Introduction

Advertising discourse has changed from being focused on the qualities of the product or service to projecting narratives more focused on emotion and user experience. At the same time, digital platforms take advantage of the possibilities of interaction with audiences and user-generated content (UGC) to co-create brand discourse within digital communities. Thus, through social marketing and branded content strategies, brands provide their audiences with symbolic representation, turning them into unofficial brand ambassadors (Brooks et al., 2022).

Despite the growing interest in the scholarly community in converting advertising into storytelling that creates communities in social networks, few efforts have been made to compare the interactions generated about the same product or service from its officially owned media and the User-generated content (UGC).

User-generated content

User-generated content (UGC) is a relatively recent concept that has gained particular relevance thanks to the possibilities of digital content creation and discussion in forums and social networks by target audiences (Christodoulides et al., 2011). According to Christodoulides et al., (2012), UGC is characterized because: (1) it is available in some publicly accessible environment, such as the Internet; (2) it reflects some degree of creative effort and; (3) it is created by practices and routines that are free and external to the brands. Thus, the adaptation and appropriation of advertising messages and storytelling by non-professionals not linked to the brand are one of the ways in which UGC is produced (Castillo-Abdul et al., 2022).

Although UGC is a neologism, its practice is not, since as early as 1995, the academic literature differentiated between commercially published materials and those produced by audiences under names such as Word-of-Mouth (WoM), co-creation or appropriation of the brand message (Cheong and Morrison, 2008; Hung and Li, 2007). However, thanks to ICT and social networks, this type of content has become more visible and influential since there has been a change in the communication model from being unidirectional (one-to-many) based on conventional media, to a multidirectional and interactive one (many-to-many), based on online platforms (Hoffman and Novak, 1996).

Berthon et al. (2008) explained that there are three primary motivations for users to generate advertising content: (1) “intrinsic enjoyment,” in which the stimulus follows the purpose of self-expression; (2) “self-promotion” in which consumers use the promotion of a brand to promote themselves in their communities and; (3) “change perceptions” in which the objective is to make other consumers see the brand differently.

In the same direction, Daugherty et al. (2008) explained five motivations that consumers may have to create content for brands: (1) “utilitarian function” (e.g., generate UGC for monetary incentives); (2) “knowledge function” (e.g., produce UGC to understand how the product works); (3) “value-expressive function” (e.g., produce UGC as a form of self-expression); (4) “ego-defensive function” (e.g., create content to feel part of a group) and; (5) “social function” (e.g., create content to interact with a community) (Cuesta-Valiño et al., 2021).

According to this, there are two general motivations for user-generated content marketing: the one carried out by users for personal motivation, i.e., in which there is no exchange or incentive beyond the interaction in social networks (Bonilla-del-Río et al., 2022), and the one based on economic incentive, either for promotional content and advertising or for exchange of products and services. The first category includes the general public, especially younger generations, such as millennials or centennials, while the second category usually includes influencer marketing (Castillo et al., 2021).

However, users do not usually develop UGC for personal motivations without a pre-existing brand strategy (Ma and Gu, 2022) that drives social interaction. Not surprisingly, marketing and advertising agencies are increasing their investments in creating campaigns whose narratives give rise to co-creation and advertising appropriation by users. According to Poch and Brett (2015), extrinsic rewards (economic incentives) lead to more positive intentions to create UGC than intrinsic motivations. However, they observed an altruism effect that reveals that consumers with a high degree of altruism are likelier to create positive content, such as tutorials and recommendations for their community of followers.

For their part, Asmussen et al. (2013) and van Doorn et al. (2010) found a positive correlation between engagement and intrinsic (personal) motivations for creating user-generated content, with the stimulation of content through the provision of branded content being a determinant of this (Kang, 2018; Wirtz et al., 2013).

On the effects of UGC on brands, Nagoya, Bernarto and Antonio (2021) and Radovic et al. (2021) argue that brand-generated content and UGC positively affect organizations’ values and intangible assets. Diwanji and Cortese (2020) found that brand-generated content, rather than user-generated content, strongly influenced firms’ attitudes toward their stakeholders, while Irelli and Chaerudin (2020) confirmed that consumers’ perceptions of user-generated content positively impacted purchase intention (Gutiérrez Rodríguez et al., 2017).

Moreover, Goh, Heng and Lin (2013) demonstrated that participation in brand communities on social networks positively increases purchase expenditures and that UGC affects consumer purchase behavior through embedded information and persuasion, as natural prescribers enjoy greater credibility than corporate ones.

Unofficial brand ambassadors and influencer marketing

Brands need digital communities as a captive advertising audience for the visibility and reach of their communication campaigns, consumer loyalty, and purchase behavior. In this sense, to generate interactions that in social networks translate into greater visibility, reach, and relevance of campaigns, brands often use strategies of appropriation of the message through challenges, filters, and avatars that link their digital community and turn the message into something that takes on a life of its own from the UGC (Romero-Rodriguez and Castillo-Abdul, 2023). In other words, through social marketing strategies and branded content, brands give their audiences a symbolic representation, turning them into unofficial brand ambassadors (Brooks et al., 2022).

The messages co-created by UGC from brand campaigns, altruistically or for personal non-economic motivations, are very different from influencer’s content marketing because, with influencer marketing, organizations seek those profiles of prescribers with a large audience reach within a specific segment and make economic agreements or exchanges for the exposure of brand products or services, while Unofficial Brand Ambassadors can adopt the brand messages and exposure of their products on their initiative or by some strategy of providing branded content (Fig. 1).

Fig. 1: Differences between Influencer’s content marketing and Unofficial Brand Ambassadors.
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While influencer marketing is an economic advertising activity in which the brand usually has control of the messages, UGC tends to be audience dynamics without brand control. Source: Romero-Rodríguez and Castillo-Abdul (2023).

While influencer marketing usually includes a contract or advertising representation agreement that explains the brand’s obligations and exposure limits, this is not the case with Unofficial Brand Ambassadors, which can represent a potential risk for the brand. In this regard, it must be understood that advertisers can control many aspects of Influencers before hiring their services, such as their profile, the target customer base of their followers, and the content and exposure of messages about the brand. However, they cannot do so with Unofficial Brand Ambassadors since they generate messages on their initiative or by providing branded content, of which they can make a free interpretation not tied to contractual terms.

Social media interactions and effects

Most of the academic literature has focused on the effect of celebrity campaigns on mainstream media, explaining that these public personalities have an enormous influence on audiences’ attitudes, behaviors, and decision-making (e.g., Hoffman and Tan, 2013, 2015). Celebrity endorsements can enhance a brand’s value and product’s desirability, conferring social capital (Ohanian, 1990; Till and Shimp, 1998). More recent neuroscience research has shown that brain regions that create positive associations are activated by seeing or hearing celebrity endorsements (Klucharev et al., 2008; Sung et al., 2018).

Trust is a factor that impacts eWom (electronic Word-of-Mouth) in social networks. The higher the level of familiarity of the audience with these influencers, the greater the likelihood that they will be involved in the search, broadcast, and transmission of opinions about products (Shu-Chuan & Yoojung, 2011), so consequently, it is assumed that the message produced by UGC will have a more significant impact, reach and effectiveness than those made by the official owned media, especially because of the credibility of them.

Unlike celebrities in conventional media, brand endorsement information is often implicit in UGC, and sponsors tend to use different tactics than those employed by advertisers on traditional media platforms to maximize impact and trust with their followers. For example, users may use “digital native” advertising strategies similar to product placement, such as posting selfies with a product, using product-branded backgrounds (Ashley and Tuten, 2015; Campbell et al., 2014), but also doing product experience reviews (so-called “haul”), unboxing sessions or virtual tours.

This leadership of specific users with significant social capital encourages many commercial brands to find in the profiles of these opinion leaders the ideal space to penetrate, in a non-intrusive way, the imaginary of their target audiences and to adhere to the credibility and trust transmitted by the prescriber. In this sense, the business model of platforms such as Instagram, TikTok, YouTube, Twitch, or Facebook, where Social Media Influencers upload their creations, is based on the attention economy, mainly because accessing their content is free for the user. However, these users’ attention is marketed and monetized to brands based on the traffic generated by this content (Brooks et al., 2022).

According to Romero-Rodriguez and Castillo-Abdul (2023), in the attention economy, brands face an over-saturated sea of advertisements competing for audience awareness and the credibility of messages and engagement. In this regard, the most effective strategies to approach the public are non-invasive and user-generated, with a more natural message focused on the storytelling of opinions and experiences (Gutierrez Rodriguez et al., 2017). As a result, UGC becomes an ideal strategy, as it combines the naturalness of a user’s exposure with media exposure to a group of followers on social networks who trust the content creator.

Methods

The main objective of this research is to identify which narrative elements used by the official accounts of the nation branding on Instagram and by the users (UGC) of hashtags promoted from those official accounts generate higher organic interaction on that social network (likes and comments). Likewise, with a correlational view, we seek to compare whether the promotion of countries in both cases generates more interaction between those generated by owned media and users. In this sense, the following research questions (RQ) arise:

  • RQ1: What types of posts generate the most interaction and reach in owned media and UGC?

  • RQ2: What narratives and resources enhance the interaction and reach of owned media and UGC publications?

  • RQ3: Does UGC generate more interactions on the nation branding than owned media?

In order to meet the proposed objective and to be able to answer the research questions, this study has a quantitative design and a descriptive and correlational scope since it seeks to interrelate effects and interactions in terms of narratives or types of content.

As interactions (likes or comments) are this study’s primary target, it is important to note some characteristics. Both (likes and comments) are defined as «count» data, meaning it is not continuous, has a minimum of 0, and (in this case) has no defined maximum. Also, likes and comments follow a Poisson distribution (bell-shaped but highly skewed to the left). Therefore, using ANOVA tests or similar is not the best practice. For multiple group comparisons (3 or more), a Dunn’s post hoc test was used to determine which group was different. Paired with different sample sizes for some of the desired comparisons, this meant that a Kruskal–Wallis Test was the best option to determine the statistical difference between groups.

Instrument

To conduct the content analysis, both in the official accounts of the country brands and the UGC on Instagram, two quantitative analysis sheets were designed and validated by expert judgment (Table 1). These instruments were built from instruments of previous studies such as those of Laestadius & Wahl (2017), Vasallo et al. (2018), Brooks et al. (2022), Castillo-Abdul et al. (2021), and Castillo-Abdul et al. (2022).

Table 1 Analysis sheet variables of both instruments.

The analysis was conducted by three coders and was performed in Spanish because it is the official language of the five selected country brands. Inter-coder reliability was achieved because two of them independently analyzed the whole sample, while the third coder reviewed the categorizations and decided on cases of mismatches.

Sample

In order to select the sample, we first conducted an exploratory review of 23 official profiles (owned media) on Instagram of country brands of Ibero-American States. In this exploration, sample inclusion criteria were sought, such as: (1) That they are active profiles (they have not had more than one month without publications); (2) That they have carried out campaigns to promote destinations, both for tourism and to attract investment and; (3) That they use a specific hashtag for all their campaigns.

Using these criteria, five official country brand profiles were selected: Argentina (Ar) (@marcapaisar), Ecuador (Ec) (@ecuadortravel), Mexico (Mx) (@visitmexico), Panama (Pa) (@visitpanama) and Venezuela (Ve) (@minturvenezuela). For each profile, the last 20 posts of 2022 were selected (for a total of 100 country-branded posts), eliminating from the selection those that are not directly related to the promotion of the country (e.g., Christmas messages).

From the review of these official profiles, a series of hashtags with which these accounts promoted the conversation on their social networks were determined, such as (Ar) #Argentina, #OrgulloArgentino, #TurismoArgentina; (Ec) #VisitEcuador, #Ecuador, #EcuadorPrimero; (Mx) #VisitMexico; (Pa) #Panama, #VisitPanama, #Liveformore; (Ve) #Venezuela, #Ven, #MidestinoesVenezuela.

Using these hashtags, the first 100 featured posts produced by users (excluding corporate profiles) were chosen. Instagram ranks these publications by relevance criteriaFootnote 1. To eliminate bias in the post retrieval, an ad hoc email was created with which an account with no previous activity on Instagram was accessed. The search and data processing was performed between December 12, 2022, and February 13, 2023.

It is important to explain that Instagram’s algorithm benefits those posts that generate the most interaction, placing them at the top of the search option as “featured posts”. In this sense, although the sample selection has been random (the first 100 results of each campaign in each country based on the hashtags), these prioritized results coincide in being those that obtain the highest number of interactions (likes and comments).

Nation brand dataset

The Owned-brand/Owned-media dataset consists of 100 total entries, with 20 entries per country. The characteristics of the individual posts do not follow a set distribution regarding the post type or other characteristics. Table 2 shows the overview of likes and comments.

Table 2 Owned media like and comment overview.

User-generated content dataset

The UGC dataset consists of 502 total entries, with 100 or 101 entries per country. As with the owned media dataset, distribution outside of entries by country is not standard (there are only 5 video posts, while two countries only have reels as a post type, for example) (Table 3).

Table 3 Users like and comment overview.

Results

Owned media: correlations between narrative, contents, and interaction

Going by Post type, the Kruskal–Wallis Test determined that at least one of the groups was significantly different in terms of likes with p = 0.00018***, Dunn’s post hoc test (Table 4) determined that Reels differed from Photo rolls or single Photographies (Video had too few instances to test), while Photo rolls and single photos are not statistically different.

Table 4 Dunn’s post hoc test values for owned-brand likes.

Surprisingly, Fig. 2 shows Reels obtaining significantly fewer likes than other types of posts. No significant difference was found for post types regarding comments.

Fig. 2: Likes per post type for owned media.
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Photo content is the type of content on Instagram with the highest positive reactions, while videos and reels have lower reaction rates. In the analysis of country accounts, Argentina and Mexico are where this phenomenon can be most verified.

Contrary to what might be expected if a contest (giveaways) was present on a post, the Kruskal–Wallis Test determined the “No” and “Yes” groups to be significantly different in terms of likes with p = 0.0247*. Figure 3 shows that for owned media, giveaways generated significantly less likes. Going by if the post-promoted interactions, the Kruskal–Wallis Test determined the “No” and “Yes” groups to be significantly different in terms of comments with p = 0.0198*. Figure 4 shows that promoting interactions generated significantly more comments for owned media.

Fig. 3: Likes when a contest (giveaway) is mentioned for Owned media.
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Contrary to the popular belief that contests promote interaction on social networks, this study shows that the number of likes on this type of content significantly reduces interaction.

Fig. 4: Comments when promoting interactions for owned media.
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Posts that promote interactions (e.g., asking questions to the audience or seeking feedback) generate more interactions, especially comments.

It is also noteworthy that in the national brands studied, the presence of celebrities and influencers did not generate statistically representative differences in interactions (likes and comments). No statistical differences were found for either likes or comments regarding the presence of special effects or social responsibility content in brand posts. Also, no statistical differences were found for either likes or comments regarding the presence of tourism ads celebrities in brand posts.

UGC: correlations between narrative, contents, and interaction

Going by Post type, the Kruskal–Wallis Test determined that at least one of the groups was significantly different in terms of likes with p = 3.0631e-23***, Dunn’s post hoc test (Table 5) determined that Reels differed from Photo rolls, single Photography, and Videos, Photo rolls were different from Reels and single photos, single photos were different from Reels and Photo Rolls, and video is only different from Reels.

Table 5 Dunn’s post hoc test for user likes.

Going by Post type, the Kruskal–Wallis Test determined that at least one of the groups was significantly different in terms of comments with p = 9.7926e-10***, Dunn’s post hoc test (Table 6) determined that Reels differed from Photo rolls, single Photography, and Videos. Other post types did not differ. Figure 5 shows Reels obtaining significantly more comments and likes than other types of posts.

Fig. 5: Likes and comments per post type for UGC posts.
figure 5

In contrast to the interactions generated by country brands (Fig. 2), in UGC publications, Reels are by far the type of content that produces the highest rates of reactions (likes and comments).

Table 6 Dunn’s post hoc test for user comments.

Going by if the destination appeared on a UGC post, the Kruskal–Wallis Test determined the “No” and “Yes” groups to be significantly different in terms of likes with p = 7.5471e-6***, and comments with p = 8.5563e-5***. Figure 6 shows that the destination appearing in the post for user posts generated significantly more likes and comments.

Fig. 6: Likes and comments by the presence of destination for UGC posts.
figure 6

User-generated content posts about country brands that included images and videos of tourist destinations generated significantly more interactions.

Going by user post sentiment, the Kruskal–Wallis Test determined the “No” and “Yes” groups to be significantly different in terms of likes with p = 1.0143e-8***, and comments with p = 3.4877e-7***. Figure 7 shows that a positive sentiment generated significantly more likes and comments for user posts.

Fig. 7: Likes and comments by sentiment for UGC posts.
figure 7

As expected, posts with positive content generated more interactions.

No statistical differences were found for either likes or comments regarding the presence of the owned-brand in user posts.

Correlation heatmaps

We can observe in Fig. 8 that likes and comments are highly correlated, that aside from the use of special effects, mentioning social responsibility, or promoting interactions, most other strategies appear to reduce engagement with the users. For these correlation maps, “Yes” and “Positive” answers were replaced with 1, and “No” and “Neutral” were replaced with 0. There were no negative sentiments in these datasets.

For UGC posts (Fig. 9), likes and comments are somewhat correlated but less than in owned media. Brand appearances reduce engagement, but special effects, destination images, and sentiments might slightly promote engagement. The presence of a destination image highly correlates with positive sentiments and somewhat with the presence of special effects.

Fig. 8: Correlation heatmap for owned media.
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The heat map shows a notable correlation between likes and comments for owned media, with other features having little to no correlation or even a neagtive effects on interactions.

Fig. 9: Correlation heatmap for user posts.
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A smaller correlation between likes and comments was found for UGC compared to owned media, and positive sentiments were highly correlated with the presence of a destination image.

UGC vs. owned media: differences between content origins

Overall, the Kruskal–Wallis Test determined the Owned Brands and UCG groups to be significantly different regarding comments with p = 0.0071**. Figure 10 shows that user posts generated significantly more comments.

Fig. 10: Overall comments of Brands and Users.
figure 10

User-generated content generated significantly more comments than official country brand accounts.

Going by country, the only significant difference was seen in Mexico, with a similar result to the overall groups: the Kruskal–Wallis Test determined the Owned Brands and UCG groups to be significantly different in terms of comments with p = 0.0111*. Figure 11 shows that user posts generated significantly more comments for Mexico than Owned brands.

If we compare post types, some interesting differences show themselves: for the Photographs and Photo Rolls, Owned brands generate more likes than UGC. The Kruskal–Wallis Test determined that Owned Brands and UCG groups are significantly different in terms of Likes for Photographs with p = 9.2421e-8***, and Likes for Photo Rolls with p = 0.0003***. Figure 12 shows these results.

However, this relationship reverses when talking about Reels, the most popular user post type. The Kruskal–Wallis Test determined that Owned Brands and UCG groups significantly differ regarding Likes and Comments, with p = 0.003** and p = 0.0008***, respectively. Figure 13 shows UGC easily overshadowing Owned Brands.

Fig. 11: Comments for brands and users in Mexico.
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In the case of Mexico, it could be more easily evidenced that Instagram could shadowban the publications of country brands that do not advertise.

Fig. 12: Likes for brands and users for photographs and photo rolls.
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Photographic content generated a higher rate of interactions in the official country brand accounts than in the UGC.

Fig. 13: Likes for brands and users for reels.
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In contrast to photographic content (Fig. 12), Reels generated higher interaction rates in UGC.

Conclusions and discussion

In response to RQ1, which inquired about which types of posts generate higher levels of interaction (likes and comments) and reach in owned media and in the UGC, the data are very different in the comparison. As observed in Fig. 1, Photo Rolls have the highest interaction on official accounts, with Reels having the fewest likes. On the contrary, in user-generated posts (UGC), Reels get more than three times as many likes and comments as other types of posts (photos, videos, and photo Rolls). This may be because the platform makes Reels from non-corporate accounts more visible, while it shadowbans those from corporate accounts not paid with advertising in the Instagram stories section.

Photographic contents (photography and photo roll) in owned media achieve higher interactions (likes and comments), while in UGC posts, Reels reach almost six times more interactions than other types of posts. In this sense, it is important to highlight that in the content strategies of nation branding, it is essential to focus on visual content, while for vertical videos (Reels), it is better to use influencer marketing strategies, which achieve greater reach and, consequently, interactions with the brand (Figs. 12 and 13).

These results are aligned with Castillo-Abdul et al. (2022) on the strategic need for brands to define what type of messages and posts work for their owned media and to find referents and brand ambassadors, such as influencers and celebrities with great social reach, to support advertising strategies on those platforms and types of content in which their owned media have less reach. This sense of co-creation and redefinition of messages and, above all, of the official storytelling to a more natural one, as occurs in UGC (Cheong and Morrison, 2008; Hung and Li, 2007), can have a positive impact on the reach and notoriety of the campaign, but also -and more importantly- on the engagement of the corporate audience.

Regarding RQ2 on the types of narratives and resources that enhance the interaction and reach of owned media and UGC posts, it was surprising that contests (giveaways) generated fewer likes. However, as expected, those posts that promote interactions with the audience (such as asking questions) generated significantly more comments than those that did not. It is important to remember that with more likes and comments, the organic reach of a post increases so that the brand can achieve a larger audience and social capital.

It should be understood that ordinary users can also be multipliers of the nation’s branding message when sharing the messages of owned media and professional influencers. Taking advantage of this multiplication of digital social capital (also called viralization of content) is one of the objectives of many advertising agencies specializing in online advertisement. Nevertheless, it should also be understood that it is not common for users to become unofficial brand ambassadors for simple personal and altruist motivations (Poch and Brett, 2015; Romero-Rodriguez and Castillo-Abdul, 2023) without a pre-existing brand strategy that links them and promotes audience participation (Asmussen et al., 2013; Ma and Gu, 2022; van Doorn et al., 2010).

In addition to the increased outreach of the campaign, UGC on brands enhances the perceived intangible values and assets of the brand (e.g., its image and reputation), as user-generated messages have greater credibility in public opinion than corporate messages themselves, which, by nature, are biased (Irelli and Chaerudin, 2020; Nagoya, Bernarto, and Antonio, 2021; Radovic et al., 2021), so UGC has greater persuasive power on the audience (Goh, Heng, and Lin, 2013).

Contrary to what might be expected, social responsibility content from owned media did not report statistically representative differences in the interactions generated. Likewise, those posts featuring influencers and celebrities from owned media did not generate more interactions. The latter result largely contradicts most of the scientific literature on the effect influencers and celebrities have on campaigns (e.g., Hoffman and Tan, 2013, 2015; Klucharev et al., 2008; Ohanian, 1990; Sung et al., 2018; Till and Shimp, 1998), and could open the door to a new debate on whether influencers are becoming in the minds of audiences an extension of brands’ official discourse and whether this affects message credibility and, consequently, on interactions.

In fact, in this exploratory study, it seems clear that non-professional UGC has greater reach and interaction than influencer and celebrity content, although it must also be said that in line with Shu-Chuan & Yoojung (2011), the real effect that influencers have happens when the audience of the campaign has a high level of familiarity with it. Therefore, brands should not only pay attention to the types of messages and platforms used by these professional influencers but also the choice of the influencer’s profile should be in line with the target audience to which the campaign is addressed.

On the other hand, UGC posts where the destination appears (mainly as a tourist attraction) generate more than twice as many interactions as those in which the destination does not appear. Likewise, posts with positive sentiment content achieved more than twice as many interactions as those with neutral sentiment. This may be closely related to the fact that audiences use social networks as a means of leisure and entertainment, so messages should flow naturally in scrolling and zapping (Romero-Rodriguez and Castillo-Abdul, 2023), i.e., they should keep linearity with the prevailing storytelling in each social network, which is generally contents with many graphic stimuli.

Finally, concerning RQ3, UGC posts have been shown to generate more comments than owned media by a factor of at least four overall and for Mexico. Considering all five countries and all types of posts, there is no significant statistical difference for like generation, but there are some cases where these smaller groups show differences. Owned media generates more likes in the single Photograph and Photograph Roll type posts, but it is important to note that these types of posts are far below Reels in popularity for users. This popularity difference can also be seen in the interactions generated for Reels by UCG, as these are approximately six times more numerous than the ones generated by owned brands.

The main theoretical implications of this study point out that contrary to what has been continuously stated in the scientific literature on the positive incidence of the use of celebrities in advertising (e.g., Hoffman and Tan, 2013, 2015; Klucharev et al., 2008; Ohanian, 1990; Sung et al., 2018; Till and Shimp, 1998), in this exploratory study the posts from owned media with the presence of celebrities and influencers did not generate greater interaction than those in which they did not appear. In fact, some posts made by non-professional UGC achieved greater reach and interaction, which could begin to highlight the relativity of the effect of the use of influencers in these types of campaigns, or that these campaigns are not correctly defining the celebrity or influencer concerning the target audience of the campaign or the platform.