Abstract
This article investigates the values expressed by good morning memes—an understudied subgenre of social media inspiration featuring a “good day” wish—and the criteria that users from different countries and generational groups adopt to evaluate them. Expressed values were detected through a content analysis of 414 memes in English and Italian, while insights about evaluation were derived from 20 semistructured interviews with American and Italian social media users. Analysis revealed cross-cultural divergences in the core values conveyed in the two subsets, with self-efficacy foregrounded by English memes and met with humorous skepticism by Italian memes. Interview data revealed a cross-generational cleavage in the interpretation of the genre based on communicative values, with younger users negatively evaluating the memes as inauthentic due to a lack of creativity and older users appreciating them as genuine attempts to cultivate affiliation between users. Such generational distinctions emerged as crucial to the establishment of a three-way connection between an imagined audience of older users, content types framed as kitsch such as good morning memes, and specific platforms, especially Facebook. The article concludes that such heuristic associations infuse the ways in which people visually imagine social media platforms, coalescing into recognizable platform aesthetics: notions of what platforms look like based on who we believe inhabits them.
In recent years, generation has resurfaced as a crucial social cleavage. Reporting on the popularity of the “Ok, Boomer” catchphrase, The New York Times declared “the end of friendly generational relations” (Lorenz, 2019). Noticing emerging intergenerational divides in youth culture, The Guardian wondered if “Gen Z-ers hate Millennials now?” (Noor, 2020). Academic research has also picked up on this societal trend, suggesting that digital media is playing a pivotal role in the re-discovery of generational labels as meaningful social categories (Anderson, 2023; Zeng & Abidin, 2021). Most of this research investigates how generationally defined social groups (Baby Boomers, Gen X, Millennials, Gen Z) frame themselves and other generations in digital content, especially memes (e.g., Carter, 2021). So far, however, little attention has been devoted to how generation influences the expression of values on social media and the evaluation of content produced by generationally defined “others.” Furthermore, the cross-cultural salience of generational divides is often inferred but seldom tested systematically.
In this article, I use the concept of valuation as a prism to investigate how generation and culture intersect in digital spheres. Following Heinich (2020), I define valuation as the process through which individuals assign worth to things, people, or states of affairs. Valuation is intertwined with the notion of taste and its role in the acquisition of cultural capital (Bourdieu, 1984), as different notions of what is worthwhile create social distinctions based on class, age, or nationality (Lizardo & Skiles, 2015). Such dynamics are intensified in digital spheres, where knowledge of the ever-changing rules guiding the evaluation of content requires high levels of subcultural literacy (Nissenbaum & Shifman, 2017).
Good morning memes offer an illuminating case study to investigate the interplay between generation and culture in the valuation of social media content. Good morning memes are a subgenre of social media inspiration (Dale et al., 2020; Rieger & Klimmt, 2019) popular among older cohorts of users. These memes feature text with a wish for the upcoming day, usually paired with images of coffee mugs, flowers, or cute animals against a solid or natural background. While some studies have presented cross-cultural analyses of inspirational content (e.g., De Paola & Hakoköngäs, 2020), the subgenre of good morning memes and the lens of generation have so far been neglected. Addressing this gap, I investigate the core values expressed in good morning memes and the principles that social media users adopt to evaluate them. My analysis highlights that social distinctions between communities of users based on appreciation or distaste for seemingly trivial digital artifacts such as good morning memes shape our shared platform imaginaries (van Es & Poell, 2020), especially their visual component.
In the first part of the article, I chart a theoretical understanding of good morning memes as digital artifacts that express values and that, in turn, are objects of evaluation reflecting taste-based social distinctions. I then introduce the case study: a sample of English and Italian data designed to capture potential divergence between “global” and “local” incarnations of the genre. The methods section details the two analytical processes of this study: a content analysis of memes in English and Italian, and semistructured interviews with users based in the United States and Italy. The findings of the content analysis indicate that good morning memes largely follow a shared global template, yet also present meaningful elements of cross-cultural variation regarding the prominence of self-efficacy. The interviews reveal that generational taste is crucial to the evaluation of the genre, with different age cohorts expressing divergent opinions based on different understandings of the communicative value of authenticity. In conclusion, I reflect on how these divergences are core to the classification struggles that produce imagined connections between users, content types, and platforms. In turn, I suggest that these associations infuse the visual component of how people think of and relate to social media (Hallinan et al., 2021; van Es & Poell, 2020), coalescing into specific platform aesthetics: notions of what platforms look like based on who we believe inhabits them and the content they value.
Literature Review
Classification Struggles, Generation, and Memes
The production of cultural artifacts and their valuation are key practices through which different social groups distinguish themselves. Following Heinich (2020), I define valuation as the social processes through which “value” is assigned to objects, people, events, or states of affairs. In this context, value is defined as (1) the worth of an object, (2) those objects that are regarded as worthy (e.g., technology, family), and (3) the principles according to which worth is assigned to objects (e.g., authenticity, creativity). Valuation is crucial to what Bourdieu (1984) calls “classification struggles”: processes of symbolic contestation that set the boundaries of different social groups. By expressing what they value through the artifacts they produce and by showing appreciation or distaste for the artifacts produced by others, individuals mark their membership in a social group and their alterity from those with different values.
Sociotechnical environments are not immune from these dynamics and often constitute a field where different groups perform taste-based distinctions (Pitcan et al., 2018). In online classification struggles, the sharing and appreciation of memes contribute to the reproduction of social distinctions (Literat & van den Berg, 2019). Following Shifman, I define memes as groups of digital items that are circulated and transformed by Internet users and share common characteristics of content, form, and/or stance (Shifman, 2013, p. 41). Memes are groups of texts featuring variation alongside a shared “core” that ties together all of their individual incarnations (Segev et al., 2015).
Class distinctions are obviously relevant to the valuation of user-generated content (see Yates & Lockley, 2018). However, a different social cleavage has proved pivotal for the case of good morning memes: generation. Even though the category of generation is somewhat marginal in Bourdieu’s work, the notion of classification struggles can be applied to “all types of social classification, irrespective of the ‘content’ of those classifications” (Purhonen, 2016, p. 100). Furthermore, as pointed out by Edmunds and Turner, Bourdieu considered generational struggles as “especially important in major ruptures in taste and practice” (Edmunds & Turner, 2002, p. 13). Indeed, recent global and local crises (e.g., the COVID-19 pandemic, post-Brexit economic recession) foregrounded generation as a crucial cleavage between social groups with different understandings of the crises’ causes and possible solutions (Pina-Cabral & Theodossopoulos, 2022, p. 456). Thus, while narratives such as the “generation war” between Baby Boomers and Millennials are often reductionist (White, 2013; see also Bristow, 2021; Elliott, 2022), they nonetheless represent key instances of symbolic contestation through which the boundaries of generationally defined social groups are negotiated (Connolly, 2019).
In recent years, social media has been a prime site for the articulation and contestation of generationally defined social categories (Bolin, 2016). An example of this trend is the “OK, Boomer” catchphrase, used by Gen Z TikTok users to tag memetic content in which they express discontent toward Baby Boomers for causing climate change and upholding oppressive social norms, among other complaints. “OK, Boomer” acted as a rallying cry to express a generational identity built around the values of environmentalism and freedom of expression (Zeng & Abidin, 2021). While some interpreted the phenomenon as a purely antagonistic youth fad (e.g., Anderson, 2023), I suggest that “OK, Boomer” is an example of a classification struggle that uses memes to distinguish generationally defined groups based on their values.
Value-based distinctions between generations of users like the one surfaced by “OK, Boomer” memes have important implications for the ways in which people imagine and relate to social media (Hallinan et al., 2021; van Es & Poell, 2020), as they often result in heuristic associations between audiences, content types, and platforms. The audience-content-platform association is arguably crucial to Manovich’s (2016) notion of “Instagram-ism,” coined to describe the atmospheric, pristine, and emotional aesthetic dominating Instagram’s mainstream because of its popularity among a “new global digital youth class that emerges in early 2010s” (p. 119, emphasis in the original). A similar set of associations is invoked by Zappavigna and Ross (2022), who select the Instagram hashtag #avotoast as a fruitful case to study food ideology in digital spheres because of its ubiquity on the platform and its commonplace depiction as an over-indulgent brunch choice favored by Millennials. Audience-content-platform associations are neither exclusive to Instagram, as testified by TikTok’s reputation as a platform saturated by Gen Z dance challenges (Cervi, 2021), nor limited to generation, as exemplified by 4Chan’s association with far-right meme production (Tuters & Hagen, 2019).
Memetic Values and the Social Production of “Good Taste” in Memes
Meme literacy—the ability to recognize the codes and subcultural references of which memes are ripe—often functions as a marker of social belonging, as it requires keeping up with the fast-paced and unstable vernacular of specific online communities (Nissenbaum & Shifman, 2017). Meme literacy encompasses knowledge of community-specific canons to discriminate between memes that are “in good taste” and memes that are not, setting those that are “in the know” apart from those that aren’t (Milner, 2012). In turn, liking or disliking specific memes creates status distinctions between users with “good” and “bad” taste (Nissenbaum & Shifman, 2017, p. 486).
Memes are a highly diverse format of user-generated content expressing a wide range of core values—ideas about the desirable that govern individual and collective thought and behavior (Schwartz, 2012). Despite this variance, Shifman (2019) argues that memetic expression promotes a narrow set of communicative values: norms mandating how we should speak about the world. Shifman’s list of memetic values includes authenticity, creativity, communal loyalty, freedom of information, and expressive egalitarianism. Authenticity, communal loyalty, and creativity are crucial to how individuals evaluate memes and the people who post them. Widely regarded as key to communication in digital spheres (e.g., Senft & Baym, 2015), authenticity refers to the correspondence between statements and an observable truth (“external authenticity”) or the deep essence of the person speaking them (“internal authenticity,” see Shifman, 2018). Communal loyalty and creativity refer instead to the tension between fixity and novelty inherent to memes. Any meme must be loyal to a template to be recognizable, but must also creatively rework that template to be appreciated as more than a copy (Milner, 2012).
Good morning memes arguably represent an example of what Trillò et al. (2022) define as social media rituals of “relationship work” (see also Burgess et al., 2018). These are typified communicative practices on social media that initiate, maintain, or repair relationships with others. While specific genres may express a diverse range of content-level values, good morning memes and other rituals of related work such as Facebook birthday wishes (Theodoropoulou, 2022) or YouTube apology videos (Choi & Mitchell, 2022) are tied together by their commitment to the core values of care and intimacy as well as the communicative value of affiliation. By using good morning memes to share a good day wish with others, social media users express commitment to their social media audiences as a community that should be preserved by the daily exchange of courtesies.
Based on the above, I suggest that the evaluation of good morning memes may depend on whether the viewer sees them as voicing the core values characterizing rituals of relationship work (intimacy, care), thus producing the expected feeling of affiliation between users, while also respecting the principles governing memetic expression at large (authenticity, creativity, and loyalty). Memes adhering to these norms are likely to be evaluated favorably, while those that do not may be read as “in bad taste.” Such memes would arguably represent an example of kitsch: a veteran concept developed to describe those mass-produced artifacts that imitate the codes of high art but fail to pass as such because of their banal character and exaggerated sentimentalism (Eco, 1964; Greenberg, 1986). As detailed in the analysis below, having the meme literacy to recognize inauthentic and uncreative memes as kitsch can be a crucial criterion that sets apart different communities of social media users.
“Good Morning World!” The Articulation of Values in a Globalized Meme Template
The specific focus of this article is on the genre of “good morning memes.” The shared core of good morning memes features text with a good day wish imposed on a plain or natural background, paired with images featuring natural objects, coffee mugs, or people (see Figure 1). Good morning memes have not been the object of systematic investigation, even though commentary on subcultural platforms (themarktully, 2020) and mainstream social media (Babushka, 2020) has pointed out their transnational popularity. A simple Google search for “good morning memes” yields about 450 million results. As noticed by a Singapore-based Redditor (eatdabian, 2020), the “happy for you” category in the Google Play store features 70 different apps to produce, edit, or download good morning memes and adjacent genres.
Examples of good morning memes contextualized in the interface of WhatsApp (L) and Facebook (R).
Good morning memes have a historical precedent in greeting cards, mass-produced artifacts purchased as a gift or to accompany a gift. Commercialized in the late 19th century, greeting cards fill the niche between letters and postcards, allowing people to send quasi-personalized messages to each other without the effort of writing them (Stern, 1988). Despite tremendous commercial success, selling more than six billion units per year in the US market alone (Greeting Card Association, 2020), greeting cards are often an object of distaste because of their banality and exaggerated sentimentalism (West, 2010).
While greeting cards represent a significant historical precedent, good morning memes exist within the wider ecology of “inspirational” social media content. Social media inspiration encourages users to cultivate a sense of meaning and personal relevance (Dale et al., 2020), through a narrow set of key tropes like celebrating moral virtue, appreciating art and architecture, cherishing human connections, coping with pain and sorrow, and contemplating the beauty of nature (Rieger & Klimmt, 2019). As suggested by De Paola and Hakoköngäs (2020), different incarnations of social media inspiration are structured around two opposing views of happiness: one in which happiness can be built over time through hard work and one in which happiness is ever-elusive and should be sought in the present moment.
Created by Internet users in different countries and distributed in a wide number of languages, good morning memes represent a particularly fruitful entry point for the study of globalization in digital spheres. The use of memes as proxies for culture should be approached with caution, as the demographic characteristics of meme-producing “digital elites” may set them closer to each other than to their co-nationals (Jenkins et al., 2013). As suggested by Shifman, however, the expected similarity between content producers from different countries may be a blessing in disguise, insofar as the differences that may emerge in their content “can be plausibly regarded as indicators for cultural distinctiveness” (Shifman, 2016, p. 5645).
I suggest that good morning memes can be regarded as examples of “user-generated globalization” (Shifman et al., 2014). This is a process simultaneously characterized by tendencies toward the homogenization of content across national borders and contrasting tendencies toward its localization (Boxman-Shabtai & Shifman, 2016). Global meme templates surely favor continuity, privileging, for example, Western worldviews expressed in English and North American cultural references. However, the customization inherent to memes encourages users to re-elaborate global templates in light of localized vernaculars, producing unique glocal hybrids (Shifman et al., 2014).
Based on the above, I interrogate data gathered from two linguistic settings: English and Italian. English is recognized as the language of globalized Internet spheres (Danet & Herring, 2007), and its widespread adoption is a testament to (and one of the drivers of) the overlap between globalization and Americanization (Billig, 1995). Conversely, Italian speakers are a large yet space-bound language community mostly located in Italy and southern Switzerland.
Italy was selected as a “local” testing ground for the generalizability of the findings from the “global” English-language data. This approach is in line with established theories of cultural values, historically emphasizing Italy’s cultural alterity to other Western countries, especially the United States. Early research by American scholars sought to explain Italy’s alleged underdevelopment as the combined effect of negative local values such as familism and the absence of values believed to be the backbone of American global hegemony such as enterprise (Banfield, 1958; Putnam, 1993). In a related fashion, value theories from organizational studies (Hofstede, 2003), political science (Inglehart & Welzel, 2005), and social psychology (Schwartz, 2012) emphasize cultural diversity between the individualism of Western English-speaking countries and Italy’s collectivism, especially in areas such as religion and family relations; theories that are echoed by several Italy-based sociological studies (Buzzi et al., 2007; Cipriani, 1992).
My analysis is guided by three interrelated research questions. Striving to identify the defining visual features and the core values of good morning memes, I ask what are the main elements in the visual composition of good morning memes? and which values do they explicitly foreground? As outlined above, I approach these questions with an eye to cross-cultural similarities and differences between English and Italian memes. Furthermore, seeking to uncover cultural and generational differences in the evaluation of the memes, I also ask how do users from different countries and age groups evaluate good morning memes?
Methods
My investigation draws from two different approaches. A content analysis of a corpus of good morning memes addresses the first two research questions, while interviews with social media users located in the United States and Italy shed light on the third one.
Content Analysis
Good morning memes can be found on multiple social media platforms. Instagram was selected as a suitable site for data gathering because of its focus on visual material. Crucially, however, many of the memes in my sample had visual markers (aspect ratio, cropping, resolution) suggesting that they originated elsewhere on the Internet. As highlighted in the analysis below, while good morning memes can be found on Instagram, they are not native to the platform and their aesthetic is associated with other social media.
Using the python-based package Instaloader, I collected metadata from two popular hashtags with equivalent meanings in English and Italian: #goodmorningeveryone and #buongiornoatutti. Metadata was retrieved on 12 separate 3-day intervals, one for each month of the year. The searches cover all days of the week equally (Sunday-Friday: 5 occurrences per day) except for Saturdays (6 occurrences), as well as major religious holidays (Easter, Pesach, Eid al-Fitr, Rosh HaShanah, Christmas). The resulting, unfiltered corpus included 2,912 posts in English and 2,452 in Italian.
Thereafter, I cleaned the corpus in a three-stage process. In the first stage, I selected and manually screenshotted each of the still images featuring text on a plain background or a combination of text and another visual element (e.g., animals, flowers, coffee mugs). In the second stage, I excluded memes featuring commercial advertisements, memes featuring recognizable users, and memes that refer to a holiday without also including a good day wish. Given my focus on the explicit expression of values, the final cleaning stage excluded memes in which the textual component only stated “good/happy morning” with no further text. The resulting dataset included 240 memes in English and 174 memes in Italian.
After cleaning the dataset, I developed a codebook for the analysis of the visual and textual components of the memes. The codebook contains four questions about the protagonist of the visual composition, its background, the values expressed in the textual component, and the stance of the meme. The codes for the first two variables are based on established schemas for the analysis of images (Kress & Van Leeuwen, 1996) and preliminary screening of the corpus. The codes to identify values in the text of good morning memes are inductively derived based on Heinich’s (2020) aforementioned pragmatist approach to valuation. Through several rounds of close reading, I identified 11 categories of objects that the memes consistently identified as “worthy.” Specific definitions for each code and modified examples from the dataset are listed in Table 1. Given the complications associated with identifying values in humorous texts, coders were instructed to categorize memes that explicitly feature jokes as “Other.” Finally, I operationalized the category of stance from Shifman’s (2013) definition of memes to differentiate between “ironic/funny” memes and “serious” ones.
Value Coding Scheme With Definitions and Examples.
After a pilot phase, a research assistant and I performed a reliability test on a set of 50 units in English and Italian, passing Krippendorff’s alpha threshold for intercoder reliability in exploratory studies (α = .67) for all variables (main visual protagonist: α = .81; background: α = .77; values in the text: α = .80; stance: α = 1.00). Following the intercoder reliability test, the full dataset was coded. To identify statistically significant differences between the two subsets, I measured the independence of all four variables through Pearson’s chi-square test with the simulated p-value. Thereafter, I identified unique features of the two subsets using Fisher’s exact test corrected for multiple testing using the Benjamini-Hochberg false discovery rate procedure.
Interviews
The interviews for this article were conducted in November–December 2020 as part of a wider research project investigating the expression of values on social media. During the interviews, users from different countries were shown several genres of social media content, including good morning memes. Specifically, interviewees were presented with a collage of three typical examples of good morning memes and asked to (1) identify up to three values expressed in the content, (2) voice their opinion on the memes, and (3) disclose how they usually engage with the genre. Interview transcripts were then coded according to the following categories: explicit values named by the interviewees (open question), evaluation of the genre (positive, negative, mixed, indifferent), and engagement (share, share with modification, like/comment, not share).
My analysis draws on 20 interviews conducted by the author and one of their colleagues with social media users located in the United States (n = 9) and Italy (n = 11). US-based interviews are used as an admittedly imperfect proxy to draw insights into how a “global” community of English speakers engages with the Americanized good morning meme genre. To ensure anonymity, each interviewee has been assigned a pseudonym. Demographic information associated with each pseudonym is listed in Table 2. As the table illustrates, seven of the interviewees belong to Gen Z, six are Millennials, two are “Xillennials,” three are Gen X-ers, and two are Baby Boomers (see Dimock, 2019).
Demographic Information of the Interviewees.
In light of the limited sample size and the relatively skewed age distribution, the analysis of the interviews was qualitative. Despite its limited scope, interview data corroborated the findings of the content analysis regarding the values explicitly expressed in the memes and provided crucial information regarding the imaginaries that users associate with the genre.
Results
Visual Components: Protagonist and Background
The 414 memes sampled for this study were fairly consistent in their visual and verbal components. In a plurality of cases, the main subject of the visual representation was either an object of nature such as flowers (n = 81) or a “cute” character (an animal or a human baby; n = 73). Somewhat less frequently, the memes foregrounded food and drinks associated with breakfast time (coffee mugs, eggs, croissants; n = 44) or adult human figures (n = 39). In a large number of cases, however, the representation only foregrounded plain text (n = 93). Concerning the background, the memes were almost equally split between images with a solid or blurred background (n = 173) and images with a natural background (n = 164). Finally, a sizable minority of the memes were set against the background of domestic or urban space (n = 77).
Cross-cultural differences in the visual components of the memes were minimal. While the chi-square test of independence signaled significant differences between the two subsamples (χ2 = 29.065, p = .0005), Fisher’s exact test revealed that the only significant divergence between them was the relative prevalence of plain text in English (p = .007). These differences amount to a “cleaner” visual outlook for the memes in English and a somewhat more “cluttered” one for those in Italian due to the presence of multiple visual tropes alongside the text overlay. However, such differences should not be overstated: the English subset is by no means free from examples of visual clutter, and the Italian subset also features many text-on-plain-background memes.
Verbal Components: Values and Stance
For what concerns the verbal components, a plurality of posts in both languages foregrounded one of two values: courtesy (n = 97) or positivity (n = 81). The former refers to the presentation of a fairly empty wish addressed to a generic “you” or to a broad group of people (e.g., “good morning to all those who wake up early”). The latter refers to invitations to look on the bright side of things and adopt a happy-go-lucky approach to life. A smaller but sizable number of memes featured an orientation toward the values of self-efficacy (n = 49), inner peace (n = 32), and resilience (n = 28). Other values, such as romance, friendship, pleasure, religiosity, and gratefulness, were not as prevalent in the datasets.
The chi-square test revealed again statistically significant differences between the two subsets (χ2 = 36.445, p = .0005), attributed by Fisher’s exact test to the relative prevalence of self-efficacy in the English subset (p = .021). This is defined as an explicit reference to achieving tangible goals and individually affecting change through hard work and dedication. Another realm of difference between the two datasets was the relative prevalence of humor in the Italian subset. Even though good morning memes were overwhelmingly serious (n = 386), a statistically significant majority of the humorous memes in the corpus (n = 28) came from the Italian subset (χ2 = 11.987, p = .0015).
The interplay between these statistically significant results represents the main site of cross-cultural divergence between the two subsets. The textual component of the English-language subset frequently foregrounds self-efficacy through messages such as “Falling down is an accident, staying down is a choice. Good morning” and “Good morning. It’s going to be hard, but hard does not mean impossible.” Conversely, the ironic memes in Italian specifically push back against this orientation, as exemplified in messages such as “here, here . . . I’m getting up . . . Even though I don’t consent! Good morning” or “‘Monday’ directed by Alfred Hitchcock.” Thus, while both subsets emphasize positivity and courtesy, a more granular analysis revealed that they adopt divergent attitudes toward self-efficacy.
Interview Analysis: Explicit Values and Association With Platforms
Data gathered during the interviews confirmed that good morning memes are a popular and readily identifiable content type. All 20 interviewees expressed familiarity with the genre. When presented with examples of good morning memes and asked to name up to three values that they saw expressed in them, the 20 interviewees mentioned a total of 41 distinct values.
Interviewees of all ages in both countries recognized a number of positive values as being expressed by the memes. Interviewees from the United States were more likely to emphasize the uplifting, inspirational character of the genre, associating it with values such as fun, smiling, positivity, and optimism. For example, Anthony (Gen Z) listed the value of “inspiration,” explaining that the memes are actively “asking you to have a good day.” Similarly, Mary (Gen Z) commented that good morning memes are “trying to be motivational or inspiring. . . . maybe bringing a smile on someone’s face.” On a slightly different note, Richard (Gen X) listed supportive, entertaining, and funny as the values of good morning memes, and commented that the people who post them are “not taking themselves too seriously, taking a moment to share a good, silly photo.”
Italian interviewees focused on the communicative act of sharing good morning memes with one or more recipients, naming values connected to relationality (e.g., connection, closeness, family) and courtesy (e.g., politeness, friendliness, wishing others well). For example, Martina (Gen Z) listed “love” as one of the values, explaining, “it may be that we are thinking about that person when we send these images, and behind the thought towards this person, there is a kind of love.” Similarly, Luca (Gen X) commented that good morning memes are “a good way to start the day, in the sense of friendship and closeness to people, also thinking about others, not just about yourself.” Making specific reference to the presence of coffee mugs in one of the memes, Valeria (Gen X) mentioned “conviviality” as one of the values, and articulated that “when we eat, we do both: to nourish ourselves, but also to be together with others. So I put a photo with a cup of coffee and sweets to try to have breakfast with whoever sees this.”
The cultural differences in answers about explicit values may reflect the different platforms associated with the meme. American interviewees strongly associated good morning memes with Facebook. For example, John (Gen Z) defined the memes as “very Facebookesque” and offered a detailed explanation of the social media practices supporting their popularity. In John’s view, users frequently sharing good morning memes might have large lists of Facebook friends, but they only . . . recognize having a few friends that they . . . interact with on Facebook more visibly. And so, they’re sharing that photo to that small group, even though everyone else can . . . see it. So, it still feels personal.
Some Italian interviewees also associated good morning memes with Facebook. However, many of them also described the memes as a content type broadly circulated on WhatsApp. For example, Ludovica (Xillennial) reacted to the memes by saying: “I have my cell phone clogged with these here. . . . I ran away from WhatsApp groups because my cell phone is bursting.” Referencing a conversation with acquaintances that frequently share good morning memes, Ludovica further explained that It is a gesture of courtesy to send a happy, serene image to start a day. . . . as if to say “we do not see each other, but I send you a good morning in this way so that you know that I am close to you.”
The association of good morning memes with different platforms might be an effect of their relative popularity in the two countries: WhatsApp has overtaken Facebook as the second most popular platform after YouTube among Italians (Hootsuite, 2021a), while it remains relatively unpopular in the US market (Hootsuite, 2021b). However, while people might share good morning memes on different platforms and with slightly divergent practices, interviewees depicted the people who share them as motivated by a desire to preserve connections with geographically dispersed friends.
Interview Analysis: Evaluation and Generational (Dis)Taste
As outlined above, there was wide agreement over the positive character of the values expressed by good morning memes. Nonetheless, most interviewees did not like the genre. This is especially true for Gen Z-ers, none of whom expressed appreciation for good morning memes, and for Millennials, among whom only one respondent seemed to like the genre.
Even though Salvatore (Millennial) was the only interviewee to explicitly invoke “kitsch” when describing good morning memes, the distaste voiced by younger users often targeted their aesthetic qualities and, interestingly, was motivated by the memes’ association with older age cohorts and the platforms that are popular among them. For example, Layla (Gen Z) commented that the aesthetic of good morning memes “looks like what my grandmother posts, yes. . . . I see them a lot on Facebook, for sure.” The same opinion was voiced by Carlo (Gen Z), who commented that the memes were “very similar to the photos my grandmother sends me every morning,” and also added that “it must be a [WhatsApp] group of over 40, over 50 who send these photos.” These associations between generation and platform are somewhat unsurprising, given the popularity of Facebook with older cohorts of American users (Auxier & Anderson, 2021), and the pivotal role that WhatsApp plays in intergenerational family communication in Italy (Taipale & Farinosi, 2018).
Among the interviewees, Samantha (Gen Z) probably best captured the trend associating older users with an aesthetic perceived as poor, commenting that older folks may not be as tech literate or savvy . . . And the stuff in the picture, it’s straightforward. . . . Anyone can understand it and I think it’s easy to make. You don’t—you don’t need some advanced skills.
A similar view was expressed by Jia (Millennial), who commented, “the editing level we have reached now, as a whole, is completely different from the editing in these pictures.” Explicitly mentioning generation as a factor for disaffiliation, Jia concluded that good morning memes are not content that younger users “would find interesting. . . . That’s not something we would post anymore because we don’t care for it.”
Other interviewees were less sympathetic toward the genre, explicitly pointing out their banal character as a crucial factor in their negative evaluation. For example, Jillian (Millennial) commented that good morning memes are “kind of, like, the fridge magnet of the Internet,” and argued that they “seem too vague. Just . . . well-meaning and nothing.” Similarly, Claudio (Millennial) commented, “I see them as a trivial, obvious thing. Recycled. The same photo with different writing every day.” Overall, good morning memes appear to be digital artifacts that younger users dislike because of their kitsch aesthetic and impersonal character.
Evaluation by other age groups was more mixed, leaning positive or negative depending on personal experience. Richard (Gen X), for example, commented that he appreciates good morning memes because they get his day “off to a good start with a laugh or a smile.” A similar view was expressed by Rachel (Xillennial), who also believes that good morning memes have a positive impact on the receiver and commented that “you can actually change someone’s mood with one of these.” On a somewhat different note, Stefano (Baby Boomer) claimed to appreciate the memes for “having no hidden agenda” and being a genuine invitation to have a positive day.
Discussion
This study offers a first cross-cultural comparison of the core values and visual features of good morning memes, as well as an investigation of their evaluation by social media users from different language communities. For what concerns core values, good morning memes in English and Italian adhere to the tropes of social media inspiration, especially the theme of appreciation of life (Rieger & Klimmt, 2019) and the associated value of positivity. The memes also seem to respect the commitment to intimacy and care typical of rituals of relationship work (Trillò et al., 2022) expressed via the adjacent value of courtesy. Adherence to the broad framework of social media inspiration is also reflected at the visual level through natural motifs such as flowers, leaves, or “cute” animals cast against a natural or plain background.
Beyond these similarities, the findings also show small but meaningful cross-cultural differences regarding the value of self-efficacy. In line with the established theorization of individualism as a pivotal American value (Eppard et al., 2020) propagated globally through banal Americanism (Billig, 1995), memes in English were more likely to foreground self-efficacy. Memes in Italian invoked self-efficacy statistically less often and frequently made fun of morning hustle culture. Ultimately, the “global” English-language incarnation of the genre promotes an understanding of happiness as something that can be built through hard work (De Paola & Hakoköngäs, 2020), while the Italian-language “local” version adopts humor to voice its skepticism toward the notion that such project is indeed worthwhile. These differences are arguably representative of cross-cultural distinctions between users from different locales based on the core values expressed in the memes that they produce.
The evaluation of good morning memes proved to be a prime site to observe the pivotal role of communicative values in determining appreciation or distaste for a social media genre, in turn contributing to generational distinctions between users. While interviewees of all ages seemed to agree that authenticity is a crucial communicative value mandating how memes should speak about the world (Shifman, 2019), different age groups seemed to disagree on what counts as authentic. Younger interviewees in the United States and Italy were united in their negative assessment of good morning memes as inauthentic because of their uncreative use of forced tones and trivial subjects. By contrast, older interviewees appreciated good morning memes as artifacts that successfully produce the intended affiliation between users (Trillò et al., 2022) through authentic expressions of positivity and courtesy that become unwelcome only when overshared. Crucially, younger users invoked authenticity-as-creativity as a key norm to judge the genre as kitsch and mark their distinction from a generational “other” imagined as lacking the meme literacy to recognize that such memes are in bad taste.
Conclusion
Based on the above findings, I offer three interrelated overarching observations. The first observation pertains to the role of values in the meme-based struggle over classification in digital spheres. As pointed out by my analysis, distinctions between groups of social media users take place at the level of core values (what memes say about the world) as well as at the level of communicative values (how memes say it; Shifman, 2019). At the level of core values, my analysis uncovered a cross-cultural distinction based on the value of self-efficacy, explicitly endorsed by the “global” English version of good morning memes and humorously questioned in the “local” Italian version. At the level of communicative values, my analysis revealed that different understandings of the pivotal memetic values of authenticity (Shifman, 2019) are crucial to the evaluation of good morning memes and, in turn, to social distinction between generations of users. Depending on generational notions of what counts as authentic, good morning memes were judged as successful rituals of relationship work or as kitsch digital artifacts that do not deliver the intended feeling of affiliation (Trillò et al., 2022).
Second and connectedly, my findings highlight that younger users leverage the generation-specific notion of authenticity-as-creativity as a norm marking their distinction from an imagined cohort of older users who dwell in specific digital spaces and have bad taste in memes. I see this as an example of how classification struggles centering communicative values may be productive of collective imaginaries that connect audiences, content types, and platforms. While the popularity of markedly Gen Z memes like “OK, Boomer” (Zeng & Abidin, 2021) suggest that such classification struggles may also take place at the level of core values, communicative values are central to the association between older users, kitsch digital artifacts, and specific digital spaces (Facebook, WhatsApp family chats).
Finally, based on the pivotal role of aesthetic comments in the interviews, I contend that audience-content-platform associations like the one identified in this study are crucial to how individuals visually imagine and relate to different social media platforms. I interpret these associations as heuristic devices that may coalesce into recognizable platform aesthetics: collective notions of what specific platforms look like based on who we believe inhabits them and what content types we think they value. Far from reflecting the actual user-base or dominant content of any social media, platform aesthetics describes widely shared imaginaries regarding the overall visual outlook of a platform. For example, the vernacular term “Instagrammable” (Tiidenberg, 2020) defines the platform aesthetics emerging from shared assumptions regarding what visual tropes are successful on Instagram because appreciated by the “global digital youth class” imagined as its core demographic (Manovich, 2016). I propose “Facebookesque” as an adjacent term encapsulating shared assumptions regarding Facebook as a platform inhabited by older users who supposedly have poor taste and is therefore saturated with kitsch memes. Crucially, both terms describe broad aesthetic imaginaries reaching far beyond the platforms from which they borrow their names: Instagrammable selfies can be posted to SnapChat; Facebookesque memes can be shared via WhatsApp.
While this project is the first systematic attempt to analyze good morning memes as a subgenre of social media inspiration, it has some limitations. The most obvious is the Western focus of the analysis due to the selection of the case study. In an attempt to be true to the transnational character of the English subset of the data, I proposed an understanding of English as a transnational language that nevertheless embeds an Americanized set of values. Connectedly, US-based interviews were used as an imperfect proxy to draw insights into how a “global” community of English speakers engages with the Americanized meme template of good morning memes. While Italian data represents a theoretically justifiable “local” counterpart, it does so only within the context of the West. Hence, while my findings seem to apply both at the global and local levels, they might not hold when comparing Western and non-Western users.
Limitations notwithstanding, my study presents compelling evidence regarding the articulation of values in good morning memes, identifying a cross-cultural convergence in how “global” and “local” incarnations of the template foreground positivity and courtesy, as well as cross-cultural divergence in the prevalence of self-efficacy. Furthermore, my findings support an understanding of good morning memes as a genre that older users appreciate because, in their view, it successfully produces affiliation between users. Conversely, younger users express distaste for the genre based on the notion that such memes are uncreative and therefore inauthentic. I highlight how this distinction between generationally defined groups of users has important implications for how we visually imagine social media, arguing that content types popular among social groups imagined as the core user base of a platform may coalesce into visual paradigms that I called platform aesthetics. I hope that future studies will build on these insights, integrating them with Eastern and Southern perspectives, thus contributing to our shared understanding of taste-based social distinctions and their role in defining what we imagine platforms to look like.
Footnotes
Acknowledgements
I wish to express my gratitude to the anonymous reviewers for their insightful and collegial comments on this manuscript. I am also indebted to Limor Shifman, Blake Hallinan, and CJ Reynolds for their valuable feedback and assistance. Finally, I thank Anna Balestrieri for her meticulous coding of the images.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant Agreement No. 819004).
