An analysis of the most viral posts from Ibero-American fact-checkers on Facebook in 2021

Jesús Pérez-Seoane, Juan Manuel Corbacho-Valencia, Alberto Dafonte-Gómez

An analysis of the most viral posts from Ibero-American fact-checkers on Facebook in 2021

ICONO 14, Revista de comunicación y tecnologías emergentes, vol. 21, no. 1, 2023

Asociación científica ICONO 14

Análisis de las publicaciones con mayor repercusión en Facebook de los fact-checkers iberoamericanos en 2021

Análise das publicações com maior impacto no Facebook realizadas pelos fact-checkers ibero-americanos durante 2021

Jesús Pérez-Seoane *

Universidad de Vigo, Spain

Juan Manuel Corbacho-Valencia **

Universidad de Vigo, Spain

Alberto Dafonte-Gómez *

Universidad de Vigo, Spain

Received: 13/september /2022

Revised: 01/october /2022

Accepted: 06/december /2022

Published: 18/january /2023

Abstract: More and more people are retrieving information through social networks, whose routines for creating, sharing and reacting to content have favored the appearance of hoaxes and false information. In this context, there is a proliferation of initiatives dedicated to content verification, which combat disinformation using the native language and codes of this environment. The purpose of this article is to analyse the publications with the highest volume of interactions made by the Ibero-American fact-checkers of the International Fact-Checking Network during 2021, to determine their reach and impact among audiences. After compiling the metadata of a total of 36,359 posts published by 19 issuers, a quantitative and content analysis was carried out of the six publications with the best interaction ratio for each of them during the analysis period (n=114). Most of them are links or photographs on political content, where textual verification of the content is almost as frequent as the use of visual or iconic elements that reinforce the message. The main type of interaction is of an emotional nature, with significant correlations observed between users' reactions and the number of times a post has been shared. In addition, the results of the research show that those publications with a higher interaction ratio cause an increase in followers in the days following the publications that is much higher than that which would be generated organically.

Keywords: Disinformation; Fact-checking; Fake news; Social media; Journalism; Post-truth.

Resumen: Cada vez más personas se informan a través de las redes sociales, espacios concebidos desde una perspectiva de entretenimiento donde las rutinas para crear, compartir y reaccionar ante los contenidos favorecen la aparición de bulos e informaciones falsas. En este contexto proliferan las iniciativas dedicadas a la verificación de contenidos, que combaten la desinformación utilizando el lenguaje y los códigos nativos en este entorno. El propósito de este artículo es analizar las publicaciones con mayor volumen de interacciones que realizaron los fact-checkers iberoamericanos de la International Fact-Checking Network durante 2021, para determinar su alcance e impacto entre las audiencias. Recopilados los metadatos de un total de 36.359 posts publicados por 19 emisores, se ha realizado un análisis cuantitativo y de contenido de aquellas seis publicaciones con mejor ratio de interacción de cada una de ellas durante el período de análisis (n=114). Son, en su mayor parte, enlaces o fotografías sobre contenidos políticos donde la verificación textual de los contenidos es casi tan frecuente como el uso de elementos visuales o icónicos que refuerzan el mensaje. El tipo de interacción mayoritario es de naturaleza emocional, observando correlaciones significativas entre las reacciones de los usuarios y el número de veces que un post ha sido compartido. Además, los resultados de la investigación constatan que aquellas publicaciones con mayor ratio de interacción provocan un incremento de seguidores en los días posteriores a las publicaciones muy superior al que se habría generado de forma orgánica.

Palabras clave: Desinformación; Fact-checking; Noticias falsas; Redes sociales; Periodismo; Posverdad.

Resumo: Cada vez mais pessoas estão a obter informação através de redes sociais, espaços concebidos a partir de uma perspectiva de entretenimento onde as rotinas de criação, partilha e reacção ao conteúdo favorecem o aparecimento de embustes e informação falsa. Neste contexto, há uma proliferação de iniciativas dedicadas à verificação de conteúdos, que combatem a desinformação utilizando a língua e os códigos nativos deste ambiente. O objectivo deste artigo é analisar as publicações com o maior volume de interacções feitas pelos fact-checkers ibero-americanos da International Fact-Checking Network durante 2021, a fim de determinar o seu alcance e impacto entre as audiências. Após a compilação dos metadados de um total de 36.359 postos publicados por 19 emissores, foi efectuada uma análise quantitativa e de conteúdo das seis publicações com a melhor relação de interacção para cada uma delas durante o período de análise (n=114). A maioria deles são links ou fotografias sobre conteúdo político, onde a verificação textual do conteúdo é quase tão frequente como a utilização de elementos visuais ou icónicos que reforçam a mensagem. O principal tipo de interacção é de natureza emocional, com correlações significativas observadas entre as reacções dos utilizadores e o número de vezes que um posto foi partilhado. Além disso, os resultados da investigação mostram que as publicações com uma maior taxa de interacção provocam um aumento de seguidores nos dias seguintes às publicações que é muito maior do que o que seria gerado organicamente.

Palavras-chave: Desinformação; Verificação de factos; Notícias falsas; Meios de comunicação social; Jornalismo; Pós-verdade.

1. Introduction

1.1. Broadcasting information on social networks

Covering over 90% of world population, the Internet is currently the leading means of communication (Newman et al., 2021). Social networks combined with online media constitute the main pathway to accessing information (Newman et al., 2022). This is a marked trend for people under 25 years old, who increasingly use these platforms as their main source of news (Newman et al., 2022; Kantar Media, 2021).

This new media ecosystem was researched (Campos-Freire et al., 2016; Gottfried & Shearer, 2016; Zubiaga et al., 2016; Al-Rawi, 2019; Amazeen et al., 2019, Salaverría & Martínez-Costa, 2022) with a view to considering how important the Internet is as a resource for obtaining news and the broadcasting capacity social networks have. Nevertheless, hardly a third (specifically, around 33%, according to the report Trust in News; Kantar Media, 2021) of users believe the contents they consume this way are trustworthy.

In this setting, Aguilera and Casero-Ripollés stated that, “the logic of social media has eclipsed that of conventional media” (2018, p. 6). This implies there are important special features about consuming news from the social networks vis-à-vis traditional media. Kim et al., (2019) indicate three main differences in this new paradigm: reader motivation (who are hedonists from a social perspective and seek entertainment, as opposed to the utilitarianism observed in traditional consumption); the chance users have to create and share contents (often, bypassing the fact checking stage); and attributing sources (which vary a great deal on social networks and users do not always identify nor choose them). Therefore, as there is neither any identified broadcaster, nor any rigorous methodology for checking information and considering networks target less critical audiences, this rising trend in the world of news has become a fertile breeding ground for creating and broadcasting fake news. The large amount of information we are bombarded with means recipients preferably consume news connected to their preconceived ideas. This reinforces their beliefs and exposure to other points of view (which may be necessary to have an objective viewpoint) are avoided (Amazeen et al., 2019; Kim et al., 2019; Zubiaga et al., 2016).

Al-Rawi (2019) puts forward the notion that readers tend to consume that news which are in tune with their own beliefs in order to validate their convictions. Therefore, users of social networks prefer to read and share positive news. This consideration is shared by Valenzuela et al. (2017), whose view is it is easier for highly emotive content to go viral than it is for quality journalism.

In the view of Wihbey (2014) very emotive posts are those which are more likely to be shared. Also, Berger and Milkman (2012) claimed that topics which evoked sensational positive or negative feelings had more chances of going viral than those which were more neutral. These reactions are so important that Alhabash and McAlister (2015) believe that in order to determine to what extent a post on a social network is influential it would be interesting to know the type of reaction it triggers. Therefore, to assess its potential, one not only has to look at its reach (expressed in objective data such as the amount of times a content is shared), but also at what is termed "evaluation" and deliberation" (as indicated by the number of likes or comments it receives, and concerns the emotional response a content produces among users).

Ksiazek et al. (2016), state that the reactions readers give to news is coloured by the opinions and reactions previously expressed by other users on the social networks. They make a distinction between user-user and user-content reactions. The search for information, socialisation and entertainment are the three underlying factors which are conducive to these types of interactions on social networks.

This is how the role reactions, shares and comments play in terms of spreading information on social networks are explained (García-Perdomo et al., 2018). It is a strategy which those spreading disinformation use to make certain topics more visible and which attracts and encourages the community itself to share it (Calvo et al., s.f.).

1.2. Countering disinformation by means of social networks

Although disinformation has always existed, it is the digital media, and, especially, the social networks, where a large number of individuals cluster. They can easily be grouped into a space in which the time spent on the platform and the amount of interactions is incentivised. It is here where fake news has found an outlet and it is a space for non-journalists to create seemingly journalistic contents and share them.

Tandoc et al. (2018) emphasise the role users have as coeditors of fake news, since they can interact with content, express how they feel and even comment. They take on the role of producer/broadcaster in order to make a post which is not authentic seem true and predisposes future readers to perceive it as real. This situation is made worse by the speed at which news is received and the frequency at which elements in thefeed are rotated. This hinders reflection and criticism (Zubiaga et al., 2016), and makes it harder to access (and, sometimes, even identify) the original source of the news (Kang et al., 2011).

Even though academic research usually focuses more on Twitter, Facebook is still the main network for informing oneself according to data from Digital News Report 2022. To be specific, 30% of people use it with this in mind. This is a figure higher than YouTube (19%), WhatsApp (15%), Instagram (12%) and Twitter (11%) (Newman et al., 2022). This justifies scrutinising Facebook when researching the consumption and distribution of information and disinformation.

In so far as people use social networks to inform themselves, and in so doing are exposed to disinformation, those countering it must also appear on them. Fact-checking may be defined nowadays as an activity “which applies journalistic data techniques to unmask the errors, ambiguities, lies, lack of rigour and inaccuracies in some contents posted on communication media " (Ufarte-Ruíz et al., 2018, p. 734). However, it may also concern contents distributed on the social networks and messaging tools whose author is not identified. It is not a new way of journalism per se (Guallar et al., 2020; Vázquez-Herrero, et al., 2019). However, with the emergence of numerous initiatives specifically on this topic (mainly between 2015 and 2019) it has become established as a specialised model of reporting (Stencel et al., 2022).

It is no wonder, therefore, that in an era in which social networks channel a large part of public discourse and disinformation, fact-checkers look to these platforms as being vehicles for distributing their contents. In recent years, different research has addressed the presence of fact-checkers on the social networks, both from an overall perspective (Dafonte-Gómez, Míguez-González and Ramahí-García, 2022) and by means of case studies (Bernal-Triviño & Clares-Gavilán, 2019; Magallón Rosa, 2019; Ufarte-Ruiz et al., 2020) or by analysing their activity on the networks and specific platforms such as Facebook (Martínez-Rolán et al., 2021), Instagram (Míguez-González et al., 2021), Twitter (Magallón Rosa, 2018), YouTube (Ramahí-García et al., 2021) TikTok (García-Marín and Salvat-Martinrey, 2022) and WhatsApp (Palomo & Sedano, 2018).

In addition, Latin American or Ibero-American fact checking also increasingly provides material for academic research (Guallar et al., 2020; Moreno-Gil et al., 2021; Palau-Sampio, 2018; Rodríguez-Pérez et al., 2022; Vizoso & Vázquez-Herrero, 2019). This rise may be attributed both to the specific weight of the region in terms of global fact-checking and the numerous partnerships created between checkers in different countries within this common cultural space.

The presence of checkers on the social networks means being on the same channel (as well as instant messaging applications) on which disinformation mainly spreads and sharing their findings organically by the same pathway, (Robertson et al., 2020). They are also helped by interactions from users which enable them to extend their reach (Margolin et al., 2018) mainly in contexts in which the algorithms of the social networks may not work in their favour.

At present, the newsfeed for Facebook users is made up of 49.1% of contents posted by their contacts, 20.5% of posts from groups and just 15.7% from contents from websites (Widely Viewed Content Report: What people see on Facebook, 2022). Therefore, it is quite difficult for them to reach users (even their followers) organically. This is the result of a policy initiated by the company in 2018 which (through its content selection algorithm, preference is given to posts from close contacts and groups with whom users interact a great deal. This diminishes the chances fact-checking websites have to extend their reach (Vogelstein, 2018).

Interactions with content, firstly, show the interest it arouses in the community of followers of the fact checkers. Secondly, they are an opportunity to organically spread their messages beyond the community of people interested in checked contents and even to broaden it.

2. Materials and methods

The purpose of this article is to describe the posts created by Ibero-American fact-checkers on Facebook which had the most interactions, determine what their features are, the effect they have on the audience and what possible influence they may have in terms of obtaining new followers.

For this purpose, two main research objectives were set:

  1. O1. To describe the posts with the highest interaction ratio and their features.

  2. O2. To determine whether having a higher number of interactions translates into a rise in the number of followers.

When the results for these two questions are received, we can respond to two other objectives of a secondary nature.

  1. To detect whether there are possible links between the main type of post and the type of post whose contents enjoy the highest interaction ratio.

  2. To find out what type of reaction is linked to the posts with the highest interaction ratio.

For this purpose, activity on Facebook was analysed between 1st of January and 31st of December 2021 for all fact-checkers operating in Ibero-America and that were members of the International Fact-Checking Network (IFCN) in the period of study. There were a total of 19 broadcasters which posted in Spanish and Portuguese and which operated in 12 countries (Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Spain, Mexico, Peru, Portugal, Uruguay and Venezuela). Using the tool CrowdTangle (CrowdTangle Team, 2020) the metadata for a total of 36,359 posts were compiled, among which a sample made up of six posts from each broadcaster which obtained the highest interaction ratio (n=114) was chosen.

The method set for gathering data was to make a quantitative analysis of the content. This is a valid technique "for studying any kind of communication objectively and systematically, by putting messages or contents into categories and subcategories, and subjects them to statistical analysis” (Hernández-Sampieri et al., 2010, p. 260). Moreover, it has been successfully implemented in communication sciences since the mid twentieth century. It is therefore one of the most suitable techniques for carrying out an analysis of information and news (Krippendorff, 2018).

To determine the most important fact-checker posts, the interactions ratio was used. This is a variable for measuring digital audiences and weighs the number of interactions according to the number of followers a given website has at the time of posting (total number of interactions/ followers at the time of posting x 100). To calculate the number of interactions, the seven reactions permitted by Facebook, as well as comments and shares, were taken into account.

Table 1
Fact-checker activity in 2021
Fact-checker activity in 2021

Source: Produced by the author

For each of the 114 posts the final sample was made up of the following variables were analysed:

  • Broadcaster, and type of post (status, photo, link, native video, video, live video, YouTube).

  • Topic and reach of posts: topics and predominant areas for hoaxes were broadly studied from different angles and according to both fact-checking activity on social networks (Vázquez-Herrero et al., 2019; Blanco-Afonso et al., 2021; Ceron et al., (2021), and disinformation techniques themselves (Salaverría et al., 2020; Kapantai et al., 2021). Creating a list with topics predefined by the 19 fact checkers was of little use for making a comparative analysis since sections became too atomised. In order to cover the 114 posts analysed, a series of categories were set from a more journalistic angle in keeping with the approach by García-Vivero & López García (2020). The topics revolved around politics, society, the economy, science and technology, events, sports and others, in keeping with the most typical sections in the media. Cultural contents were included under “society” in order to take a more holistic approach. Moreover, health was added for the reasons stated by Ceron et al. (2021). That is, the politics-health tandem predominated among the most shared hoaxes. Also, reach was added as a feature for differentiating between the national and international scope of these contents.

  • Formal features and graphics used.

  • Interactions created (classified by comments, shares, likes, love, wow, ha ha, sad, angry and care).

  • Number of website followers, both at the start and end of the posting period and for each post.

The data gathered was put onto a spreadsheet in which the values were recorded in absolute numbers and percentages, as well as those averages which best enabled objective data to be put into context.

To determine whether the posts with the greatest impact led to a rise in the number of followers in the next few days a metric was implemented by taking the three-day period after the post as the reference. This was carried out in order to compare it with the number of followers obtained with the expected organic growth (EOG) over that period of time. This EOG was obtained by analysing the difference between the number of followers for each fact-checker between 1st of January and 31st of December 2021. The results were divided between the number of days in a year in order to weigh them, and in turn by three days (as this was the time reference chosen).

Subsequently, this expected organic growth for each fact-checker was compared with the variation in the number of followers gained by each of the six most successful posts over the three following days (day x+3) after posting (day x). In this way, to what extent this growth in the number of followers matched the EOG over the same period was analysed.

3. Results

3.1 Broadcaster and type of post

The vast majority of contents posted in 2021 were links (69.14%) and photos (21.67%), which surpassed other possible resources such as videos (8.55%).

The predominant category in the posts with the best interaction ratio (those with the greatest impact and which this study is concerned with), tended to match the main type of content. That is, if a fact checker tended to post links to its websites, usually some of these were what lead to a higher interaction ratio. This point was already brought up by authors such as Martínez-Rolán et al. (2021) and were corroborated in this analysis.

3.2 Topic and reach of posts

Among the 114 most important posts in 2021, 40% concerned politics –a prevailing subject in the sample– followed by health (23.68%, with the backdrop of the vaccination against COVID-19), society (13.16%) and the economy (8.77%). These results concurred with those from Ceron et al. (2021), who stressed that the politics-health tandem surpassed any other topic of interest for the fact-checkers.

In most cases (85 out of 114), the reach of the topic of these posts was restricted to national territory (74.56%), while only 22.81% had an international scope.

One striking fact is that among the posts analysed an identical repeated rebuttal appeared by the same checker at different times of the year and three concerned the fact checker engaged in self-promotion.

3.3 Formal characteristics and graphics used

Regarding composition, practically all the posts with the most number of interactions were made up of an image (in 112 posts), a catchy headline (in 110) and a text (which occurred in 114 cases).

It was also typical to use graphics for indicating fake news. This concerned outstanding visuals which helped recipients instantly gauge whether the information displayed was true or false by showing graphic symbols. This was a visual code whose purpose was to discourage the sharing of fake news by making deceitful information less credible. This was highly efficient from a communicative (Mena, 2019) and psychological point of view (Koch et al., 2021) which, in this study could be observed in 74 of the 114 cases (64.91%). Other frequent resources used were emojis in the body of the text (55.26%) and hashtags(50.88%). A significant number of fact-checkers used these popular symbols and emojis in a similar way, almost as if they were following a template. These were normally used to round off their posts, and their purposes were to appeal (a magnifying glass or siren, for example); to give emphasis (an x or a red circle which reports fake content); to direct users (arrows and hands which guide readers in a certain direction); to describe (a bar chart to refer to some statistics, a mobile phone to talk via Whatsapp, etc.); and as decoration (a feather to identify the one who has checked the information). These resources were normally found in the body of the texts, not in the titles.

With a catchy graphic, often an unedited image (50%), or a photomontage (28.07%) was used. Other formats used and which also lead to a high number of interactions were videos (8.77%), infographs, memes, graphical humour and carousels.

3.4 Classification of general interactions

Out of a total of 466,936 reactions to the posts analysed, hardly 8.40% corresponded to comments. Normally, the content (from the post analysed was shared, which happened 194,480 times) and in such a way it stood out, and emotional responses were shown by means of reactions (this happened 237,042 times or 50.76%).

Within the latter categories, the most typical reaction to show approval for content on Facebook was to give a "like" and this was registered 172,312 times in the 114 posts analysed (36.90% of all the interactions in the sample). Apart from indicating a “like”, one could also express other emotions such as “love”, “wow”, “ha ha”, “sad”, “angry” and “care”, which appeared 64,730 times (13.86%). All in all, users expressed a total of 237,042 emotional reactions out of which most (216,337 or 91.27%) clearly corresponded to positive feelings. (That is, like, love, wow and ha ha).

Table 2
Pearson´s correlation between shares and emotional reactions
Pearson´s correlation between shares and emotional reactions

Source: Produced by the author

As for what influence these emotional expressions as reactions had on deciding whether to share content (and thereby extend its reach) we observed positive and significant correlations at level p<0,05 between “share” and all the reactions apart from “ha ha”. However, we could only consider strong correlations which occurred between "share” and “like”. This is the main one and concurred with the results from Dafonte-Gómez, Míguez-González and Martínez-Rolán (2022); and “share” and “care”. In a similar vein, albeit to a lesser extent, were the correlations between "angry" and "love" and comments.

These results vindicated the approach set out by Valenzuela et al. (2017) and Al-Rawi (2019), according to whom readers tended to consume positive contents which they liked and this reinforced their convictions. It was also striking that many users showed they were specially involved in the contents. It is remarkable that the “like” reaction was always widespread on Facebook, but this was not true for “care” and even less so when it came to sharing the content about which such concern was shown. This eventuality was foreseen by Berger and Milkman (2012), for whom not only the contents associated with positive reactions were those which most tended to be shared, but also those which encouraged greater connivance and which were most stimulating for recipients, regardless if this was in a positive or negative way.

3.5 Number of followers of the websites

The final part of the study was aimed at determining whether there was a marked rise in the number of followers in the days after the posts appeared with the highest interaction ratio.

This estimation was applied to each of the 114 posts analysed. Table 3 shows the global average for the six most relevant posts from each fact-checker and this is compared with the EOG.

Table 3
Rise in number of followers three days after posting
Rise in number of followers three days after posting

Source: Produced by the author

Analysing the data concerning the 114 posts studied, there was a clear, positive, albeit weak, correlation (Pearson´s r =0,199) and a significant one at level p<0.05 between the growth ratio and that for interaction with the posts. Almost three quarters of fact-checkers at least doubled the growth rate of their expected audience. Moreover, there were some outstanding observations, such as AFP Factual, Cotejo and La Silla Vacía, which almost multiplied their number of expected followers by 15.

The availability of the data can be consulted at the following link:

4. Conclusions

Conceived as entertainment and leisure platforms, social networks are settings conducive to sharing contents. However, using them as a source of information poses the risks inherent to an environment in which content without contrasted sources are consumed rapidly and influenced by previous evaluations from other users.

It is a context which encourages disinformation, an environment in which fact-checkers are the best guarantor of trustworthy information. This is because they put inaccurate content into a context and denounce the lies circulating on the social networks. In their work, they adapt to the typical way users express themselves on these platforms, and become broadcasters of checked contents. They aim to make their contents go viral both among their real and potential followers.

An analysis of the features of their posts with the highest interaction ratio (objective 1) is of academic interest as we can gain an insight into how fact-checkers assume the language of the social networks to establish a social discourse in order to resonate with their audiences. It is also of interest to professionals as we gain an insight into how their contents are structured in order to create the highest number of interactions on Facebook.

The topics which trigger most reactions are national politics. Apart from that, contents with a social impact, such as on health or society are also outstanding. Posts are largely made up of an image, a short caption (with plenty of emojis and other visuals). Also, they even have a graphics system to illustrate their verification work by way of symbols (stamps, traffic lights and icons which, when illustrated with a picture, enable people to see at a glance whether the content is true, incomplete or false). The here and now is also a value which can encourage interaction with a content, since many confine themselves to current events.

This does not mean that the same post that had a great effect on Facebook will enjoy similar results a few months later. It must also be stressed that among the contents with the highest reach not only concern news but also self-promotion. This shows the interest fact checkers have in social networks and their capacity to express themselves in the native language of this media and provide contents which can go viral even though they are not news.

Links to news on the websites, photographs (which also usually contain links) and native videos are the contents with the highest interaction ratios. As there is a close correspondence between the main type of post and those with the highest interaction ratio, it is hard to identify those entries which by their very nature have the highest impact.

It is easier to find the type of reaction to the posts with these ratios, having seen that over half of these interactions (50.76%) stem from emotional reactions, predominantly those associated with positive feelings. It is striking that the other interactions come from commenting and sharing contents, two activities which require more effort and implication from the audiences. Of course, this goes far beyond merely expressing oneself with an emoticon.

The amount of times the analysed contents were shared (194,480, which accounted for 41.65% of interactions) was extraordinarily remarkable. Moreover, positive correlations were found between emotional kinds of reactions, especially the number oflikes, and the times a post was shared, but also with the “care” reaction.

The posts with the highest interaction ratio resulted in a rise in the number of followers which surpassed that of the average post (objective 2) over the same period. This implies that the contents with the most engagement obtained more organic reach and could bypass the Facebook algorithm because users shared them and, in this way, helped fact-checkers grow their audiences. In any event, one cannot make any categorical statement in this respect, since there were three limiting factors in this study: it was restricted in time (limited to a natural year), the ongoing influence of the pandemic caused by Covid-19 (which was still in the news); and the area of influence of the fact-checkers analysed.

However, there are certain indications there are topics, compositional elements and angles which can help raise the rate of interaction of contrasted news on social networks. This way, the number of fact checker followers can rise. All these can be corroborated in future research which will transcend the social, culture and time limitations of this study.

Contributions from the authors

Jesús Pérez-Seoane: Conceptualization, Data curation, Formal Analysis, Methodology, Research, Software, Validation, Supervision, Writing- original draft and Writing-review and editing. Juan Manuel Corbacho-Valencia: Conceptualization, Formal Analysis, Methodology, Research, Resources, Validation, Writing- original draft and Writing-review and editing. Alberto Dafonte-Gómez: Conceptualization, Resources, Software, Visualization, Supervision, Project Management, acquiring funds and Writing-review and editing. All the authors have read and agree with the published version of the manuscript. Conflicts of interest: The authors declare they have no conflict of interests.


Work carried out within the project “Digital narratives against disinformation. Study of networks, topics and Ibero-American fact-checker formats”, financed by the State Agency for Research (Ref. PID2019-108035RB-I00/AEI/10.13039/501100011033).


Aguilera, Miguel de; & Casero-Ripolles, Andreu (2018). ¿Tecnologías para la transformación? Los medios sociales ante el cambio político y social. Revista ICONO 14. Revista científica de Comunicación y Tecnologías emergentes, 16(1), 1-21.

Alhabash, Saleem; & McAlister, Anna R. (2015). Redefining virality in less broad strokes: Predicting viral behavioral intentions from motivations and uses of Facebook and Twitter. New Media & Society, 17, 1317-1339.

Al-Rawi, Ahmed (2019). Viral News on Social Media. Digital Journalism, 7(1), 63-79.

Amazeen, Michelle A.; Vargo, Chris J.; & Hopp, Toby (2019). Reinforcing attitudes in a gatewatching news era: Individual-level antecedents to sharing fact-checks on social media. Communication Monographs, 86(1), 112-132.

Berger, Johna; & Milkman, Katherine L. (2012). What Makes Online Content Viral? Journal of Marketing Research, 49(2), 192-205.

Bernal-Triviño, Ana; & Clares-Gavilán, Judith (2019). Uso del móvil y las redes sociales como canales de verificación de fake news. El caso de El Profesional de la Información, 28(3).

Blanco-Alfonso, Ignacio; Chaparro-Domínguez, María Ángeles; & Repiso, Rafael (2021). El fact-checking como estrategia global para contener la desinformación. Estudios sobre el Mensaje Periodístico, 27(3), 779-791,

Calvo, Ernesto; Aruguete, Natalia; Ventura, Tiago; Contursi, Adrián; & Miller, Katherine. Chequeado en Argentina. Fact checking y la propagación de noticias falsas en redes sociales. Consultado el 19 de enero de 2022.

Campos-Freire, Francisco; Rúas-Araújo, José; López-García, Xosé; & Martínez-Fernández, Valentín A. (2016). Impacto de las redes sociales en el periodismo. El profesional de la información (EPI), 25(3), 449-457.

Cappella, Joseph N.; Kim, Hyun Suk; & Albarracín, Dolores (2015). Selection and Transmission Processes for Information in the Emerging Media Environment: Psychological Motives and Message Characteristics. Media Psychology, 18(3), 396-424.

Ceron, Wilson; de-Lima-Santos, Mathias-Felipe; & Quiles, Marcos G. (2021). Fake news agenda in the era of COVID-19: Identifying trends through fact-checking content. Online Social Networks and Media, 21, 100116.

CrowdTangle Team (s.f.). Consultado el 8 de febrero de 2022.

Dafonte-Gómez, Alberto; Corbacho-Valencia, Juan Manuel; & García-Mirón, Silvia (2021). El fact-checking en Iberoamérica: Evolución reciente y mapa de situación. En J. Sotelo González & J. González García (Eds.), Digital Media. El papel de las redes sociales en el ecosistema educomunicativo en tiempo de COVID-19 (pp. 877-889). McGraw-Hill.

Dafonte-Gómez, Alberto; Míguez-González, María-Isabel; & Martínez-Rolán, Xabier (2022). Los fact-checkers iberoamericanos frente a la COVID-19. Análisis de actividad en Facebook. Observatorio (OBS*), 16(1), 160-182.

Dafonte-Gómez, Alberto; Míguez-González, María-Isabel; & Ramahí-García, Diana (2022). Fact-checkers on social networks: Analysis of their presence and content distribution channels. Communication & Society, 35(3), 73-89.

Freeman, Cole; Alhoori, Hamed; & Shahzad, Murtuza (2020). Measuring the Diversity of Facebook Reactions to Research. Proceedings of the ACM on Human-Computer Interaction, 4(GROUP), 1-17.

García-Perdomo, Víctor; Salaverría, Ramón; Kilgo, Danielle K.; & Harlow, Summer (2018). To Share or Not to Share. Journalism Studies, 19(8), 1180- 1201.

García-Marín, David; & Salvat-Martinrey, Guiomar (2022). Viralizing the truth: Predictive factors of fact-checkers’ engagement on TikTok. Profesional de la Informacion, 31(2).

García-Vivero, Gloria; & López, Xosé (2021). La verificación de datos en Europa. Análisis de 5 iniciativas europeas:, Newtral, Pagella Politica, Les Décodeurs, BBC Reality Check. AdComunica, 21, 235-264.

Gottfried, Jeffrey; & Shearer, Elisa (26 de mayo de 2016). News Use Across Social Media Platforms 2016. Pew Research Center. Consultado el 10 de enero de 2022.

Guallar, Javier; Codina, Lluís; Freixa, Pere; & Pérez-Montoro, Mario (2020). Desinformación, bulos, curación y verificación. Revisión de estudios en Iberoamérica 2017-2020. Telos: revista de Estudios Interdisciplinarios en Ciencias Sociales, 22(3), 595–613.

Hernández-Sampieri, Roberto; Fernández-Collado, Carlos; & Baptista-Lucio, Pilar (2010). Metodología de la investigación. McGraw Hill.

Herrero, Esperanza; & Herrera-Damas, Susana. (2021). Spanish-speaking fact-checking: Competences, difficulties, and potential improvements from factcheckers’ perspective. Profesional de la Información, 30(6).

Householder, Elizabeth E.; & LaMarre, Heather L. (2014). Facebook politics: Toward a process model for achieving political source credibility through social media. Journal of Information Technology & Politics, 11(4), 368-382.

Kang, Hyunjin; Keunmin, Bae; Zhang, Shaoke; & Sundar, S. Shyam (2011). Source Cues in Online News: Is The Proximate Source More Powerful than Distal Sources? Journalism & Mass Communication Quarterly, 88(4), 719–736.

Kantar Media. (2021). Trust in News. Consultado el 12 de enero de 2022.

Kapantai, Eleni; Christopoulou, Androniki; Berberidis, Christos; & Peristeras, Vassilios (2021). A systematic literature review on disinformation: Toward a unified taxonomical framework. New Media & Society, 23, 1301-1326.

Kim, Antino; Moravec, Patricia L.; & Dennis, Alan R. (2019). Combating Fake News on Social Media with Source Ratings: The Effects of User and Expert Reputation Ratings. Journal of Management Information Systems, 36(3), 931-968.

Koch, Timo; Frischlich, Lena; & Lermer, Eva (2021). The Effects of Warning Labels and Social Endorsement Cues on Credibility Perceptions of and Engagement Intentions with Fake News [Preprint]. PsyArXiv.

Krippendorff, Klaus (2018). Content Analysis. An Introduction to Its Methodology. SAGE Publications Inc.

Ksiazek, Thomas B.; Peer, Limor; & Lessard, Kevin (2016). User engagement with online news: Conceptualizing interactivity and exploring the relationship between online news videos and user comments. New Media and Society, 18(3), 502-520.

Magallón Rosa, Raúl (2019). Verificado México 2018: Desinformación y fact-checking en campaña electoral. Revista de Comunicación, 18(1), 234-258.

Magallón Rosa, Raúl (2018). Nuevos formatos de verificación. El caso de Maldito Bulo en Twitter. Sphera Publica, 1(18), 41-65.

Margolin, Drew B.; Hannak, Aniko; & Weber, Ingmar (2018). Political Fact-Checking on Twitter: When Do Corrections Have an Effect? Political Communication, 35(2), 196–219.

Mena, Paul (2019). Cleaning Up Social Media: The Effect of Warning Labels on Likelihood of Sharing False News on Facebook. Policy and Internet, 12(2), 165-183.

Martínez-Rolán, Xabier; Míguez-González, María Isabel; & García-Crespo, Oswaldo (2021). Fact-checkers iberoamericanos en Facebook: Análisis de interacciones y comunidad en 2020. En J. Sotelo González & J. González García (Eds.), Digital Media. El papel de las redes sociales en el ecosistema educomunicativo en tiempo de COVID-19 (pp. 447-467). McGraw-Hill.

Míguez-González, María Isabel; Abuín-Penas, Javier; & Pérez-Seoane, Jesús. (2021). ¿Cómo utilizan los fact-checkers las redes sociales para combatir la desinformación? Análisis de la actividad de los fact-checkers iberoamericanos en Instagram. En M. Blanco Pérez (coord.), El progreso de la comunicación en la era de los prosumidores (pp. 15-39). Dykinson.

Moreno-Gil, Victoria; Ramon, Xavier; & Rodríguez-Martínez, Ruth (2021). Fact-Checking Interventions as Counteroffensives to Disinformation Growth: Standards, Values, and Practices in Latin America and Spain. Media and Communication, 9(1).

Newman, Nic; Fletcher, Richard; Robertson, Craig T., Eddy, Kirsten; & Nielsen, Rasmus Kleis (2022). Reuters Institute Digital News Report 2022. Reuters Institute for the Study of Journalism. Consultado el 10 de enero de 2022.

Newman, Nic; Fletcher, Richard; Schulz, Anne; Andi, Simge; Robertson, Craig T.; & Nielsen, Rasmus Kleis (2021). Reuters Institute Digital News Report 2021. Oxford: Reuters Institute for the Study of Journalism. Consultado el 10 de enero de 2022.

Palau-Sampio, Dolors (2018). Fact-checking and scrutiny of power: Supervision of public discourses in new media platforms from Latin America. Communication & Society, 31(3), 347-363.

Phelps, Joseph E.; Lewis, Regina; Mobilio, Lynne; Perry, David; & Raman, Niranjan (2004). Viral Marketing or Electronic Word-of-Mouth Advertising: Examining Consumer Responses and Motivations to Pass Along Email. Journal of Advertising Research, 44(4), 333-348.

Picone, Ike; De Wolf, Ralf; & Robijt, Sarie (2016). Who Shares What with Whom and Why?: News sharing profiles amongst Flemish news users. Digital Journalism, 4(7), 921-932.

Ramahí-García, Diana; García-Crespo, Oswaldo; & Dafonte-Gómez, Alberto (2021). Los formatos audiovisuales en la verificación de datos. Análisis de la actividad de los fact-checkers en YouTube (2009-2020). AdComunica, 22, 73-96.

Robertson, Craig T.; Mourão, Rachel R.; & Thorson, Esther (2020). Who Uses Fact-Checking Sites? The Impact of Demographics, Political Antecedents, and Media Use on Fact-Checking Site Awareness, Attitudes, and Behavior. International Journal of Press/Politics, 25(2), 217–237.

Rodríguez-Pérez, Carlos; Seibt, Taís; Magallón-Rosa, Raúl; Paniagua-Rojano, Francisco Javier; & Chacón-Peinado, Sonia (2022). Purposes, Principles, and Difficulties of Fact-checking in Ibero-America: Journalists’ Perceptions. Journalism Practice, 0(0), 1-19.

Salaverría, Ramón; Buslón, Nataly; López-Pan, Fernando; León, Bienvenido; López-Goñi, Ignacio; & Erviti, María-Carmen (2020). Desinformación en tiempos de pandemia: tipología de los bulos sobre la Covid-19. El Profesional de la Información, 29(3), e290315.

Salaverría, Ramón; & Martínez-Costa, María del Pilar (2022). Medios nativos digitales en España. Comunicación Social Ediciones y Publicaciones.

Shorenstein Center on Media, Politics and Public Policy. Conusultado el 20 de enero de 2022.

Stencel, Mark; Ryan, Erica; & Luther, Joel (2022, junio 17). Fact-checkers extend their global reach with 391 outlets, but growth has slowed. Duke Reporters’ Lab. Consultado el 15 de enero de 2022.

Tandoc, Edson C. Jr.; Lim, Zheng Wei; & Ling, Richard (2018). Defining “Fake News”. Digital Journalism, 6(2), 137-153.

Thompson, Nik; Wang, Xuequn; & Daya, Pratiq (2020). Determinants of News Sharing Behavior on Social Media. Journal of Computer Information Systems, 60(6), 593-601.

Ufarte-Ruiz, María José; Anzera, Guiusseppe; & Murcia-Verdú, Francisco José (2020). Independent fact-checking platforms in Spain and Italy. Features, organisation and method. Revista Mediterranea de Comunicacion, 11(2), 23-39.

Ufarte-Ruíz, María José; Peralta-García, Lidia; & Murcia-Verdú, Francisco José (2018). Fact checking: A new challenge in journalism. El Profesional de la Informacion, 27(4), 733-741.

Valenzuela, Sebastián; Piña, Martina; & Ramírez, Josefina (2017). Behavioral Effects of Framing on Social Media Users: How Conflict, Economic, Human Interest, and Morality Frames Drive News Sharing. Journal of Communication, 67(5), 803-826.

Vázquez-Herrero, Jorge; Vizoso, Ángel; & López-García, Xosé (2019). Innovación tecnológica y comunicativa para combatir la desinformación: 135 experiencias para un cambio de rumbo. El Profesional de la Información, 28(3), e28030.

Vizoso, Ángel; & Vázquez-Herrero, Jorge (2019). Fact-checking platforms in Spanish. Features, organisation and method. Communication & Society, 32(1), 127-143.

Vogelstein, Fred (2018, enero 11). Facebook Tweaks Newsfeed to Favor Content from Friends, Family. Wired. Consultado el 12 de enero de 2022.

Wihbey, J. (2014). The Challenges of Democratizing News and Information: Examining Data on Social Media, Viral Patterns and Digital Influence.

Zubiaga, Arkaitz; Liakata, Maria; Procter, Rob; Wong Sak Hoi, Geraldine; & Tolmie, Peter (2016). Analysing how people orient to and spread rumours in social media by looking at conversational threads. PLoS ONE, 11(3), 1-29.

Author notes

* Associate Professor PhD in the Department of Audiovisual Communication and Advertising

** Associate Professor in the Department of Audiovisual Communication and Advertising

Additional information

Translation to English : Toby Wakely

To cite this article: Pérez-Seoane, Jesús; Corbacho-Valencia, Juan Manuel; & Dafonte-Gómez, Alberto. (2023). An analysis of the most viral posts from Ibero-American fact-checkers on Facebook in 2021. ICONO 14. Scientific Journal of Communication and Emerging Technologies, 21(1).

Cómo citar
ISO 690-2
ICONO 14, Revista de comunicación y tecnologías emergentes

ISSN: 1697-8293

Vol. 21

Num. 1

Año. 2023

An analysis of the most viral posts from Ibero-American fact-checkers on Facebook in 2021

Jesús Pérez-Seoane 1, Juan Manuel Corbacho-Valencia 1, Alberto Dafonte-Gómez 1