platforms opt for official or governmental sources more often than the rest.

After the verification process, the fact-checkers could only identify the author or promoter of one-fifth of the analyzed pieces. These pieces suggest an increasing use of AI in creating fraudulent content (see García-Marín & Salvat-Martinrey, 2023). While generative AI is not yet dominant in quantitative terms, a significant repertoire of deceptive methods is evident. These methods are linked to the use of generative AI and include photographs, videos, and especially deepfakes. This aligns with the findings of Weikmann et al. (2024). Deepfakes are particularly effective from a persuasive and credibility standpoint because they achieve high levels of verisimilitude through the facial recognition of public figures, in this case, the candidates. Thus, AI facilitates the mass production of hoaxes and makes them appear credible, hindering their detection and verification and posing new challenges for media outlets and verification platforms.

This study contributes to the existing literature on electoral disinformation by focusing on an under-explored phenomenon: the reception and dissemination of hoaxes about foreign elections in the Spanish media. Thus, this article offers a transnational approach, demonstrating how narratives and techniques of deception transcend borders. The analysis identifies formal, thematic, and technological patterns, building upon previous studies' findings (cf. López-Martín & Córdoba-Cabús, 2024; Salaverría et al., 2020; Valera-Ordaz et al., 2022). Therefore, this work updates our understanding of electoral disinformation and proposes a more complex interpretation of the phenomenon that incorporates global, technological, and narrative factors.

In short, disinformation is a widespread and entrenched practice in electoral processes (cf. Lava-Santos et al., 2023; Pérez-Curiel et al., 2022). Magallón-Rosa (2019) argues that it is constantly developing and evolving toward new techniques and formats of deception. According to Huber et al. (2022) and Sádaba and Salaverría (2023), this phenomenon's rise could threaten the future of democratic societies because its effects can negatively impact polarization and the formation of a public opinion lacking critical thinking. Two limitations of this study stand out. First, the sample is limited to disinformation verified by Spanish fact-checking platforms, i.e., messages previously selected by these outlets. This suggests that the actual flow of falsehoods disseminated in Spain about the U.S. elections was greater. Additionally, it is worth noting the potential overrepresentation of some content, as hoaxes debunked by various fact-checking platforms were treated as separate units. Additionally, the analyzed disinformation concerns an event that occurred in another country. Thus, the hoaxes that circulated in the United States during this period may differ in characteristics from the hoaxes that circulated in Spain and were recorded in this study. Future research should delve deeper, analyzing the mechanisms behind hoax construction regarding subsequent electoral processes. Given the rise and widespread impact of AI across society, future research should also explore AI's penetration and use in creating fraudulent content.

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FUNDING AND ACKNOWLEDGMENTS

Funding: This investigation did not receive external funding.

Conflict of interests: None 

 

AUTHOR:

Álvaro López-Martín

University of Malaga.

He holds a Doctorate in Education and Social Communication from the University of Malaga, graduating with honors and receiving the Cum Laude distinction. Accredited by ANECA and ACCUA for PCD and PUP. He received an FPU contract and a Collaboration and Research Initiation Scholarship in the Department of Journalism at UMA. He is the author of over 50 scientific works, including articles and book chapters. He has presented over 70 papers at international conferences, and he has served on the scientific committee and organized over twenty international conferences. He participated in two national R&D&I projects, and in 2023, he completed a research stay at the University of Vienna (Austria), ranked 3rd in the Shanghai Ranking.

alvarolopezmartin@uma.es

Índice H: 8

Orcid ID: https://orcid.org/0000-0001-7871-2137

Scopus ID: https://www.scopus.com/authid/detail.uri?authorId=57219651671

Google Scholar: https://scholar.google.es/citations?user=2h9zrdgAAAAJ&hl=es&oi=ao

ResearchGate: https://www.researchgate.net/profile/Alvaro-Lopez-Martin

Academia.edu: https://uma.academia.edu/%C3%81L%C3%B3pezMart%C3%ADn

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