Keywords

Introduction

When we talk about traces in digital environments, we mean all the information that we leave online which profiles our activities, tastes, and preferences. These can be conveyed directly or indirectly and can refer to actions that we decide to perform online or even the responses to such actions.

The most classic example of traces that we experience when we access any web page concerns the accepting of cookies—strings of text that are used to report and store server-side the information we are going to produce on that website. The cookies keep track of the information we enter online. Two more classic examples of traces are our browsing history, which records our navigation paths, and web mapping services like Google Maps. Even activities, such as uploading a new profile photo, sharing a funny piece of content, or a conversation with a friend, are pieces of information that say something about us, which become traces that we leave behind in the social media digital environment.

This work aims to question the traces we leave on social media platforms, either intentionally or unintentionally, and, especially, those we do not want to leave. These traces describe us, providing clues about us that are accessible to third parties, precisely because of the “public” dimension of these platforms: they portray us and, in turn, influence the idea that we have of ourselves. For this reason, this chapter focuses on the traces that we voluntarily leave behind on social media platforms, dictated by the selection of what we want to show and what we want to hide and how these affect our perception of ourselves.

Firstly, this research topic will be addressed by framing the concept of social media platforms and investigating via what processes the activities we perform in these digital environments are translated into data—which are then collected and organized.

Consequently, the focus will shift to how the data that we enter into these platforms profile us, thus offering a description of ourselves that is the result of a dynamic relationship between the user and the platform. This process influences the perception we have of ourselves, of our image mediated by the platform, and induces us to manage those pieces of information.

Thereafter, these theoretical premises will be discussed and compared with the empirical data which emerged from 20 qualitative interviews conducted with 20 young journalists who are accustomed to mediating their public image online. The interviews were conducted for the research of my doctoral dissertation, from which part of this chapter is taken (Casagrande, 2021).

The findings suggest that both the intentional and the unintentional traces we leave online contribute to the profiling of our public image. They tell something about ourselves, and by managing these traces, we also manage the image we want to portray. Moreover, the decision of what to share and make visible, and what to keep private, is the consequence of a personal interpretation of the algorithm, as a result of the dynamic between data, users, and platforms. Therefore, not only the data we input but also those we receive as outputs shape not only our public image but also the perception we have of ourselves.

Social Media Platforms: How Do They Collect and Organize Our Data?

Social Media Platforms and Online Traces

The analysis proposed in this chapter starts from the digital environments of social media platforms, in which we leave traces of ourselves, directly or indirectly, voluntarily or involuntarily. Primarily, it is useful to clarify what a “digital platform” is.

For van Dijck, Poell, and de Waal, “an online ‘platform’ is a programmable digital architecture designed to organize interactions between users—not only end users but also corporate entities and public bodies. It is geared towards the systematic collection, algorithmic processing, circulation, and monetization of user data” (van Dijck et al., 2018 p. 4). Thus, the main characteristic of digital platforms is “to host and organize user content for public circulation, without having produced or commissioned it” (Gillespie, 2017 p. 1). Furthermore, the techno-commercial nature of social media brings out the communicative trend of the personalization of contents (Poell & van Dijck, 2015). This is determined by the platforms’ algorithms which, by including or excluding certain signals, decide what can be “considered ‘relevant’ or ‘trending’” (Ibid. p. 530). Indeed, through the specific affordances, social media enables users to make their connections as “personal” as possible, i.e., they encourage the tendency toward personalization.

From this perspective, the symbolic significance of the platforms’ design choices and affordances is well explained by Facebook’s “Like” button. Initially enabled only for content sharing, the “Like” button changed its function and meaning in 2011, when it was transformed into a content approval and rating index. Gerltiz and Helmond argue that the “Like” button enables data flows, turning user engagement into numbers. This has further consequences such as enabling device tracking and creating an infrastructure in which social interaction, as well as users’ emotions and affections, is immediately transformed into data (Gerlitz & Helmond, 2013). These social buttons are present in many platforms and serve to recommend posts and pages. At the basis of the principle of recommendation or ranking, there is the possibility of creating a comparison: the recommendation or ranking vote is, in fact, visible both to the user affected by the evaluation and to the others, in order to establish some comparisons.

In short, the design choices as well as the algorithms underlying social media platforms modulate our social interactions, simultaneously transforming the information, or traces, we leave behind whenever we access or use these platforms into codified data.

Datafication, Big Social Data, and Self-Tracking

The process by which any object or phenomenon can be translated into data is described as datafication (Mayer-Schönberger & Cukier, 2013). Indeed, this process is about making any phenomenon or object quantifiable, so that it can be measured through shared parameters, cataloged, analyzed, and predicted.

Potentially everything can be translated into data; even intangible aspects such as emotions, experiences, and relationships can undergo this process. In social media platforms, every comment, word, recorded image, and emotion is part of an information flow that starts from the users, as an expression of sociality, and is converted into data.

Mark Coté (2014) identifies as Big Social Data all the information which comes from the mediated practices of our daily lives. To access any social media platform, we must generate social data, for instance, when we create our profile, and this is a structurally unavoidable requirement. Big Social Data, then, are generated as symbolic, affective, or informational contents and are the “result of spontaneous, contingent and free-form communicative sociality” (Ibid. p. 129). They materialize our daily symbolic practices, deployed in sociality and relationality.

This process, according to Cheney-Lippold (2017), also impacts our identity, since the data used to categorize users do not directly describe the users themselves, but rather standardized subjects according to the rules of the platforms. It is precisely from the act of sorting, categorizing, and evaluating that a user moves from being a person to being a “profile.”

As academic Frank Pasquale pointed out, we live in the black box society (Pasquale, 2015), in which anyone can be labeled based on the information entered and then collected by, usually, companies or special analytics firms. Then, these companies can, for example, assign a score to each profile and decide how to rate a user. Therefore, a person may be marked as “unreliable” or “dangerous” in the database, without even being aware of it. However, the meaning of such labels, as “unreliable” or “dangerous,” is not agreed upon, but attributed by the author of the algorithm.

Given this logic, characteristics related to our identity also undergo the same process. Aspects such as gender or age, for example, will not be consequent to the actual representation of the self, but to consumer choices: a subject will be identified as a woman or a man, young or old if the information entered identifies them as such. Consequently, our online identities are the result of a constant reshaping between the information we enter into the system and how it is interpreted by algorithms in an ever dynamic composition of our digital selves (Cheney-Lippold, 2017).

To better explain the circular dynamic involving data, users, and platforms, Deborah Lupton (2016) analyzes self-tracking practices and the digital devices that enable them such as apps that monitor weight control or evaluate a sports performance. Lupton states that through these apps, people who practice self-tracking can monitor themselves and, as a result, know themselves through data. Indeed, the information collected creates patterns and associations that can be identified and understood by the users. They recognize their own behaviors and can make changes in their lifestyles, for example, by deciding which food to buy for their diet or which route to take on their morning run. Consequently, self-knowledge and self-management pass through self-monitoring, mediated by the digital technologies.

In the process of intersection and interrelationship between data and users, people can get involved and respond emotionally to the outputs generated through self-tracking technologies. Such emotional responses are triggered especially when relationality is involved, and this is particularly true in the case of social media platforms, where it is impossible for users not to make a comparison between their own performances and those of others.

The practice of self-tracking (Lupton, 2016) causes users to be personally responsible for their own self-management and, consequently, also for all the invisible ensuing repercussions. For example, when the app compares daily miles traveled with those of another user, someone may respond to this information by deciding they want to “perform” better.

In social media platforms, among the various objects and phenomenon that can be datafied, there are also traces that are not immediately tangible such as our emotions and feelings and symbolic elements that animate our daily social and relational practices. We have just seen how this dynamic produces outputs that can easily manifest themselves even outside the online dimension and that, in turn, induces an activity or reaction in users.

Digital Selves and Digital Data: How Do We Manage Our Visible and Invisible Traces?

There is therefore a significant correlation between the data we enter online and the perception of our own identity, here understood as the result of the interpenetration between online and offline (Floridi, 2015).

For Goffman, “the self emerges from a social situation” (Goffman, 2009 p. XVI) and serves as an “indispensable code for conferring meaning on all social activities and for providing a basis for organizing them” (Ibid. p. XVIII). Individuals convey their identities both voluntarily, often verbally, and indirectly, via involuntary behaviors.

In this sense, social media platforms represent the ideal stage for self-presentation, for the interaction of public and private life, and for the negotiation of individual and collective identities (Papacharissi, 2011). This is partly due to the specific functions of the platforms, which allow users to manage aspects of their identity, at times strategically. In fact, through their architecture and design, these environments enable the creation of profiles, networks of contacts, and expressive and communicative capabilities. The affordances of social media platforms allow the representation of multiple online identities, in relation to different situational contexts, creating a new, mediated, perception of the self.

Identity and Visible Traces, Direct and Indirect

Nancy K. Baym (2010) emphasizes the presence of multiple representations of self in online environments, each of them authentic and genuine yet distinct. Both online and offline, these identities are often the result of a negotiation of what a person wants or can show, wants or can hide, wants or can communicate.

She argues that online we have several functions and tools at our disposal to trace our personal and social identity. Falling into the first case are the most well-known operations, which we could describe as voluntary actions, such as the identification through one’s name or nickname; images, photos and video, or also avatar customization; the technical skills needed to costume and manage personal sites, or blogs; as well as more sophisticated functions on social network sites, which also provide information about our capabilities; finally, many social media platforms require—sometimes compulsorily—the compilation of certain categories of data, from biographical or demographic ones to more generic categories such as those related to cultural identification, like musical preferences or favorite books and TV shows.

All this information can be described as traces that, regardless of privacy settings, we can define as equally visible to the user, to their contacts, and “to the platform,” as data that will be recorded. These pieces of information are obtained directly, often through compilation operations.

Moreover, Baym explains that the quantity and type of our contacts also provide insights of users’ identities and, when connections are made visible and traceable, become very useful in determining social reputation. Also, social status and political affiliations can be easily guessed by third parties through our social connections (Ibid. p. 112), even if this is sensitive information that people may not necessarily want to circulate.

Other sensitive data related to users’ identities may be, for example, those related to gender, social class, and nationality. In addition, information can transpire from our language. Do we communicate in a formal or colloquial manner? Do we use foreign languages or dialects? Do we use interjections or quotations? Does our language indicate our age cohort or nationality? Again, preferences or dislikes could be indicators of users’ class, socioeconomic level, and education.

In all these cases, the traces we leave of ourselves on the various platforms are visible because, for example, if we comment on a piece of content, we are revealing a language style that characterizes us. At the same time, these traces are also indirect, since they are not information explicitly requested by the platform. All the data we enter into social media provide traces, direct or indirect, which shape the various representations of ourselves.

For van Dijck (2013), users have learned to manage this information strategically, for example, by showing different sides of themselves in different platforms—in other words, staging different identities. Thus, a person can show a more playful and flirty side on Instagram while conveying an exclusively professional profile on LinkedIn, etc. However, in doing so, users are incentivized by the design and affordances of each platforms.

Context Collapse and Imagined Audience

The way we present ourselves changes according to the personal and public network, the context, and the environment. Therefore, even the practices related to self-promotion will have different characteristics depending on the social platform, the affordances it implies, the type of contacts in the network, and so on.

Moreover, in the digital environment of social media platforms, the traditional distinctions imposed by space and time are blurring, affecting what we imagine our target audience to be.

In this regard, Marwick and Boyd (2011) define as imagined audience the specific audience to which users think they are directing their content, even if on social media platforms anyone can potentially enjoy a piece of content. Indeed, users tend to “imagine” their audience based on clues, or traces, that they perceive within the digital environment. Therefore, when users present themselves on social media, they relate to an imagined audience, which does not necessarily reflect a real one.

This happens because social media “flattens multiple audiences into one—a phenomenon known as context collapse” (Ibid. p. 122). Users find themselves having to “manage” this type of audience that, due to the coexistence of various planes that we previously imagined as separate, brings out tensions between public and private aspects, between frontstage and backstage, thus shaping the identity and content conveyed by the user.

However, this dynamic also brings out the need to balance the desire of sharing the performance of the self with the necessity for privacy and to protect some sensitive or personal data from the risk of public dissemination.

Management of Personal Online Traces

Users are able to implement forms of control in managing their online identity. These actions are identified by Duffy and Chan (2019) with the concept of imagined surveillance, indicating the kind of responses consequent to both the scrutiny and the interaction with an “imagined audience (Litt, 2012; Litt & Hargittai, 2016) and the imagined affordances of individual platforms (Nagy & Neff, 2015)” (Ibid. p. 121). Indeed, with the term of imagined surveillance, these scholars identify those response mechanisms that users enact through social media as attempts in finding a balance between the tendency to visibility incentivized by platforms and the need to protect personal information.

In social media platforms, therefore, people modulate their activity according to the imagined audience, calibrating content, activities, and functions. In doing so, surveillance practices are put in place with respect to audiences, for example, through privacy settings; content, through self-surveillance or platform-specific presentations; and connections, which may point to one’s identity, using pseudonyms or multiple pseudonyms (Ibid.).

According to Duffy and Chan, users have internalized an approach to a surveillance culture (Lyon, 2018; Zuboff, 2019) that leads to these acts of ubiquitous monitoring. In the qualitative study conducted by the two academics, it emerges that most respondents claim that ““you never know who is looking” at your social media profile(s)” (Duffy & Chan, 2019 p. 132), and consequently, preventive measures are put in place, such as the self-monitoring of their activities, which also includes the elimination of contents or materials as forms of self-surveillance, or the settings for the use of privacy, which refer to the technological possibilities of the platforms. Duffy and Chan argue that these activities cannot be understood as separate from each other, but rather as one.

Therefore, users manage representations of themselves online, both by strategically using the affordances of the platforms and, at the same time, by self-regulating and self-monitoring in order to protect their private and sensitive data.

On Self-Branding and Online Traces

The branding of the self for economic and career purposes (self-branding) is one of the main activities in which users must manage all the data that identifies and represents themselves. The online self-branding is declined in communicative practices that have the purpose of enhancing the reputation of the user, creating a professional, uniform, and credible public image. Underlying online self-branding is the idea that visibility is something to be strategically managed, because it implies as much the manifestation of one person’s social situation as its economic value (Gandini, 2016; Draper, 2019). Therefore, these communicative acts are linked to the manifestation of a social identity, precisely because they are aimed to build a public self, and they can be directed and exhibited, but can also be subtle and implicit.

In this sense, the work of Brems et al. (2017) provides an interesting contribution, analyzing how journalists create their own brand on Twitter and certifying how self-branding activities expressed in an overly direct and assertive way can become counterproductive. The journalists they interviewed negatively evaluated activities that are too self-referred or too openly devoted to promoting their own content. In fact, they prefer a subtle and moderate approach, for example, by discussion with other users, expressing their opinions, and interacting with colleagues via private messaging.

This particular approach on self-branding is categorized by scholars as implicit, as opposed to more explicit forms of self-branding (Molyneux, 2014), which are flawed in conveying authenticity toward their audience. Among the forms of implicit self-branding, there are, for example, sharing a personal experience or a persona image rather than communicating strictly professional content, commenting and reacting to other users’ content, and interacting through private messaging. All these activities create information that users leave in the digital environment: traces that describe them, visible but indirect.

Journalists are an effective professional target to investigate when exploring self-branding practices on social media. On the one hand, journalism has undergone processes of radical transformation precisely because of the innovations introduced by digital media and especially by social networks and mobile devices (Anderson et al., 2012; Bell et al., 2017). On the other hand, news and media professionals often have a need to publicly interact and, consequently, become able to manage the communication trends incentivized by these technologies in order to enlarge and reach their audience. Unavoidably, this implies embracing the trend toward personalization, as previously described by van Dijck.

Methodological Note

The aim of this chapter is to offer an insight into the traces we leave on online platforms, especially focusing on describing both visible and invisible traces, and the resulting implications on the perception we have of ourselves.

In this regard, the theoretical premises previously outlined have been supplemented by the empirical data obtained from 20 in-depth interviews, conducted with 20 young journalists at the beginning of their careers. The interviews were conducted between 2019 and 2020, with young professionals who represent the Millennial generation who grew up with digital technologies and social networks, in the shadow of the economic crisis of 2008 (Dimock, 2019). The participants, aged between 23 and 35, work in journalism in a variety of sectors—from cultural to political journalism, from foreign affairs to crime or local news—and with different contractual modalities, freelance, permanent, and fixed-term contracts.

This chapter focuses on the intangible and invisible elements that form part of the flux of data at the basis of the structure of social media platforms. As discussed previously, these invisible elements—or invisible traces—simultaneously provide indications about the public image of users while also affecting their perception of themselves.

Therefore, the analysis was carried out through a qualitative and hermeneutic-discursive approach, which better responded to the need to qualify the experiences of the participants, which can be complex and difficult to standardize. This approach, in fact, prioritizes questioning in order to be able to engage with the personal experiences of the subjects, accessing their worldview and the meanings of certain situations, actions, attitudes, and feelings, as well as the vision of themselves (Blumer, 1969). Among the various techniques used, the non-standardized and semi-structured interview is preferable, as it allows participants to deepen their point of view and provide details about their experiences, thoughts, and feelings (Pitrone, 1984; Losito, 2004; Gobo, 2011; Gobo & Mauceri, 2013).

As the questionnaire touched on personal topics, it was conducted by face-to-face interviews. All the participants were identified by using a non-probabilistic sample, snowball sampling, and all the information obtained from the questionnaires was anonymized.

Finally, the data collected from the interviews was processed via thematic analysis, following a survey strategy inspired by grounded theory (Strauss & Corbin, 1990), which is used to explore social processes not yet fully defined and, consequently, to propose new theoretical frameworks. The analysis, therefore, moves from the empirical material of the interviews by creating codes identified from the most recurrent keywords for each thematic area and then gives rise to new conceptual categories.

Tracking the Traces

Social Media and Self-Branding

From the data collected through the interviews, it emerges that for most participants, the use of social media platforms is professionally necessary, for self-branding purposes and as tools for keeping up to date, finding breaking news, and identifying and getting in touch with useful contacts.

The participants also demonstrated familiarity with the promotional strategies to be conveyed through their profiles or pages. These strategies vary, ranging from the simple scheduling of content sharing—i.e., on which days and at what time to post certain content—to more sophisticated monitoring and publishing techniques, sometimes using dedicated apps and software, or paid sponsorships. These activities are diversified for each social media platform, paying particular attention to make the most of the specific affordances.

In using these promotional strategies, the interviewees operate a conscious monitoring of their activities, thus putting in place a form of self-monitoring of their performance, as described by Deborah Lupton.

Self-Tracking and the Algorithmic Imaginary

As briefly described earlier, the movement between data, users, and platforms can induce forms of emotional responses in the users, even despite the stated familiarity with the use of communication strategies, and an approach geared toward the constant monitoring of data.

For example, one participant reported feeling directly responsible if their post receives fewer interactions than expected. In fact, even if that is a platform-mediated response, they addressed it to personal characteristics that their audience may “dislike” or to their personal failure in their ability to master “the algorithm” in order to engage with the audience.

This aspect was also confirmed in other interviews and indicates how users enact a sort of interpretation of the algorithm that gives reasons for both the activities performed and the outputs obtained. The interpretation of the algorithm confirms what Taina Bucher called with algorithmic imaginary, that is, how users “imagine, perceive and experience” (Bucher, 2017 p. 31) the way the algorithm works and react accordingly. Experiencing the algorithm through imagined processes produces real and concrete effects (Ibid.).

Therefore, it is not unusual to try to understand the logic underlying the platforms, while not actually knowing their mechanisms, but proceeding by intuition or by “rules” dictated by common sense. Thus, the interpretation of the algorithm induces the users to read the data input and output in a certain way, which is useful in justifying the promotional choices to be made, but, also, in trying to give an explanation when these choices are not particularly efficient. However, from a different perspective, the outcomes seem to fall in the personal sphere, as if the failure of a certain goal, like trying to reach more people, was to be attributed to an individual failure.

The concrete effects of the algorithm’s interpretation manifest not only in the form of actions but also in the form of feelings and emotions. In this sense, self-monitoring activities related to the user’s (online) performance are strictly linked to how users perceive or, indeed, imagine the platform to work. In short, when users try to keep track of the traces that concern them online, these can produce outputs that involve strictly personal aspects and encourage different types of reactions, visible—for example, when a user purchases a content sponsorship service—and invisible, for instance, when a user feels at fault.

Indirect Traces, Invisible Traces

I mentioned previously how users implement self-promotion practices that do not necessarily have to be direct and explicit but which, while remaining visible, are designed to convey communicative messages indirectly.

Among these, reporting the geographic location emerged frequently among interviewees. This can be done, for example, by creating an explicit post indicating that the person is or is about to go to a specific place, by posting unequivocal photos, or by using specific platform features such as registration or tagging. Sharing the geo-localization is useful for publicly communicating the physical presence in a particular place, in order to meet old and new contacts. Therefore, by publicly reporting their location, users leave visible traces on their profiles or pages, which have also an indirect communicative function. At the same time, the geo-location indirectly provides insights about users, for example, if they go to a certain place, such as a restaurant, and how often; if they travel more willingly within their country or if they prefer experiences abroad; if they frequently visit a certain city; and so on.

Another example of visible but indirect traces that users learn to manage on social media platforms concerns the selection of personal contacts. In fact, interviews have shown that managing the audience is part of indirect self-promotion activities. This can take various forms such as eliminating the connection with all those people who are no longer considered in line with the user’s social media profiles, carefully selecting the people who can comment and interact with the published contents, or directing specific updates to a particular audience, for instance, tailoring the professional contents having already in mind a particular group of professionals.

Regarding the management of personal and professional contacts for promotional purposes, two interview respondents declared an interesting additional strategy. They stated that they purposely avoid communicating news, or any work update before the due date, for the fear that some colleague might steal their idea and in order to be among the first to deal with a specific topic. In such cases, it emerges that even the act of not posting and the act of not communicating are part of the user online relationships’ management.

As stated by many scholars (Donath & Boyd, 2004; Walther et al., 2008; Baym, 2010), online relationships can provide information about us and determine our social status. The contacts we have on social media platforms and the people we interact with are traces, visible but indirect, that can tell something about us. Therefore, selecting contacts means managing the information about us, both indirectly but visibly, the contacts with whom we interact, and indirectly and invisibly, since even the contacts with whom we do not interact are instrumental in building a personal image.

Managing the Self Online Through Invisible Traces

The creation and management of the personal image is fundamental from the perspective of self-branding and can have an impact, direct or indirect, even on the perception of oneself.

For many of the interview participants, professional identity and personal identity overlap, especially online. In fact, in the logic of self-branding, a piece of work published on a rather anonymous social media profile might have less possibility of circulation and engagement compared to those who, instead, convey their content through better defined and recognizable profiles.

Several interviewees declared that they had made, either consciously, drastically, or more gradually, a change of image on their social media profiles in parallel with the progression and development of their careers. This “restyling” manifests in various forms such as changing personal information, like the profile photo and name or nickname, or paying greater attention to personal details. This kind of information can be labelled as visible traces on personal profiles, entered directly and voluntarily, in order to convey a certain public image.

However, the personal image can also be built as a negative, not only by deciding to select the content to be shared but also by selecting the “rhythm” and therefore sparing the posting so as not to overload potential readers and, at the same time, demonstrating to have a quality profile.

From the interviews with the target group, in fact, it emerged that they pay attention not only to what—and how much—to share but also to other kinds of activities, such as minimizing and measuring the interactions, deciding not to use the sharing (or social) buttons and carefully selecting the targeted audience. All these activities serve to build the desired public image, and therefore they too can be categorized as information that profiles the user—traces, in this case, indirect and invisible.

Conclusions

In this chapter, I have briefly explored some of the different types of traces that might profile us on social media platforms, traces that tell something about our (online) persona. There are visible and direct traces, usually the result of an explicit request to fill in, such as a request to create a social media profile: a photo or an image that describes us and details about tastes and preferences.

Some elements can be visible, but are the result of an indirect action, such as the amount and type of our contacts or the type of language we use.

There are also visible traces that encompass both categories, such as sharing geographical location. Sharing a location can be both a direct action that the user performs in order to report where they are and can also have the indirect function of being a communicative tool for the people who are in that place—instead of informing them directly, for example, through private messaging.

Finally, also non-actions can provide information about the user. Not over-producing and over-sharing contents, measuring reactions and comments to the content of other users, and selecting the audience and the type of interaction with that audience: on social media, all these activities are used to shape the image, both public and private, of users. Therefore, on social media platforms, both direct and indirect visible traces, as well as invisible ones, contribute to shape a certain public image of the self.

The construction and management of this image is also the result of the interpretation of the algorithm, on the basis of which users make promotional activities using different strategies that differ according to the platform used and its relative functions. This phenomenon underlines the affective dimension in the user-platform dynamic since it overlaps, often through imaginative processes, personal aspects and technological functions. Many interview participants stated that they set their activities depending on how they imagine the algorithm to work. This interpretation process, in turn, may refer the platform’s outputs, for example, a post that received just few interactions, to personal aspects, like the idea of not being “smart” enough with the readers. The interpretation of the algorithm also highlights how the dynamic intersection between data, platforms, and users can lead to emotional responses.

In the previous pages, I briefly described how, through the process of datafication, almost every object and phenomenon can be translated into data, including those derived from the mediated practices of everyday life. Even if these data circulate autonomously, out of the control of the users, subjects tend to feel equally responsible for the outputs that emerge from the dialectic dynamic between users and data. Indeed, every trace we enter into the digital environment of social media platforms, whether direct or indirect, visible or invisible, provides information about us.

Clearly, these findings are limited to narrow research data and do not claim to be generally applicable. Nevertheless, they provide food for thought to be explored more fully in future research, especially regarding the relationship between digital environments, identity, and the practice of self-monitoring and self-management.