An experimental study of the effect of the news source on the dissemination of fake newsAbstract
Objective: This study aims to analyze the effect of the source (true versus false) of news on the intention to disseminate fake news of a brand, considering the mediation of news credibility in the relationship between source credibility and intention to disseminate fake news. Originality/value: This study’s relevance and originality revolve around the effect of the source (true versus false) on the intention to disseminate fake news about a brand. To date, we are unaware of other studies that have found the effect of a source (true versus false) on the intention to disseminate fake news about a brand. Design/method/approach: We conducted a laboratory quasi-experiment (n=153 participants), utilizing Structural Equation Modeling to analyze the data. The mediation test used the PROCESS macro.
Results: The results indicated that a true source could induce indi-viduals to disseminate fake news only when the credibility of the news mediates the relationship. Contributions: This study contributes to both fake news and brand lite-rature by presenting new findings about the effect of sources on the intention to share fake news. This study tests the mediation relationship through the PROCESS macro as a methodological contribution. Brand managers need to pay more attention to Dark Social, given the ease of manipulating content and the persuasion obtained. Public managers are responsible for reinforcing the importance of people checking the content they receive, even from a credible source.
Keywords:
fake news; source credibility; news credibility; intention to share fake news
Resumo
Objetivo: o objetivo deste estudo foi analisar o efeito da fonte (verdadeira versus falsa) de notícias na intenção de disseminar fake news de uma marca, por meio da mediação da credibilidade da notícia na relação entre credibilidade da fonte e intenção de disseminar fake news. Originalidade/valor: A relevância e originalidade desse estudo gira em torno do efeito da fonte (verdadeira versus falsa) na intenção de disseminar uma fake news acerca de uma marca. Até o momento não se sabe da existência de outros estudos que tenham encontrado efeito de uma fonte (verdadeira versus falsa) na intenção de disseminar fake news de uma marca. Design/metodologia/abordagem: Foi realizado quase-experimento de laboratório (n=153 participantes), cujos dados foram analisados por meio de Modelagem de Equações Estruturais. O teste de mediação foi realizado por meio da macro PROCESS.
Resultados: Os resultados indicaram que uma fonte verdadeira pode induzir os indivíduos a disseminarem uma fake news somente quando a relação é mediada pela credibilidade da notícia. Contribuições: Este estudo contribui tanto para literatura de fake news quanto de marca ao trazer novos achados sobre o efeito da fonte na intenção de compartilhar fake news. Como contribuição metodológica, este estudo testa a relação de mediação por meio da macro PROCESS. Gestores de marcas precisam ficar mais atentos a Dark Social, dada a facili-dade de manipulação de conteúdos e a persuasão obtida. Gestores públicos possuem a responsabilidade de reforçar a importância de as pessoas checarem conteúdos que recebem, mesmo com fonte crível.
Palavras-chave
fake news; credibilidade da fonte; credibilidade da notícia; intenção de compartilhar fake news
INTRODUCTION
Fake news is a complex and very controversial concept due to the wide variation in how it is used in public discourse. It is notoriously difficult to define, drawing into its orbit hoaxes, conspiracy theories, state-sponsored propaganda, biased information, manipulated content, satire, and parody (Tandoc Jr. et al., 2018). The theme/phenomenon is not new, as in 1835, The New York Sun newspaper published a series of articles about “the full moon hoax” (Altman, 2014). These articles dealt with the existence of living beings on the moon. However, with the advent of the internet, it gained strength due to the expansion of its reach. Despite not being new, this news was not active until mid-2016, when the United States presidential elections took place (Allcott & Gentzkow, 2017). With consulting studies and research repositories, such as the Web of Science, it is possible to notice a significant increase in publications about fake news after the 2016 US elections. In 2017, there were less than 50 articles on the topic. In the year’s analysis of 2021, we found over 900 academic articles that dealt with fake news.
We know that people with malicious intentions intentionally create fake news, and other people sometimes spread it without malicious intent. People’s carelessness and lack of attention when reading posts contribute to this spread of fake news (Pennycook & Rand, 2019). Sharing fake news about a brand by a credible source can equally persuade word-of-mouth (negative or positive) (Costa Filho et al., 2023). According to Gildin (2003, p. 94), “when consumers want to purchase a new product or service, they tend to seek information from family, friends, and others as sources of privi-leged information.”
This becomes even more problematic as people are exposed to a high amount of information daily. In other words, online news is shared daily, and it is not always possible to understand what is fact (real) or fake news (Allcott & Gentzkow, 2017). One way for news consumers to attribute credi-bility to news is an organization or person’s endorsement of a particular content (Sundar, 1998). Thus, based on underlying beliefs, people tend to believe news shared by sources they deem credible (Mahapatra & Mishra, 2017; Park & Lee, 2008).
Although not decisive, there is a consensus that the credibility of the news influences content-sharing intentions and behavior (Appelman & Sundar, 2016; Mena, 2020). Although the literature already covers a large part of the issues surrounding the effect of source credibility and news credi-bility on the intention to disseminate fake news, few studies have focused on understanding the effect of a false source versus a true source as a predictive variable (Visentin et al., 2019; Bauer & Hohenberg, 2021).
A survey performed by ABREJE (Brazilian Business Communication Association) identified that around 50% of the organizations interviewed have already suffered from fake news. When fake news was related to a sector (and not a company directly), this figure increased to 66%. Around 58% of companies/sectors suffered economic and financial (Quintino, 2022). This only highlights the relevance of this study and the need to understand the cognitive triggers that facilitate individual persuasion and drive the dissemination of fake news.
Previous studies tested the effect of true versus fake news sources. One study, which sought to explain word-of-mouth (positive and negative) concerning a brand, found no explanation through the source (Bauer & Hohenberg, 2021). Another (Visentin et al., 2019) sought to understand the effect of fake news on the brand, with the news endorsed by a source of high credibility (versus low).
To mitigate the research gap, this study’s central objective is to analyze the effect of the news source (true versus false) on the intention to disseminate fake news through the credibility of the source and the news. We examined this in negative fake news about a brand. Although we do not seek to understand the effects on the brand, we recognize that the proliferation of any false information can harm it (Gildin, 2003). This is the first work done in Brazil to analyze the effect of the source on the intention to disseminate fake news. Our study covers these gaps, as it presents the effects of the source (true versus false) on the intention to disseminate fake news about a brand. We seek to answer the following research question: What is the effect of the news source on the intention to share fake news?
This study made two major contributions. First, we identified that the fact that a source is true affects the credibility of the source and the intention to disseminate fake news. Second, we discovered that the credibility of the news has a mediating effect between the source’s credibility and the intention to disseminate fake news. More than believing in the source, it is also necessary for the receiver to trust the news so that they are more likely to disseminate fake news.
THEORETICAL FRAMEWORK AND ELABORATION OF HYPOTHESES
This section presents the theoretical framework regarding fake news, source credibility, and news credibility, besides the conceptual model and hypotheses of the present study.
Fake news
Scholars define fake news as news that is false or contains deliberately misleading elements incorporated into the content or context (Lazer et al., 2018). They occur in the digital environment as an online publication of intentionally or knowingly false statements of fact (Klein & Wueller, 2017; Fisher, 2018). The focus is on articles or messages posted online, expecting the message to go “viral” (Zhang et al., 2019).
Fake news as a concept became more popular after the 2016 American presidential elections, in which articles and fabricated news (fake news) were actively shared millions of times among American voters on social media platforms such as Facebook, YouTube, and Twitter (Papanastasiou, 2020). The reach of fake news in those elections was impressive. Facebook estimated that fake news regarding the 2016 elections reached over 126 million Americans (Clarke et al., 2020). The real impact of fake news is less well understood. For example, it is unclear whether fake news, despite its reach, significantly impacted the election outcome (Clarke et al., 2020).
In addition to politics, researchers from different areas have sought to understand this phenomenon (Garrett, 2009; Di Domenico & Visentin, 2020; Michael & Breaux, 2021). The areas most affected by the proliferation of fake news have been politics (based on false information, voters can have a distorted view of a candidate or even an elected politician) (Allcott & Gentzkow, 2017) and the health (e.g., low vaccine adherence rate) (Iacobucci, 2019). However, fake news can also be considered a threat to organizational brands (Di Domenico et al., 2020; Mishra & Samu, 2021; Visentin et al., 2019). The QualyBest Institute surveyed 62 organizations, pointing out that fake news can cause damage to the brand’s reputation organization’s image, generate economic losses, and damage credibility (Quintino, 2022). For example, McDonald’s suffered from a false promotion that caused customers to go to stores with brooms to get a free snack (Santos, 2020).
Humans and robots can disseminate fake news (Shao et al., 2018). Dissemination can also happen involuntarily (due to carelessness and lack of checking) or deliberately (intentionally). This study seeks to understand the involuntary dissemination and the mechanisms to explain this phenomenon.
Individuals are fascinated by everything new and unprecedented, and because fake news was invented, it is appealing. Furthermore, in the age of digital social media, there is a direct correlation between being the first to report the news and being perceived as the best informed. Fake news also reaches much deeper into the public’s subconscious; it arouses greater emotion and more involvement and, consequently, is shared instantly (Kumar et al., 2023). This was confirmed during the 2016 United States presidential election campaign when information claiming Pope Francis had endorsed presidential candidate Donald Trump flooded the web. To give this fake news the perception of truth, the authors also inserted an altered photograph that showed the Pope and Donald Trump together (CNBC, 2016). Over 10 million people saw this publication on Facebook, indicating the extensive reach of fake news spread on virtual social media and how dangerous it can be.
Previous studies showed some reasons why bad-natured individuals create and disseminate fake news. Financial motivations [when fake news is used to generate free online traffic on websites that pay for online traffic or to sell a product or service] and ideological motivations [when fake news is used to manipulate public opinion] are the main reasons for this practice (Tan & Hsu, 2023).
Therefore, in the next chapter, we will address some factors that can impact the spread of fake news.
Factors influencing the dissemination of fake news
Despite being a phenomenon that recently became relevant (since 2016), the advancement of research into fake news and factors that can influence individuals to share certain content is notable (Koohikamali & Sidorova, 2017; Pennycook & Rand, 2021). In cognitive studies, there is evidence that the echo chamber (Corneille et al., 2020; Hassan & Barber, 2021) can influence the attribution of news credibility, as individuals in this situation tend not to seek information outside their “bubble.” Furthermore, people exposed to content containing images (versus without) (Nadarevic et al., 2020) and/or exposed to the same news more than once (Corneille et al., 2020) can also attribute greater credibility to a piece of news, even if it is false, contributing to its dissemination.
Other studies have to understand how news bias, political ideological bias (Rhodes, 2022; Tsang, 2020; Kumar et al., 2023), nudge, social norms (Andi & Akesson, 2020), news source (Bauer & Hohenberg, 2021), skepticism (Nekmat, 2020), and social ties (Moravec et al., 2018) can impact the intention to share fake news. Such studies focus on the impact of an individual’s beliefs and values on the attribution of news credibility and the dissemination of fake news.
Researchers identified that placing the source of the news before the content can influence individuals’ judgment process in discerning the news’s credibility, which enhances the intention to share (Di Domenico et al., 2021; Kim & Dennis, 2019). This and other examples mentioned occur because people do not check the information (Apuke & Omar, 2021) and cannot discern what is fact or fake news (Breakstone et al., 2018).
Despite advances, we found gaps. Therefore, this study seeks to understand the effect of news sources on humans’ involuntary dissemination of fake news. We intend to understand the deliberative process of the individual who receives false news about a brand from a known (versus unknown) source. Therefore, in the next section, we address the source’s credibility and the news.
Source and news credibility
The source of the news is the person or institution that disseminates/shares the news, such as journalists, editors, and magazines/newspapers (Shoemaker & Vos, 2009).
In the context of fake news, especially nowadays, texts and images can be perfectly edited as a form of manipulation. Malicious people can create fictitious fonts to look like real fonts (Bauer & Hohenberg, 2021) and manipulate images by inserting real fonts. Therefore, they could easily persuade and manipulate inattentive people who do not usually check facts.
Factors that can accentuate the effects caused by a fictitious source are a lack of fact-checking (Apuke & Omar, 2021), lack of attention (Pennycook & Rand, 2019), and too much exposure to information (Allcott & Gentzkow, 2017). Nowadays, individuals are exposed to a large amount of information daily, and given this volume, it is practically impossible to check all the information individuals are exposed to. Combined with the lack of attention required when reading information, when an individual is exposed to content with a source, even if fictitious, this tends to activate past beliefs, and through heuristics, people deliberate and judge the source as credible or not.
In this context, when exposed to fake news shared by an existing source, inattentive people can be easily impacted and attribute credibility to the source and, subsequently, to fake news. Malicious actors can manipulate images and insert trusted news sources with a certain perceived credibility. It is also possible that news previously published by genuine sources may be discovered to be false in the future. For example, UOL, a digital news channel, announced in 2017 that the drug Omeprazole caused cancer and later, in 2022, made a new post with an endorsement from a doctor, saying the information was false. However, both news items remained on the website and could have been shared. Thus, people exposed to false news shared by a valid source may believe the news due to previous attitudes and beliefs attributed to the news source. Therefore, at this stage in the process of propagating fake news, when true sources propagate false information, there is greater credibility of the source of the information. Therefore, our first hypothesis is:
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H1: A true source has a direct positive effect on source credibility.
People have subjective impressions, not necessarily conscious, about the credibility of a source, influencing results such as beliefs and sharing intentions (Bauer & Hohenberg, 2021). For example, on social media platforms, people tend to selectively associate with individuals of similar viewpoints and consume information that appeals to their perspectives. The personalization features of social media amplify this effect (Pariser, 2012). Fake news acts as a catalyst to intensify readers’ points of view further and runs the risk of polarizing information (Guess et al., 2018).
In other words, the credibility of the news is often shaped by the personal preferences of the individuals themselves, with the information that pleases them most. Thus, given daily choices, people usually receive information from sources they trust. The associative links that people form in their social networks can shape the source’s credibility. This means that people can give more credibility to news when they already give credibility to the source spreading the news. Thereore, we have the following hypothesis:
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H2: Source credibility has a positive effect on the credibility of the news.
Persuasion through the news source is a widely studied topic (Appelman & Sundar, 2016; Bauer & Hohenberg, 2021; Johar, 2022). It is generally understood that when shared by a source, a piece of news has been reviewed, and, therefore, expertise and credibility can be attributed to the source of the news, given the prior knowledge the individual has about it. With this in perspective, we argue that when there is already prior knowledge about a news source, that is, it is known who the person or institution is that is disseminating that information, there is a greater probability of not only giving credibility to the news (H2) but also to disseminate this information to other people.
The source’s credibility depends on two main factors-objective and subjective-(Bauer & Hohenberg, 2021). The objective factor concerns the veracity of the information disclosed by the source. A source’s trustworthiness is enhanced by accurate information and diminished by false information, if the source is objectively truthful. The subjective factor concerns ideological alignment. Media trust standards suggest that it may not just be objective truth that makes a source credible in recipients’ eyes: people consider media organizations that align with them ideologically to be more trustworthy (Bauer & Hohenberg, 2021).
In this sense, depending on the individual’s previous beliefs about the news source, we believe that a source, when considered credible, can persuade the individual more (versus less) and will increase the chances of spreading fake news. Therefore, we propose a third hypothesis:
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H3: Source credibility has a positive effect on the intention to disseminate fake news.
The same authors argue that people tend to believe the news because of the credibility attributed to a true news source-expertise, credibility, and trust. Given the credibility of the news, attributed to the source’s credi-bility, people tend to share more (versus less) content (Visentin et al., 2019; Pennycook & Rand, 2021). Thus, this validity attributed to the news tends to increase the likelihood of sharing this content.
If the news is considered true, several factors can influence the dissemination of fake news. News about a brand can be shared given its self-relevance (Mishra & Samu, 2021), the perceived relevance for the third party (Mesquita et al., 2022; Sousa, 2022), to improve its social image (Mishra & Samu, 2021; Sousa, 2022), or due to the need for social approval (Mesquita et al., 2022). After accepting the content as fact, given the credibility attribu-ted to the source, individuals can share this content due to several factors. In this study, we focus strictly on the effects of a credible expert and trustworthy source on the individual’s belief in the content, which will be shared more (versus less). Therefore, based on this argument and our entire framework, we also propose the fourth hypothesis of this work:
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H4: The credibility of the news has a positive effect on the intention to disseminate fake news.
In addition to the direct effects, we argue that given the credibility attributed to the news source, based on previous beliefs, the individual will tend to believe the news and then share fake news. This argument is con-sistent with the literature that argues the source’s credibility and other factors can influence news credibility, such as the delivery channel and the structure of the messages themselves (Appelman & Sundar, 2016). It is also consistent with the argument that news credibility is a state and effect rather than a fixed structure or cause of origin (Appelman & Sundar, 2016).
Based on the literature, we suggest that the persuasive power of a message depends on both the perceived credibility of the source and the content (Borges-Tiago et al., 2019; Mishra & Samu, 2021). The likelihood of further propagation increases if the content is perceived as more credible (Visentin et al., 2019). Therefore, we propose the fifth hypothesis:
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H5: Credibility of the news will mediate the relationship between source credibility and the intention to disseminate fake news.
Next, we present the conceptual model of this study (Figure 1) with the relationships proposed by the hypotheses.
METHODS
This section presents the methodological options that guided the empiri-cal phase of this study.
Study context
The aim of this study resulted in us conducting descriptive and quantitative research. Thus, we tested five hypotheses configuring the proposed conceptual model (Figure 1). For this, we constructed a data collection instrument that was applied online to students from three Brazilian universities. We conducted this study in June 2022.
Stimulus
For convenience, we chose CNN News as the known news source. As an unknown source, we created a source (QSF News) with a respective logo. Using a pre-test, we asked 49 university students studying Business Adminis-tration at a higher education institution to assess how well they knew the news sources. Of the 49 students, 44 (89.7%) said they did not know of the QSF News source, and 37 (75.5%) reported that they knew of the CNN News source.
After choosing the sources and carrying out the pre-test, we requested an image processing specialist to develop two identical layouts, except for the source. The layouts simulated news broadcast through Instagram. The news consisted of the following message (fake news): “American Thomas Housner, 42, a former Apple engineer, stated that the low quality of the devices’ batteries is intentional to reduce the useful life of iPhones and induce exchanges by up to two years.” According to Tandoc Jr. et al. (2018) and Wardle (2017), the authors fabricated the news story. Figures 2 and 3 show the manipulations.
Collect data proceedings
We sent the survey link to students at three Brazilian higher education institutions, two private and one public. A teacher who taught in each room distributed the access link, and the students responded during the class period. The teacher did not state completing the survey was a mandatory activity in the subject he taught. Students who agreed to participate, when accessing the platform, saw the following message:
“Hello! We would like to invite you to participate in a survey we are conducting. It is a brief survey that should take a maximum of 10 minutes. There are no right or wrong answers. Generally, your first opinion is the best answer. Do not proceed to the next screens without having performed the task indicated on the current screen. Depending on your device configuration, you may need to use the sidebar to view the entire screen. Can we start? Let’s go.”
Two buttons labeled “I am ready” and “I wish to continue” were at the bottom of the screen. One directed the respondent to the activity and the other to the thank you screen. By agreeing to respond, the survey randomly presented the stimulus. Next to the stimulus, the following message appeared:
“Imagine yourself in the following situation: you opened your Instagram and started viewing the content, and the image below caught your attention. View the image well and read the news below the image. Analyze the image and text without rushing, and when you are ready, select one option that is right after the photo.”
After viewing the stimulus, individuals responded to the questionnaire. The survey directives informed respondents they could take as much time as they needed to avoid time pressure influencing their responses. The questionnaire comprised items from the scales, manipulation check, filter, control, and demographic variables. We used the QuestionPro platform at all stages.
Scales used and sample description
We constructed the research instrument with already validated scales. However, it was necessary to translate the measurement items. We used Harmon and Coney’s (1982) source credibility scale, with seven items. To measure the credibility of the news, we used the four-item scale by Appelman and Sundar (2016). We also used the intention to share fake news scale, composed of three items, by Myrick and Woydynski (2016) adapted from Myrick and Oliver (2015).
We measured involvement with the brand as a control variable (or covariant) using the Zaichkowsky (1994) scale in the version translated by Mesquita et al. (2022). Participants who couldn’t answer what the news was about (manipulation check) were excluded from the sample. We used dummy variables to classify the stimuli as 0 for a false source and 1 for a true source. Below are all items from the psychometric scales used (Table 1).
The manipulation check (which smartphone brand was the news about?) excluded 12 participants. We did not exclude respondents who preferred not to report sociodemographic data (n=7). Therefore, the sample for this study comprised 153 respondents, of which 84 (54.9%) were women. The average age of the sample was 24.41 (σ=7.69) years. The average response time was 12.55 (σ=19.57) minutes. The complete description of demographic variables is presented in Table 2.
DATA ANALYSIS AND RESULTS
This section presents the model adjustment steps, analysis of the collected data, and results.
Adjusting the models
The model was estimated without this involvement variable because there was no significant difference in the level of involvement measured. The results of the confirmatory factor analysis (CFA) indicated a good fit for the conceptual model (Figure 1) since the composite reliability, Cronbach’s alpha values, factor loadings, and AVEs (Average Variance Extracted) scores reached the values recommended by the literature (Fornell & Larcker, 1981; Hair et al., 2014). All factor loadings exceeded the critical value of 0.5 and were statistically significant at the 1% level. Therefore, we kept all items from the original scales. The composite reliability and Cronbach’s alpha values presented values close to or above the limit of 0.7, and the AVEs reached the critical value of 0.5. The analysis procedures guarantee strong evidence of reliability and convergent and discriminant validity.
Concerning discriminant validity, the square roots of the factors exceed the correlations between them, as recommended in the literature (Fornell & Larcker, 1981; Hair et al., 2014). Thus, given the general adjustments, the CFA results indicated good discriminant validity (Table 4).
Next, we checked the quality indicators of model adjustments. Using the Stone-Geisser indicator (Q2>0), the results of the analyses indicated that the models have predictive validity. The results also showed a large effect size (f2 >0.35) for all constructs (Hair et al., 2014). Table 5 presents these results.
Structural model
As recommended in the literature, the significance of the structural path was estimated using the resampling method (bootstrapping) (Ringle et al., 2014) (Table 6). The model tested the relationships between the source (true versus false), source credibility, news credibility, and intention to share fake news. We observed that all paths displayed statistical significance except for the relationship between source credibility and intention to share.
Testing the proposed model confirmed four of the five hypotheses proposed for this study. We noticed that the source (true versus false) positively affected source credibility. The source’s credibility positively affected the credibility of the news, which in turn positively impacted the intention to share fake news. News credibility mediated the relationship between source credibility and intention to share. However, the study did not confirm the direct effect of source credibility on the intention to share fake news, indicating that for there to be an intention to share content, the individual needs to believe it.
The H5 test, the mediation test, was done by testing conditional models with the support of the SPSS software and the PROCESS macro, using model 4 of Preacher and Hayes (2008). We used model four because it is the most appropriate to the conceptual design proposed for this study. This analysis confirmed hypothesis 5. That is, news credibility mediates the relationship between source credibility and the intention to disseminate fake news (β = 0.3015, se = 0.0795, 95% CI [0.1699, 0.4332], t = 3.7916, p < 0.01). Furthermore, we identified that the mediation was complete, as, for this test, we did not find statistical significance for the direct path between source and intention to share (β = 0.0865, se = 0.1388, 95% CI [-0.1431, 0.3162], t = 0.6237, p >0.10).
DISCUSSION
This section presents the theoretical and practical implications of the study.
Theoretical implications
This study focuses on the indirect impact of the news source on the intention to share content. The literature is well documented on the effect of source credibility as an antecedent to news credibility and, in turn, the intention to share content (Petty & Cacciopo, 1984; Park & Lee, 2008; Appelman & Sundar, 2016; Mahapatra & Mishra, 2017; Mena, 2020). Howe-ver, little is known about the effect of a source (true versus false) on the intention to share fake news, especially regarding a high-value brand (Apple).
Other authors tested the effect of a credible (versus non-credible) source (Visentin et al., 2019); these did not aim to explain the intention to share the content but rather the effect of fake news on the brand. Despite finding no effect of the source on the intention to share false content, Bauer and Hohenberg (2021) identified that the true source tends to be more credible. With this, our study presents unprecedented and crucial results about the impact of a true source, even if manipulated, on the credibility of the source and the news and, in turn, on the dissemination of fake news.
In other words, given the lack of fact-checking, the true news source, whether manipulated or not, can induce the receiver to believe the news through their previous beliefs (Appelman & Sundar, 2016). Given the veracity attributed to the news, this false content gains strength to be shared (Mahapatra & Mishra, 2017), especially in the context of a brand.
The source’s credibility depends mainly on the veracity of the information disclosed and the degree of ideological alignment between the source and the receiver (Bauer & Hohenberg, 2021). However, this research went beyond these findings and studied how much the fact that a source is real (versus fake) impacts the source’s credibility and, consequently, the credibility of the news and the intention to share. Our findings suggest that the source must be credible so that consumers give credibility to the source and the news and then propagate it. This understanding is significant because it helps us understand the underlying logic behind fake news and, consequently, theorize solutions that help mitigate these elements.
Another relevant point of our research was the discovery that source credibility is not enough to drive the dissemination of fake news. Recipients need to give credibility to the news. Naturally, all of this is easier when the source of the news is true and not a false or unknown source. The true source helps to endorse the veracity of the message credited by the receiver.
Although there is evidence that a strong brand can mitigate the affects of fake news (Mishra & Samu, 2021), after being given as fact, fake news can equally circulate as a negative word of mouth since when perceiving the content as self-relevant, relevant to their friends, and or even to improve their social image and be accepted by their friends, individuals tend to share content (Mesquita et al., 2022; Mishra & Samu, 2021; Sousa 2022). Thus, when individuals are exposed to content endorsed by a credible (versus false) source, even if manipulated by a malicious individual, they believe and disseminate the content, given the attribution of veracity through previous beliefs (Bauer & Hohenberg, 2021; Johar, 2022).
Managerial and social implications
Our study exposes the ease with which individuals allow themselves to be persuaded. Lewandowsky et al. (2017, p. 360) said, “we are now facing a situation in which a large part of the population is living in an epistemic space that has abandoned the conventional criteria of evidence, internal consistency, and fact seeking.” A worrying aspect is that malevolent actors can-and do-easily invent sources that pose as legitimate online news organizations to spread fake news more easily (Bauer & Hohenberg, 2021). In this sense, brands need to be aware of possible content circulating on Dark Social, content that circulates freely without being tracked. Therefore, brands increasingly need to create ways to track circulating content that could become viral. One way to track this content is to monitor social networks and Dark Social through groups of real consumers.
Brands must actively act to educate people to avoid sharing dubious content. They need to inform their consumers about false content and how this content can persuade people to make them believe it. In other words, as seen here, people cannot simply believe a piece of news because of the source since these can be manipulated. Therefore, individuals should check the content directly on the website of the source that is endorsing the content.
This also has ties to public bodies and society. Although there are already communications about fact-checking agencies, public bodies must warn individuals not to trust content endorsed by sources without first checking them. This is a complex challenge, considering many governments encourage and share fake news for political gain.
Limitations and future research
This study focuses on a descriptive understanding of the relationships. Furthermore, it utilizes a cross-sectional and non-representative sample. Future studies could test these relationships in different contexts and with various brands in a causal way. Another limitation of this article is that we only considered one news platform (Instagram). New studies may consider analyzing fake news relationships on other platforms and social media (e.g., Facebook, Twitter, TikTok), including comparing the performance of these relationships between different platforms.
Additionally, even if we controlled involvement with the brand used in the experimental stimulus, it is possible that participants who had previous or current experience with the brand were affected differently than those who did not have the same experience. Future contributions should replicate the same experimental design in other consumption contexts.
The developed conceptual model encompassed the variables necessary to meet the study’s objective. Even so, to increase the scope of the observed results, further research could also analyze the moderating effects that intensify or attenuate the relationships between the credibility of the source (or news) and the intention to share. For example, we believe that variables linked to cognitive aspects such as self-determination, self-construction, tendency to maximize, and goal framing can be analyzed as moderating varia-bles. The logic behind this suggestion is that a large part of the behavioral intention to share news arises from aspects linked to the human mind.
Another valuable front of research may be the co-creation or co-destruction of value (Vargo & Lusch, 2004, 2008; Dolan et al., 2019; Ribeiro et al., 2023). We know that positive interactions between consumers and companies (e.g., active customer participation in the experience or suggesting improvements) can co-create value. In contrast, negative interactions (e.g., negative reviews and dialogue on travel websites) can co-destroy value. However, we still know little about how fake news and, by extension, the source’s credibility and news affect the co-creation or co-destruction of value in companies, brands, and tourist destinations. Thus, new research can attempt to analyze fake news in co-creation or co-destruction of value. For example, tourist destinations can advertise with altered images and videos that the water on their beaches is crystal clear. If tourists eventually disseminate this information, the value of this destination may be co-created based on fake news. However, what are the consequences of this? We do not know yet.
Data availability statement
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