Feeling old on Facebook: an autoethnographic analysis of ageism among younger people towards their peers

Population aging and the proliferation of numerous social networking sites such as Facebook (FB) have necessitated different approaches to investigating age-based discrimination called ageism. Although the current evidence provided information on younger adults’ attitudes towards older adults, little is known about the younger individuals’ attitudes towards their peers in a digital sphere. This autoethnographic study, conducted in November 2020, aimed at understanding younger FB user’s (n = 37) attitudes towards their peers, and the manifestation of plausible digital facets of ageism. I posted a public status using a specific FB feature called feeling old on my FB Wall and analyzed the comments (both emoticons and textual) by others in relation to the post/status. The study is guided by the theoretical lens of symbolic and interpretive anthropology. Results showed (a) younger FB users have age stereotyped negative attitudes towards their peers considering the FB status, and (b) emoticons used in comments expressed more negative attitudes towards old age compared to the textual comments. Both findings indicated potential connection to an internalized sense of ‘young’ and ‘old’ that embedded in socially grounded age stereotypes. Future and more research on digital platforms can be carried out targeting younger adults’ attitudes towards their own age group in order to understand the risk of emergence of ‘digital ageism’.


Introduction
The proliferation of social media applications posed challenges to scholars to investigate discrimination based on age, called ageism, from a different perspective (Ayalon and Tesch-Römer 2018;Nef et al. 2013;Rahman and Hyden 2020). The profound socioeconomic implications of these challenges have prompted concern about issues such as usage of social networking sites (SNS, known as social media). Although the numerous aspects of aging have been discussed within a wide range of societal institutions, the existence of ageism in the SNS is sparse (Levy et al. 2014). Moreover, the dimensions of ageism on digital platform have largely been neglected and very little is known about the analysis of attitudes within this constellation (Buolamwini and Gebru 2018;Neff and Nagy 2016).
For the last couple of decades, the means of communication have been altered from one-way communication of first-generation SNS to the interactive secondgeneration SNS communication (Nef et al. 2013). Some of the current popular means of communication is instant messaging (i.e., WhatsApp, Snapchat), SNS (i.e., Facebook), and microblogging (i.e., Twitter). Variations in the means have changed the pattern of communication. For example, users of the virtual platforms nowadays establish communication with others not only through verbal cues (i.e., text, words, phrase) but also add pervasive paralinguistic cues (i.e., emoticons, symbols, images) to represent facial expressions (Luangrath et al. 2017;Prada et al. 2018). Couple of studies based on digital platforms often identified younger adults as points of reference to the prevailing negative aging-related attitudes towards older adults (Garattini and Prendergast 2015;Ito 2013). These studies indeed give us substantial information about younger adults' attitudes towards older people on the one hand but leave the question of younger adults' attitudes towards other younger person or group on the other hand (Donizzetti 2019;Marques et al. 2020). The current study, therefore, attempts to explore younger adults' attitudes towards another younger individuals regarding 'old age.' Adopting an autoethnographic approach, two research questions posed in this study: (1) how do younger Facebook (FB) users express their reactions against specific status called 'feeling old'? (2) Are there any similarities in characteristics of the reactions in relation to aging stereotypes attitude towards 'old age'?

Study purpose
The goal of the present study is to investigate ageism (if at all) at younger people in relation to their peers. More specifically this study examined the attitudes (or responses) of younger FB users aged < 65 years, in relation to a FB status called 'feeling old' (with an assigned emoticon). To do so, I describe and discuss underlying motives of using different emoticons as paralinguistic and nonverbal cues in establishing virtual communication, and the purposes of including emoticons in textual messages. This study will perhaps contribute to comprehend the attitudes of younger adults towards individuals in similar age groups considering a virtual context that may not be captured yet in the lens of contemporary ageism research.
At this earlier stage of my writing, I would like to let the reader know that autoethnographic approach is relatively uncommon but can be a creative approach to study ageism. Most previous research on ageism adopted different quantitative tools such as cross-sectional surveys (Ha and Kim 2021;Rababa et al. 2020), longitudinal cohort study (Jackson et al. 2019;Tully-Wilson et al. 2021), content analysis (Naughton et al. 2021), or used qualitative tools includes interviews (Berde and Mágó 2022;Previtali et al. 2022), focus group discussion (Gallo 2019;Mayo et al. 2022) among others. Using an autoethnographic approach, this study provided a sense of probable manifestation of ageism on a digital platform. Importantly, the social-psychological components (e.g., cognitive, affective) of the study participants got more attention than discriminatory acts towards old age on a digital platform (Allan et al. 2014). The remainder of this study is organized as follows: a brief review of the relevant literature, then description of key concepts, theoretical standpoint, and the adoption of this particular methodology for the study. Finally, I present a discussion, study limitations, implications of findings, and draw a conclusion based on study findings.

Previous relevant studies
I conducted a primary literature search intending to review the usage of emoticons and textual messages on digital platforms (specially on FB); and what purposes they serve in aging studies. The review results, in general, indicated that the multifaceted use of different features on FB might have an influence on manifestation of ageism in virtual contexts (McHugh 2003). On the other hand, I found potential limitations in existing literature to identify how age-based stereotypes has been evolved on the digital world.
While a wide range of previous studies investigated various aspects of emoticons, few have examined the dimensions of age stereotypes on FB. A recent study, for example, concluded that an estimated 90% of FB users include at least one emoticon in public status or comments where age and gender were strong predictors (Oleszkiewicz et al. 2017). Emoticons are meant to assist users to avoid long text messages more commonly used in socio-emotional contexts than in task-oriented contexts (Derks et al. 2007). However, the meanings or interpretations are not always straightforward. For instance, emoticons are often conveying the emotional states of the sender which can be interpreted as an illustration of irony and sarcasm (Aldunate and González-Ibáñez 2017;Gülşen 2016;Vanin-aline et al. 2013). Subsequently, these nonverbal communications can result in misunderstanding and confusion that may advertently influence individuals' perceptions, knowledge, and thought process surrounding certain phenomena. The acquisition of new knowledge concerning emoticons or textual message more often impacts on changing attitudes (Alford et al. 2001).
Especially relevant for the current study, Levy and colleagues found an overwhelming proportion of FB groups have negative age stereotypes that focused on older adults (Levy et al. 2014). Several studies claimed that younger adults tend to hold negative age stereotypes which might have a strong influence while using FB (Levy et al. 2014;North and Fiske 2012). One study also demonstrated how the unintended social consequences of algorithms impact on generating a digital strand of ageist attitudes, stereotypes, and discrimination towards old age (O'neil 2019; Rahman and Hyden 2020). The study findings signal the emergence of distinct forms of age stereotypes on digital platforms.
Further, recent scientific inquiries added information on younger people's knowledge about aging (Donizzetti 2019), perceptions of old age, and attitude towards older adults (Burnes et al. 2019). From a more holistic approach, studies found different types of discrimination based on gender, race, and religion in the virtual world (Buolamwini and Gebru 2018;Neff and Nagy 2016). The literature search is evidenced by the fact that aging-related aspects have been assessed and measured predominantly through younger adults' attitudes. I argue that, especially in the context of digital platforms, the contemporary research methods in aging studies face limitations while considering the ageist attitudes among diverse groups of users.
In sum, the primary goal of existing studies often concerns over ageist attitudes of younger adults towards older people by failing to take into account the diversity of the intra-group perceptions of younger individuals. One reason for this specific thought may be that the researchers took this for granted that ageism is unidirectional to older adults by the younger people. Thus, ageist stereotypes have rarely been noticed in the discussion of emoticons and textual messages in relation to younger-to-younger adults. I further argue that an empirically grounded approach is needed to unfold if and how negative age stereotype in virtual contexts is a matter for younger adults. Overall, the slow but steady and probably silent manifestation of ageism in a corporate SNS platform has poorly been addressed to assess younger people's attitudes towards other younger groups.

Ageism
By definition, ageism is a specific form of discrimination in which older and younger adults are judged depending on their age. It directs a pattern of attitude and stereotype that can be positive, negative, implicit, or explicit (Ayalon and Tesch-Römer 2018). Ageism is often embedded both into the internal realities of individual experience and the external construction of the communal practice. As Levy (2003) points out the internalizing of aging stereotypes or prejudice may adopt from family or cultural environment the individual lives in. It begins in as early as childhood, reinforces in adulthood, and can be operated below awareness (Levy 2003). Differences in ageist approach are described as a devaluation of older adults (Bytheway 1994); 'trauma' threatening older adults (Gullette 2017); overreactions towards older adults (Neocleous et al. 2018; Rahman and Jahan 2020); a lodestone for thinking about older adults (Higgs and Gilleard 2020). In media studies, different contents related to 'being old' have commonly been described as a constructed justification of inequalities based on age. The senders' views and opinions got more attention rather than communicative perspective. From methodological aspects, many of media studies have been highly criticized due to the adoption of content analysis and suffers from theoretical discussion (Seiter 1986). To address these issues, ageism researchers developed a concept of 'visual ageism' (Loos and Ivan 2018). It refers to the social practice of visually underrepresenting older people in a prejudiced way (p. 164). As we can observe, ageism researchers have clearly put less importance on delving the perspectives of young adults even though the phenomenon refers to all forms of age-based discrimination of any age (Bodner et al. 2012).

Facebook
Like other prominent SNS, Facebook (FB) serves as a platform for the rapid dissemination of information by sharing pictures, building social interaction, expressing opinions, and even sharing personal well-being (Settanni and Marengo 2015); and is generally considered the leading and prevalent site among young generations (Hew and Cheung 2012;Networ 2020). Users can present themselves and share 'anything and everything' via their public or semi-public profile. Each user has a virtual Wall-act like a noticeboard-through which they can interact or communicate asynchronously with other users' by commenting on the post (Hew and Cheung 2012;PewResearchCenter 2020). In this study I used 'activity/ feeling' feature of FB where the FB user can choose symbols from a myriad of emoticons list to express their mood and opinion.

Emoticon
In SNS, symbolic representations are commonly referred to as emoticons (Walther and D'addario 2001). A combination of two terms-'emotion' and 'icon'-emoticon resembles of a sentence or text (Prada et al. 2018). Emoticons are the pictorial face-like icons or small graphic pictures that demonstrate facial expressions in computer-mediated communications (Huang et al. 2020). It depicts a person's emotions increase social presence, aids personal expressions, assists close social distance as well as leverages intimacy, and can interpret an ambiguous message in a meaningful way (Kaye et al. 2016;Smith et al. 2016). Even though the classical emoticons represented solely by punctuations (i.e., :-)), the use of text editor application has currently changed the punctuations into images (Smith et al. 2016). Research reveals that emoticons carry the emotional state of the human mind which may not be inferred from the words alone (Kaye et al. 2016). However, in some cases, they may create a negative effect on competence perceptions (Glikson et al. 2018).

Attitudes
Attitude is a state of mind, a personal viewpoint, and response towards other people, places, or events that can be formed by an individual's past and present experiences. Attitudes are evaluative statements that can be positive (i.e., confidence, optimism, cheerfulness/happiness, sincerity, sense of responsibility, flexibility, determination, reliability, tolerance, willingness to adapt, humility, diligence), negative (i.e., anger, hatred, pessimism, frustration, doubt, resentment, jealousy, inferiority), and/or neutral (i.e., complacence, indifference, detachment, feeling of being disconnected, unemotional) depending on how a person expresses the degree of like or dislike (Hormes 2016). Several precious studies have identified attitudes as a crucial predictor to understand the presence or absence of ageism (Gallo 2019;Rababa et al. 2020).

Theoretical frame
In this study, I adhere to the theoretical lens of symbolic and interpretive anthropological theory to discuss how emoticon as symbol influences or shapes mainly the pattern of individuals' attitudes. It probably, therefore, forms a shared system of meaning among members of the same group in a given context. According to the theoretical framework, interpretation of symbols reflects the insider's perceptions of the epistemological groundings of other contexts (Geertz 1973). It further allows researchers to interpret cultural aspects by understanding how individuals within a culture are expressing themselves and sharing their experiences. Here, I consider younger FB user as a digital cultural group and the emoticons and textual messages as a symbolic representation of that digital culture. Even though the theoretical view mostly derived from the analysis of socio-cultural symbols, it can also be applicable to digital contexts (Boyer 2010).

Study design
The study holds a framework of analytic autoethnography as a methodological stance (Anderson 2006). An analytic autoethnography refers to a data interpretation procedure where the researcher's understanding emerges as a member of the study setting. It involves the self-conscious and reflexive position of the researcher through active visibility in the texts called 'dual participant-observer role' (Anderson 2006;sm-Rahman and Jahan 2020). In other words, the researcher plays the role of 'insider' and 'outsider.' Nonetheless, the method provides a unique opportunity to the researcher(s) to turn the lens of inquiry into their own personal accounts of the phenomena.
I choose this method for three reasons: it is qualitative, self-focused, and context-conscious (Chang 2008;Ellis 2000). Further, the method is a window to understanding the socio-cultural aspects of self: as a 'subject' (the researcher who performs the investigation) and as an 'object' (a/the participant who is investigated). This autoethnography focuses on the exploration of the connectivity of 'self' within a digital context. That is, I relate '(my)self' with digital social aspects as well as with surrounding contexts. Therefore, the reflexive interpretations carried out my insider-outsider view while writing the narrative. The use of 'I/my' and content of this article is a testimony to the reader how autoethnography assists the development of my identity and voice throughout the text.

Data source and study procedure
Data I used in this study are derived from my personal FB account by using a specific FB feature called 'feeling old.' To activate the feature, I had to follow three steps: first, choose 'what's on your mind?,' second, select 'feeling or activity' and finally pick the 'feeling' emoticon designated for 'old.' Although there is an option to add text messages with the status, I used only emoticon in order to cover the research objectives. The status was available on my FB Wall as soon as I post it. The visibility of the post to others depends on how I ascribe limits such as 'only me,' 'friends only,' 'public.' I choose 'public' mode so that all my friends and their friends can comment on the status without any filtering. I had 250 accepted FB friends under my profile during the study period. The status was retained for four weeks on my Wall in November 2020. Twenty-nine participants from my FB friend list and twelve from 'friends and connections' made comments, emoticon and text, on the status. After careful assessment of the comments considering study objectives (i.e., age limit, relevant comments), a total of n = 37 participants' comments (one from each) were included for further analysis. According to the World Health Organization, old age starts after 65 years (WHO 2021), therefore, I considered the age range between 18 and 65 years as younger age. Duplicate emoticons and texts with long quotes (more than 25 words) were removed.

Data analysis
The data were analyzed in two parts. First, I investigated each emoticon in relation to their varieties in meanings. Second, textual messages (comments) were analyzed in terms of positive, negative, and neutral valence coupling with the associated factors of attitude: cognitive, affective, and conative (Ajzen 2005;Walther and D'addario 2001).

Writing of my narratives
The development of my autoethnographic narrative has gone through an iterative self-reflective process: backward, forwards, and sideways concurrent movement which was followed by recommended writing steps of analytic autoethnography (Anderson 2006). Thus, the narrative I have presented in this article is a pronouncement of self-reflexivity regarding the responses of FB status.
In my opinion, reflexivity is the researcher's self-conscious reflection on a study setting. It involves an awareness of reciprocal influence between researcher and study participants. I put the importance of bridging between me and the collected data to maintain quality and trustworthiness of the analysis. This is a process of developing valid interpretations of pertinence to symbolic and linguistic units: emoticons, texts, or phrases (Zhang and Wildemuth 2009). Furthermore, textual visibility and construction of meaning in the narrative enabled me to demonstrate personal engagement in the digital research setting. However, this type of explicit visibility can also be challenged and lead to self-absorption in what Geertz has referred to as 'author saturated texts' (Geertz 1973).

Respondents' profiles
The gender representation of the participants was female 46% and male 54% (see Table 1). The majority were aged between 25 and 40 years (65%). Participants have different levels of education where most of them completed masters (60%) and bachelor (19%) degree. The current living country of the participants was Australia, Bangladesh, India, Italy, and USA.

Responses to the FB status
I was the main subject of the current study. The status has received numerous responses. Of those, I have selected relevant comments that convey different expressions of aging. The results comprised two dimensions of comments which covered a broad range of emoticon representations and aging-related textual messages.

Emoticon analysis
There was a common observation that major proportion of the emoticons carried more negative valence compared to the other two valences (see Table 2). The negative attitude was firmly expressed in pictorial expressions of the emoticons where the meanings represented participants' negative stereotypes and attitudes towards old age. It provoked strong impacts that might be greater than that of verbal messages or face-to-face communication alone can do. Moreover, the emoticons somewhat indicated old age-related stigma expressed as 'lonely,' 'exhausted,' 'crazy.' This perceived perception reflects an internalized sense of fear of being discriminated against due to inferiority and unacceptability eventually refer to negative age stereotypes. Some of the emoticons were expressions of compassion or affective such as 'stressed,' 'anxious,' 'worried,' 'depressed.' The compassionate tones showed sympathetic consciousness of and concern for the sufferings of others. Moreover, this perception may be connected to a denial or ignorance of stressful event which is beyond their control. The participants were sometimes even sarcastic to excoriate old age comprised of ironic emoticons namely 'thoughtful,' 'proud,' 'cool,' 'special.' From the narrative perspective of aging, irony can play a subtle but crucial role in constructing the honored capacity of a person called wisdom.

Comments analysis
The textual comments I received were mainly a combination of age-related quotes and personal opinions of the participants (see Table 3). Qualitative differences were noted in this case. The key messages of quotes carried the voice of positive tones with humor. Even though the quotes were associated with aging and possible consequences of later life, the linguistic properties (the pattern of communication) were unclear to distinguish the quote as wise or unwise. The textual comments comprised of phrases like 'mentor,' 'limitation,' 'hill,' and 'less attractive' emphasize the fleeting trajectories of life. Further, some of the quotes suggested the cultivation of ironic approaches to understanding aging where emotive language played an important role. Similarly, the comments came from personal opinion implied positive attitudes which were mostly described cognitive levels of the participants. They might think the intensity of the text should be moderated by how close you are with the person. From the message receiver's point of view, for instance, these opinions seemed to give an impression of inspiration. Opinions further contained motivational message as well as were supportive to the message receiver in order to strengthen psychic level. The inner meaning of these opinions may reinforce message receiver to learn how to ignore the feeling of being old. Contrasting with quotes, the personal opinions used the same phrase 'less attractive' with a more positive accentuation.

Discussion
This study explored how a younger FB user demonstrates her/his attitudes towards other younger persons by means of emoticons and textual messages. I think the findings of this study make several contributions to provide insights into probable digital facets of ageism that carry and may constitute the socio-cultural meaning of emoticons. The overall results indicate two principal findings: (a) younger FB users have age stereotyped negative attitude towards other younger persons and (b) emoticons were more likely to express negative attitudes than the textual comments. These issues are discussed below.
First, the study participants conceived, knowingly or not, aging as a disadvantage by debilitation of physical ability and appearance. This perception possibly rooted in different social aspects such as 'fear of getting old,' 'being seen as old,' 'being treated as old' (Minichiello et al. 2000). A central tendency of own visibility was also observed among the study participants. It is a state of 'texistence': a complex, quasi-literary, narrative construction that continually 'composing' in memory and imagination from the experiences of our lives (Randall and McKim 2008). The texistence can be imposed on us against our will by personal opinions, perceptions, or policies. Some participants, for example, were sympathetic and compassionate that indicated the encouraging capacity to see something hopeful and humorous. Other participants showed a greater sense of sarcasm by affording old age as a gradual detachment from our life. This two-fold illustration emphasized younger adults' preoccupation with the concept of 'growing old' (i.e., still learning and contributing) and 'getting old' (i.e., inability to contribute).
In brief, the participants represented independent ways of expressing negative stereotypes and attitudes towards me as a younger person that corroborate the arguments of Hsiao and Hsieh (Hsiao and Hsieh 2014). They found, the preexisting ideology about old age and negative age stereotypes may have influenced the content of comments in the FB context (Hsiao and Hsieh 2014). The negative construction of 'old age' was identified as an 'automatic' cognitive component (Perdue and Gurtman 1990) which has lately been described as an outcome of internalized aging stereotypes that facilitated through a variety of cognitive processes (Levy 2003). Further, aging stereotypes predominantly connected to implicit and explicit beliefs. That means, it is highly likely that the expression of positive attitude tends to be operated by implicit negative beliefs (de Paula Couto and Wentura 2017;Levy 2003). Attitudinal dimensions were found connected to the ideology of young and old age. More specifically, the expressed attitudes were developed from socially grounded age stereotypes that are internalized and carried over to FB (Levy and Macdonald 2016).
Second, if we look back at the study findings, the use of emoticons can be related to external affective cues, moods, and feelings of the participants that elicit both positive and negative information. In my study, the responses against the FB status to some degrees are driven by the general motivation to promote positive interactions and interpretation of specific intents (Prada et al. 2018). This finding is in line with the previous studies which suggested that the emoticons are useful in strengthening the intensity of a message, improve receivers' understanding, and reduce ambiguity (Derks et al. 2008;Thompson and Filik 2016). However, other studies also argued that using only emoticons to express emotions could be a double-edged sword (Huang et al. 2020;Prada et al. 2018). This argument is consistent with my findings that is the likelihood of using singly emoticons obscured its meaning compared to textual comments. The finding further indicates that emoticons embedded textual messages might be more meaningful which correspond to the study of Huang et al. (2020). From this point of view, my study findings were more likely to be associated with the usage patterns of emoticons and texts, and the users' characteristics (i.e., age, gender).
Overall, my study findings revealed the prejudicial effects of aging stereotypes on SNS which reflects to the notion of 'visual ageism' (Loos and Ivan 2018). This might be a digital form of interactive ageism. Further, in line with a wide range of SNS studies, my study identified negative age stereotypes among FB users towards 'feeling old' (Levy et al. 2022;Rosales and Fernández-Ardèvol 2020). The negative attitudes often represent a step or stage in the process where an individual already start accepting the self as 'old.' A possible alternative to minimize the negative attitudes towards old age is to increase the visibility of older people in society as well as in the media where the 'design for diversity' approach could be effective (Loos and Ivan 2018).
As an autoethnographic narrative, this article coupled me (as a researcher) and my text (narratives) together with a self-reflexive analysis. By virtue of being a selfconscious creature, we always keep the gap in mind between 'I' and 'Me,' 'Self' and 'Other,' and 'Present' and 'Past.' The feeling about a phenomenon like old age and older adults is mediated by some of those perceptions. I found the likelihood of similar perceptions in this study that signals an approach of stereotypical ageist attitude. It is also important to note that each emoticon may generate distinct semantic meaning depending on the setting in which they operate and mediate, as well as the relationship between the message sender and the message receiver.
The emoticons are expressed online might not carry the same meaning to the message receiver as there is a possibility of defusing the emotion by the time of comments. Further, an interpretation problem could cause poor emotional support. The nonverbal textual or symbolic expressions, for instance, may have linkage to 'microaggression' that conceptually describes as cumulative 'miniassult,' and a subtle derogative behavior towards the target person or group (Sue 2010). On the social front, I would suggest how societal-based age stereotypes are manifested and practiced in a digital sphere is temporal to discuss in relation to ageism (Gendron et al. 2016).
This study sheds light on the FB's, like any other SNS, strategies that encourage brief messaging to the users that often creates ambiguous meanings and lead to a complicated passage to determine the exact nature of stereotypes. Consequently, the patterns of ageist approach may additionally be facilitated by the opportunity to form an in-group culture, which may lead to the 'depersonalization' and 'dehumanization' of the outgroup (Tajfel 1982). It may further develop a particular discourse surrounding older adults that determine how they are treated in society. Equally important, the sender and the receiver of the messages may not have perceived the attitude as a negative age stereotype if it had become a norm or a pervasive practice within the FB context.

Study limitations
The study has several limitations that need careful attention while interpreting or generalizing the results. First, due to the small sample size, it is not certain that the results of attitudinal dimensions of the younger FB user are generalizable to all younger adults. Second, the absence of age and gender-based analysis impedes the understanding of differences in emoticons. Third, I did not analyze the geographic location of the participants which may vary across cultures and influences on determining emoticon. Finally, since the FB profiles were not verified, it was not possible to know the real age of the participants. So that, I had to consider the age mentioned in the profile. However, the study can answer some of the relevant attitudinal questions such as how we evaluate various types of emoticons, and how we represent ourselves through the text in digital worlds.

Conclusions and implications
The main aim of this article is to evaluate younger FB user's attitudinal reactions against feeling old status and to examine the likeliness of the reactions in relation to old age. Results of this study highlight two main aspects that the young FB users commonly express negative age stereotypes towards their peers and the use of different emoticons demonstrates more negative valence than textual comments. The findings further represent an accumulation of younger FB users attitude, exhibit the internalization of aging stereotypes, and provided new directions on the emergence of digital facets of ageism. This study indicates that the autoethnography as a methodological tool could be effective in understanding how younger FB users' practice ageist attitudes within a digital stand.
Finally, I argue that digital facets of ageism exist in the SNS platform would qualify as digital ageism requires further attention. To conceptualize, the term digital ageism implies an individual's (younger/older) implicit/explicit ageist stereotypes and attitudes towards a similar age group (younger/older) that can be practiced through the means of computer-mediated communications where the expressions can be positive, negative, humorous, sarcastic, or mixed. Future research could be illuminated by examining the individual characteristics of the SNS user to understand possible generational differences. It will, additionally, improve our knowledge about the attitudinal expression of younger adults in a more comprehensive and heterogeneous way. article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.