THE INVISIBLE MANAGEMENT OF VISIBILITY-DRIVEN WORK: GOVERNANCE BY SOCIAL MEDIA PLATFORMS

La gestión invisible del trabajo orientado a la visibilidad: Gobernanza mediante plataformas de redes sociales

ABSTRACT

Social media platforms (SMP) are technologically mediated social action spaces that profit from collecting and selling user data. Users, not platforms, create content that attracts audiences and advertisers. While they are free to interact, they must do so in ways programmed to add value to the platform. Thus, if users are driven toward achieving organizational goals, all phenomena on these platforms have an organizational substrate. Even though business and management studies have consistently produced literature on gig work intermediation platforms, SMP are not included among digital labor platforms. By combining business literature, social sciences, platform studies, and critical algorithm studies, this theoretical essay proposes a conceptual framework that presents SMP as an organizational form of production, management, and work. This framework is then confronted with research findings on content creators, revealing that the three self-governance strategies of SMP effectively manage creators by instilling hope of visibility and fear of invisibility.

Keywords:
work management; social media; platforms; free labor; content creators.

RESUMO

Plataformas de mídia social (PMS) são espaços mediados tecnologicamente que sobrevivem da coleta e venda de dados de usuários. Os usuários, e não as plataformas, criam o conteúdo que atrai públicos e anunciantes. Embora livres para interagir, os usuários o fazem em formatos programados para agregar valor à plataforma. Assim, se toda utilização é direcionada pelos objetivos organizacionais, todos os fenômenos em PMS têm substrato organizacional. Embora haja consistente literatura acadêmica de Administração sobre plataformas de trabalho, não são incluídas entre elas as PMS. Combinando literatura de negócios, ciências sociais, estudos de plataformas e estudos críticos de algoritmos, este ensaio teórico propõe um framework conceitual que posiciona as mídias sociais como formas organizacionais de produção, gestão e trabalho. Em seguida, confrontamos nosso framework com pesquisas sobre criadores de conteúdo, revelando que as três estratégias de autogovernança das PMS gerem os criadores por meio da esperança de visibilidade e do medo da invisibilidade.

Palavras-chave:
gestão do trabalho; mídias sociais; plataformas; trabalho gratuito; criadores de conteúdo.

RESUMEN

Las plataformas de redes sociales (SMP) son espacios de acción social mediados tecnológicamente, que se benefician de la recopilación y venta de datos de los usuarios. Ellos, no las plataformas, generan el contenido que atrae al público y a los anunciantes. Si bien gozan de libertad para interactuar, deben hacerlo en formatos programados para aportar valor a la plataforma. Las SMP dirigen el uso hacia objetivos organizacionales, imbuyendo toda actividad de un carácter organizacional. Existe consistente literatura académica de gestión sobre plataformas de trabajo, pero las SMP no se incluyen entre ellas. Combinando literatura empresarial, ciencias sociales, estudios de plataformas y de algoritmos, este ensayo teórico propone un marco conceptual que define a las SMP como formas organizativas de producción, gestión y trabajo. Luego, contrastamos nuestro marco con investigaciones sobre los creadores de contenido, revelando que las tres estrategias de autogobierno de las SMP gestionan a los creadores a través de la esperanza de visibilidad y el miedo a la invisibilidad.

Palabras clave:
gestión laboral; redes sociales; plataformas; mano de obra gratuita; creadores de contenido.

INTRODUCTION

Digital platforms are not neutral spaces for human interaction. Platform companies create these reprogrammable infrastructures, organized through data collection, algorithmic processing, monetization, and distribution, to facilitate and shape human interactions (Poell et al., 2019), actions, and activities, which produce the resources central to the business. Thus, these organizations inscribe their interests and values in technical infrastructure, the general foundation for activities and interaction, becoming rule-setting and rule-enforcing actors (Dolata & Schrape, 2023).

Platforms fiercely resist legislation to regulate them and hold them accountable for what happens in their digital space, influencing public perceptions to boycott discussions and lobbying to dissuade public authorities (Haeck, 2024; Paul, 2024; Rudnitzki & Lobato, 2023). Different countries and regions have different approaches and levels of agility in dealing with it. For example, specifically regarding social media platforms (hereinafter SMP), the Digital Services Act (DSA) of the European Union came into force in 2024, requiring big techs to better regulate illegal and harmful content (Udrescu & Jacqué, 2023). While in Brazil, the Marco Civil da Internet, a 2014 law that establishes principles, guarantees, rights, and obligations for the use of the Internet, has become outdated in the face of rapid changes in the digital environment, including its inability to address the content of social networks and their creators (Agência Senado, 2024). SMP are, in practice, the first legislators of their own rules and guidelines.

Platforms’ assertions that they are already self-regulating and that external regulation would harm the economy or freedom of expression increase opposition to the adoption of local laws (Rudnitzki & Lobato, 2023). According to Ceylan et al. (2017), besides failing to moderate hate speech and misinformation, SMP are largely responsible for their dissemination. Their study about Facebook users shows that 15% of the most frequent sharers spread 30-40% of fake news because the social media’s algorithmic recommendation system rewards visibility users who share content frequently, whether sensationalist or false. Political and social falsehoods often remain online under the guise of protecting free speech, while lies about other topics, such as health, are more easily eliminated (Waddell, 2020).

The greatness of SMP political influence is evident in incidents such as the Cambridge Analytica scandal. The digital strategy that influenced the vote for Donald Trump for President of the United States in 2016 was only possible because Meta gave the political consulting firm data from millions of users of its SMP, Facebook (Cadwalladr & Graham-Harrison, 2018). Therefore, it is critical to understand that organizations-their business models, methods of monetizing and managing human interactions-underpin the phenomena that occur or result from platforms, from new occupations and forms of work to changes in cultural habits and their influence on political decisions. As digital platforms have become central to social habits and decisions, understanding how they manage and control users is essential.

Platforms profit in two main ways: a) by charging fees for intermediating transactions, for example, Apple Store and Google Play software and digital content stores, Amazon e-commerce, and transportation and delivery apps; or b) by collecting and selling user data to advertisers, namely Facebook, Instagram, YouTube, TikTok, and the Google search engine (Kenney & Zysman, 2016). The core feature of the business models of platforms for crowdwork, mobility providers, accommodation, and delivery services is the extreme outsourcing of work and means of production (Casilli & Posada, 2019; Dolata & Schrape, 2023), allowing the work-mediating platform owners to save around 30% on labor costs (Srnicek, 2017). Utilizing user labor to produce content is an unprecedented level of capitalism’s capacity to exploit non-workplace labor. Users are essential contributors, from user-generated content on social media to peer evaluations on travel or e-commerce websites (Jarret, 2022).

Even if an organization denies users the status of workers, it must still control them. Therefore, it retains authority over functions such as data collection, service pricing, and revenue collection while delegating responsibility for functions such as working methods, schedules, and performance evaluation to users and complementors (Vallas & Schor, 2020), those who complement products and services provided by platforms (Poell et al., 2022), like drivers and content creators.

There is a rich and growing body of academic work on platforms; however, each research tradition focuses on a specific aspect of platformization (Poell et al., 2022). Business and management studies and economics are foundational research areas on digital platforms, providing valuable insights into the new multi-sided markets, their strategic use, innovation, and service provision intermediation by platforms (such as delivery, ride-hailing, and microtasks). However, they do not include SMP between digital labor platforms, nor do they treat creators who are paid or seek to be paid for their digital production as workers (Aloisi & Stefano, 2020; Hagiu & Wright, 2019; Keegan & Meijerink, 2023; Kuhn & Maleki, 2017).

Scholars in other fields, such as critical political economy, creative digital labor, and media and cultural studies, have not made this omission. However, while they investigate the power dynamics between platforms and creators, they do not address work management.

Because changes in one dimension of platformization cannot be properly understood without examining related changes in other dimensions (Poell et al., 2022), observing the new occupation of content creation needs to begin by recognizing that its practices, ethos, and identity are conditioned by the organizations from which it emerges and is managed - just as administrators and journalists are conditioned by their industry.

If SMP are not evident workspaces, work management remains unexplored. The well-known term algorithmic work management (Duggan et al., 2020; Lee et al., 2015) is an example of the tired strategy of simply adding technological adjectives to earlier concepts, lacking a deeper conceptual construct, and providing little benefit to academic discussions. This phrase is commonly used in research on service mobile applications to describe automated methods of assigning and controlling tasks, punishments, incentives, and rewards for workers and is especially inappropriate for SMP. First, it reifies an instrument by making it an actor in the relationship between platform and user, thereby overshadowing the agency of organizations. Second, it perpetuates the belief that algorithms are incomprehensible black boxes that operate without human intervention, absolving companies of liability when something goes wrong with platform self-regulation and reinforcing their status as mere intermediaries (Bucher, 2018). Third, the term cannot encompass the complex, hidden management of a workforce that companies do not recognize as such. Finally, we reject neologisms because governance is the institutionalized coordination that which defines relationships, regulates access, structures permitted actions, and provides a legal basis for commercially exploiting users’ activities through terms and conditions (Dolata & Schrape, 2023).

Given the lack of literature in business and management on the creators of SMP as workers subject to management, we intend to demonstrate that organizations employ management through governance strategies. Studying these platforms’ governance is important for understanding their internal dynamics and their broader societal and political consequences.

Our discussion of the basic structures of this relationship is presented as a theoretical essay, a type of critical writing to explore existing theories, often in relation to a specific social reality, contributing to the expansion of academic discourse (Meneghetti, 2011; Moya, 2017). Theoretical essays entail reflection and interpretation to propose new ideas or alternative perspectives, emphasizing the importance of the dialectics of theoretical concepts and understanding conceptual histories, which means the conceptual incorporation of language into previous thought processes (Brons, 2010; Meneghetti, 2011; Moya, 2017). Following Moya’s (2017) suggestions for essays, we use writing structures and strategies ideologically and intentionally to deepen the social function of the text, so, as Brons (2010) postulates, “language and thought themselves function as a dialectical pair” (p. 298) whose boundaries are blurred.

Drawing on literature from economics and business, social science, platform studies, and critical algorithmic studies, we propose a conceptual framework that presents SMP as an organizational form of production, management, and work. To demonstrate that companies manage users’ work in this context through three self-governance strategies, we articulate our theoretical framework with contributions from empirical research on content creators, who are more easily identified as digital workers. Our goal is to demonstrate how SMP manage users based on business values and objectives, resulting in organizational foundations for all phenomena that occur on them.

PLATFORMS: INFRASTRUCTURE, MARKET, AND ORGANIZATIONS

A platform is a set of techniques, technologies, and digital interfaces provided to users to build social interactions and economic activities on a stable substrate (Kenney & Zysman, 2016). The owner company creates the platform as a mode of socio-technical intermediary and business arrangement (Langley & Leyshon, 2017). It enables, organizes, and directs the value creation of users and complementors. The platform earns revenue from the actions of third parties, either by charging for intermediate transactions or by selling user data. Before the first decade of this century, the web ecosystem was decentralized, with independent websites spread across the public Internet.

Platforms have captured the dispersion of the global digital network, centralizing, controlling, and monetizing the exchanges that occur on them. The rise of the platform as the dominant infrastructural and economic model of the social web-the platformization of the web-began with Facebook between 2006 and 2007. Facebook became a platform for third-party developers by giving them access to its users’ data and a set of programming tools, an Application Programming Interface (API). Programmability enables a platform to expand and embed itself in other domains, decentralize data production to complementors, and then recentralize data collection (Helmond, 2015). APIs promote content sharing, connect services, and function as regulatory instruments for platform-to-third-party relationships, business models, and data collection tools. After APIs, “social networks” have become social media platforms.

The primary source of competitive advantage, capital, power, and influence in a platform business is the positive network effect: the exponential growth of its value as the number of users increases (Parker et al., 2016; Vlist, 2022). Five platform firms own the largest, most profitable, and most widely used systems in history by concentrating on Web-based intermediation: Alphabet, Amazon, Apple, Meta, and Microsoft (Vlist, 2022). The platforms’ narratives about their long-term surveillance of user habits, fueled by the network effect, give them an alleged unbeatable advantage, preventing the launch of competitors (Giblin & Doctorow, 2022).

There is a distinction between the operating company, its platform, and how the former coordinates, controls, and exploits the latter. Corporations are organizational nuclei whose purpose is to run a profitable business. They establish rules for structuring, selecting, monitoring, and evaluating what happens on platforms. Platforms are social action spaces with a solid technical base and a reliable institutional foundation where actors engage in variable actions and activities that produce resources that the corporation transforms into commodities. The institutionalized mechanisms of coordination, control, and exploitation of social actions and economic processes on the platform link it to the corporation. Non-negotiable contractual relationships, established through detailed terms and conditions set by the corporation, establish these mechanisms (Dolata & Schrape, 2023).

Platform businesses have an unprecedented capability: they can technically and economically implement the widespread commodification of behavioral traces. This means that profit-driven strategies for valuing aspects of society, particularly people’s everyday behavior, can now be used in ways that were previously unthinkable (Couldry & Mejias, 2019). This commodification of user behavior takes place in institutionalized coordination, the interplay between the two levels of the platform architecture, the operating company and its platforms, according to Dolata and Schrape (2023).

The commodification of human attitudes on platforms is datafication: the translation of life into quantifiable and analyzable digital data to track, diagnose, and predict behavior (Lemos, 2021). The human experience is abstracted to generate profit. Thus, platforms “produce the social for capital” (Couldry & Mejias, 2019, p. 3). According to Srnicek (2017), platform capitalism is a historical extension of capitalism in which data, its surveillance, and extraction serve to train algorithms, enable the coordination and outsourcing of workers, and allow for the optimization and flexibility of production processes. The outsourcing of labors to users is an intensified and radicalized continuation of the deregulation and flexibilization of work and labor relations (Dolata & Schrape, 2023).

Besides monopolies (when sellers have power over buyers), large platforms are also monopsonies (when buyers have power over sellers). In monopsony, a company separates producers from consumers, capturing a disproportionate share of value from the relationships between them. In this chokepoint capitalism, the monopsonists drive the amount paid to workers and suppliers below what they would receive in a competitive market. Platform companies are liable for predatory practices not because they are platforms but because they strangle the market (Giblin & Doctorow, 2022).

Platforms enroll users through a participatory economic culture to create multi-sided markets, coordinate network effects, increase scale, and extract revenue from data circulation (Langley & Leyshon, 2017; Srnicek, 2017), positioning the bulk of the workforce as independent contractors rather than employees (Jarrett, 2022). Whoever signs up for a platform accepts its terms and conditions, transferring rights to the data generated to the company (Dolata & Schrape, 2023). Thus, the power relationship between the organization and the other actors on the platform is inherently asymmetrical (Cutolo & Kenney, 2021).

Social media: Structural principles and logic of exploitation

Built around the convergence of content sharing, communication, and interpersonal connection (Burgess et al., 2018), SMP are peculiar value extractors from sociality. Despite rhetorically promising to give users the power of choice, SMP structure the process, format the options, define default settings, and direct users to specific paths, granting third parties an extremely limited version of autonomy while leaving their own autonomy intact (Graham & Henman, 2019). As platforms shape and manage permitted activities, they morph into systems that design and manipulate connections.

SMP’s exploration logic is indirect: extracting users’ behavioral traces as data to attract advertising revenue (Dolata & Schrape, 2023). The organization creates digital spaces where third parties produce what it sells (Fuchs, 2013), and its technical arrangement gives people the illusion of autonomy while directing them to achieve business goals in the same way that it manages employees (Jarret, 2022). In this less obvious workspace, instruments like codes, resources, policies, and guidelines work just as well to control user practices as “the allocation of tasks in a Taylorist office,” Jarret (2022, p. 76) states.

Four principles structure SMP: programmability, popularity, connectivity, and datafication. “Programmability” is the ability to trigger and steer user contributions through algorithms (Dijck & Poell, 2013), which permits users to join the platform immediately without friction and start creating value for the business, driving the organic, scalable, and almost unlimited growth of the network effect (Parker et al., 2016). Codes direct the flow of communication and prioritize certain types of content over others. The volume of interactions in SMP exceeds the capacity of only human moderators to ensure compliance with public legislation and platform guidelines, mandating automated moderation (Katzenbach & Ulbricht, 2019). Therefore, algorithms mediate content, experiences, and relationships (Dijck & Poell, 2013), which impacts the likelihood that audiences will find and engage with posts (Beer, 2013).

“Popularity” is the power of agenda-setting or pushing certain topics to the forefront. It is evident in rankings and recommended content, whose metrics reflect the platform’s measures and are sensitive to user actions to promote or denounce a specific item. Underlying this principle is scale: the more popular a post, the greater the number of users (data producers) it attracts. The time users spend socializing on platforms is surplus production and, therefore, unpaid labor (Jarret, 2022).

“Connectivity” refers to the socio-technical capacity of platforms to connect content to user activities and advertisers. Even if users have considerable influence over content contributions, SMP always mediate and define how connections take shape. Connectivity is a strategic tactic that effectively enables human connectedness while pushing automated connectivity. Finally, “datafication” is the ability to quantify aspects of the world that have never been quantified. Datafication gives SMP the ability to develop predictive and real-time analytics techniques, allowing the immediate redirection of content and advertising to participants (Dijck & Poell, 2013).

SOCIAL MEDIA PLATFORM GOVERNANCE AND WORK MANAGEMENT

As platforms have spread, so has their power to reorganize, disperse, and recompose work. Their self-definition as technology companies that facilitate transactions between independent workers and clients, rather than employers who control their employees, hides a severe power and information asymmetry that exists in their relationship with workers (Calvo et al., 2023). Platformization, or the growing dependence on platforms to obtain, perform, and sustain work activities, tends to generalize as various labor activities rely more heavily on digital infrastructure and its underlying logic (Casilli & Posada, 2019; Grohmann, 2020).

Calvo et al.’s (2023) systemic perspective on platform work expands previous views, including a wide range of legacy industries affected by platform. From their sociological perspective, there are three broad categories of platform workers: 1) personnel and contractors directly tied to the platform company; 2) work that the platform mediates, broken down into: 2. a) virtual or in-person services hired and paid through the platform (for example, digital influencers and app developers); 2. b) vendors who sell goods or services through the platform, provided in-person (e.g., Uber and Airbnb) or remotely (such as Upwork); 2. c) content creators who post on SMP and can become paid if successful; 2. d) prosumers, everyone who interacts with a platform and incidentally provides data; and 3) work affected by the platforms, as 3. a) professional services (for instance, advertising and journalism); 3. b) indirect workers, like lawyers, scriptwriters, and web designers, who assist content creators; 3. c) other service workers (such as restaurants, and real estate); and 3. d) manufacturing sectors transformed by platforms.

Given the structuring principles of the platforms (programmability, popularity, connectivity, and datafication) and the scale of human labor mobilized, management is mostly automated. What makes it possible are the algorithms: mathematical instructions coded for transforming input data into a desired output, built on specific interests, strategies, policies, and stakeholders (Gillespie, 2018a), reflecting the beliefs, biases, values, and cultural assumptions of those who write them (Bucher, 2018). Algorithms shape where and to whom data flows as a new type of power that operates within people’s lives (Beer, 2013).

The two types of algorithms are pre-programmed, which always produces the same output for a given input, and machine learning, which learns from examples to change behavior, improve performance, and predict outputs (Bucher, 2018). In SMP, every click and every query increases the tool’s functionality. Although algorithms play a vital role, they cannot function without user-generated data (Gillespie, 2018a), implying that they are powerful but still just tools.

We must avoid the simplistic technological determinism of technology as a driver in explaining phenomena; instead, it is necessary to examine the human and institutional choices behind the mechanisms (Gillespie, 2018a). Therefore, we argue that the technological fetishism (Feenberg, 2001; Harvey, 2003) inherent in the concept of algorithmic work management is detrimental to understanding peculiar SMP’ work management. Furthermore, it reinforces the perception that the algorithm is a black box. This metaphor favors ignorance instead of knowledge, serving as “strategic unknowns” for companies to avoid liability when platform issues arise (Bucher, 2018, p. 56). Furthermore, new terms are unnecessary when the understanding of governance is appropriate.

A common understanding equates governance with regulation, which is defined as operations that intend to influence a certain behavior in a field to produce a predictable result, using standards, regulatory infrastructures, and coordination to achieve this goal. However, Hofmann et al. (2017) argue that this perspective only accounts for a limited set of ordering processes and tends to interpret existing rules and institutions as functional outcomes of problem-solving activities. They propose a new approach to governance as reflexive coordination, focusing on ‘critical moments,’ when routine activities become problematic and need to be revised. Thus, regular coordination itself requires coordination, emphasizing interaction, cooperation, and negotiation to potentially redefine the rules.

Platform governance is also relational because algorithms are social, capable of shaping behaviors, preferences, and content creation, while being redefined by them (Napoli, 2014). These codes are the result of various relationships; they communicate or act on behalf of someone or something, and their existence is always relational (Laapotti & Raappana, 2022).

Here, we adopt Gorwa’s (2019) more straightforward definition of SMP governance, which recognizes three primary forms: governance by platforms (self-governance), governance by external parties (governance of platforms), and multi-stakeholder governance (co-governance). The last one is a hybrid of the previous two, wherein the business establishes councils to gather input from the government and civil society. As mentioned in the introduction, SMP governance varies by country, with strong external interference in some and minimal in others.

Governance of platforms through specific laws is uncommon, and self-governance is the most common way SMP govern themselves before regulators intervene. This does not imply that platforms have absolute power, as they are subject to regulatory scrutiny and must abide by local laws. As long as they respond to public pleas and court orders to remove harmful and criminal conduct, SMP are not liable for user misbehavior. Nevertheless, Gorwa (2019) argues that these responses seem to be strategically crafted to evade potential external regulation while also preserving the highly profitable status quo. Platforms establish their own rules and regulations for digital spaces, but stakeholders also shape them, making governance a complex relational construct (Vlist, 2022). Therefore, notions of SMP as self-governing and open to reflective coordination coexist.

Platform services such as SMP significantly influence and mediate individual behavior, so they engage in governance at the individual user level (Gillespie, 2015). As we are dealing with individual level management here, it is governance by platforms that manages users’ work. This is operationalized by three independent, overlapping, and constantly updated strategies: regulation, curation, and moderation.

The regulation sets the formal and technical arrangement in which cultural production takes shape; it concerns standards, guidelines, and policies continuously updated, including terms of service, technical affordances, and APIs (Gillespie, 2018b; Siciliano, 2021; Poell et al., 2022). According to Bateman et al. (2021), their data on thirteen social media and messaging platforms show behavior, not content, is the top focus of community standards. The regulation also disciplines creators through instructions and educational materials, emphasizing the relevance of audience metrics, suggesting more profitable best practices, and promoting entrepreneurship (Siciliano, 2021, p. 236).

For clarity, Table 1 shows the guidelines and policies of Instagram, TikTok, and YouTube, the most popular platforms among digital influencers in Brazil (Navarro, 2024), the second-largest country with over 10 million online influencers (Gonsalves & Valim, 2024). Despite being part of the regulation, educational materials for creators differ from policies. While the guidelines address terms of service, content and behavior restrictions, and monetization standards, the educational segment (Table 2) advises and instructs creators on how to work to grow their audience and earn platform rewards. As these standards continually change, the data gathered here are snapshots in time.

Table 1
Guidelines and Policies of Instagram, TikTok, and YouTube

Category*	Policy	Instagram	TikTok	YouTube
Content Standards	Adult sexual exploitation	X	X
	Adult sexual solicitation	X	X
	Child safety and privacy/Parent’s guide	X	X	X
	Children - content with	X		X
	Nudity and Sexual Content	X	X	X
	Vulgar language policy	X	X	X
Goods and Services	Firearms	X	X	X
	Illegal or regulated goods or services	X	X	X
Integrity and Security	Privacy and cybersecurity	X	X	X
	Prohibition of encouraging guideline violations			X
	External links		X	X
Intellectual Property	Copyright	X	X	X
	Counterfeit	X		X
	Trademark	X	X	X
Misinformation and Fraud	Fake engagement	X	X	X
	Impersonation	X	X	X
	Misinformation	X	X	X
	Misinformation - Medical			X
	Misinformation - Elections	X	X	X
	Spam, fraud, scams, and deceptive behavior	X	X	X
Monetization Policies	Advertising/Branded Content earnings policy	X	X	X
	Advertiser-friendly content guidelines			X
	Earnings from fans/community	X	X	X
	Earning from Partner/Reward Program	X	X	X
	Selling products	X	X	X
Violence and Harm	Animal abuse	X	X	X
	Defamation	X		X
	Harassment and cyberbullying	X	X	X
	Harmful or dangerous content		X	X
	Hate speech	X	X	X
	Human exploitation/trafficking	X	X
	Organizing extremist, illegal or harmful activities	X	X	X
	​Suicide, self-harm, and eating disorders policy	X	X	X
	Support terrorism, criminal or hate groups	X	X	X
	Violence incitement	X	X	X
	Violent or graphic content policies	X	X	X

• Note:
• ^*
  Assigned by the authors. Data retrieved between 25 and 30/05/2024 from https://support.google.com/youtube/ https://help.instagram.com/; https://transparency.meta.com/; https://support.tiktok.com/

Table 2
Instagram, TikTok, and YouTube Educational Material Topics

Category*	Topic	Instagram	TikTok	YouTube
Learning the techniques	Choosing equipment and learn to use it	X		X
	Filming standards and techniques		X	X
	Improving accessibility	X	X	X
	Live streaming	X	X	X
	Manage asset metadata			X
	Use diverse media formats and lengths	X	X	X
	Use audio / music	X	X	X
	Video Editing Skills		X	X
Personal brand	Customize your channel and feed	X		X
	Find your 'why'	X
	Going full-time	X
	Personalize your profile	X	X
Optimizing content for visibility	Collaborate	X		X
	Craft data-driven strategies	X	X	X
	Create algorithm-friendly content	X
	Create longer videos		X
	Create shorter videos			X
	Embrace fan content trends	X	X
	Optimize your content	X	X	X
	Repurpose the content	X	X
	Strategize your content	X	X
Productivity strategies	Create Playlist		X	X
	Creating upload schedules			X
	Promoting your video		X
	Programming best practices			X
	Save time creating	X
Using data exploration tools	Track your content performance	X
	Understand your audience and their preferences	X		X
	Get insights and discover trends from data	X	X	X
Audience relationship management	Building a loyal audience / a community	X		X
	Call the audience to action	X	X	X
	Creating community posts			X
	Engage with your audience	X	X	X
	Manage unwanted interactions	X
	Managing and moderating the comments			X
	Reply and connect with your audience	X		X

• Note:
• ^*
  Categories assigned by the authors. Data retrieved between 25 and 31/05/2024 from https://creators.instagram.com/, https://tiktok.com/creator-academy/, https://youtube.com/creators/

Curation refers to topics’ categorization and selection by platform to steer user interaction. Traditional curation relies on experts and institutions to uphold cultural norms and professional conduct, while automated curation combines algorithm-driven and user-driven selection. According to their techno-commercial strategies, platform algorithms trigger and filter user activity (choices, clicks, searches, and shares) to influence content, service, visibility, and availability (Dijck et al., 2018). Curation illustrates how data-hungry platforms’ business models relate to social phenomena. While extremist content recommendations are rare for casual viewers on YouTube, they are common for those who already consume it (Chen et al., 2023), steering them toward a narrower ideological range (Brown et al., 2022) and creating echo chambers for political extremism, conspiracy theories, white nationalism, the alt-right, and QAnon (Haroon et al., 2023). Because algorithmic curation prioritizes user engagement and permanence, it feeds them more of what they already watch, regardless of content.

Finally, moderation structures content availability, consisting of pre-screening, rejection, removal, banning, demotion, or demonetization of content and accounts. This eliminates violations of the platforms’ regulations and content that cause stakeholder shock or outrage (Gillespie, 2018b; Poell et al., 2022), whether reported by users themselves or ordered by court order. SMP are often criticized for moderating too little, neglecting serious cases, or too much, filtering out historically or culturally significant topics (Dijck et al., 2018). In countries without specific laws, for example, authorities must persuade platforms to fight fake news, even when it harms victims of a tragedy (Strickland & Doria, 2024). Given this complexity, human moderation can never be fully replaced, but companies increase automation (Gorwa et al., 2020; Wright, 2022) and ask their users to flag inappropriate content (Dijck et al., 2018).

Based on the previous explanation, we depict SMP as an organizational form of production, management, and work in Figure 1. As the organizing and rule-setting core, the organization produces, provides, and controls the platform’s technological infrastructure. The owner company has defined the social rules that govern this social action space (the platform) under its values, interests, and goals, giving it an action-oriented institutional foundation. Governance regulates, structures, and monitors the users’ activities, not forcing but inducing them to take actions that leave behavioral traces, whose data are captured and transformed into saleable commodities, especially to generate advertising revenue. Thus, the central business resource comes from the outsourcing of productive work to users, who are rewarded only when their “productivity” is immense.

Figure 1
Social Media as an Organizational Form of Production, Management, and Work

THE INVISIBLE MANAGEMENT OF VISIBILITY-DRIVEN WORK

Content creators are those who try to make a living by producing digital content across multiple platforms, learning how to deal with innovative technologies and algorithms, and negotiating their identities within commerce circuits, all while building a community of followers around themselves and their activities (Arriagada & Ibáñez, 2020). This group encompasses everyone from live streamers to app developers and podcasters. A notorious subgroup on SMP is digital influencers, the quintessential internet celebrities with positive notoriety, talent, and skills (Abidin, 2018), thousands of admirers, and a personal brand produced as a commodity (Karhawi, 2016), who are successful in monetizing their online presence (Duffy, 2020; Arriagada & Bishop, 2021). To convert visibility into compensation, they use identity self-presentation strategies and form communities around themselves and their content, created with periodicity, thematization, and reputation-attributed and legitimized by the public (Karhawi, 2021).

Most aspiring content creators seek enough visibility to turn it into direct compensation through monetization on SMP or an indirect reward through agreements with brands or job opportunities outside the digital sphere (Simón, 2022). In the attention economy of SMP, the currency is platform metrics: creators need verifiable evidence of their ability to influence (like subscribers, followers, comments, and reactions) to monetize (Duffy, 2020).

Creative expression is difficult to measure and control, so it requires unusual management approaches that organize the work activity and simultaneously preserve laborers’ illusion of autonomy. Although the organization does not formally impose rules about work hours and pace, they do exist. The “invisible management” operates indirectly, such as guidelines, policies, and instructional material (Table 1 and Table 2). These mechanisms for controlling user work, prescribing the scope of acceptable activity, and punishing violators’ work just as well as daily task assignments in a “Taylorist office” (Jarrett, 2022, pp. 74-76).

Governance strategies overlap in managing work, so we will address how each one affects creative work separately for clarity.

1) Regulation influence: Visibility is presented as a value achieved only by obeying “algorithmic norms,” devices designed to govern behavior, such as instructions from Instagram Creators Lab, TikTok Creator Academy, and YouTube Creators (Table 2), as well as guidelines and policies. According to Araújo (2021, p. 30), YouTube repeats to the creators the fallacy of the algorithm as an intermediary that only portrays the audience’s choices, conditioning visibility on the creator’s ability to induce the audience to watch more videos. Behind the alleged public preferences, the instructional discourse hides the algorithm’s bias and the organizational objectives (Araújo, 2021). In addition to being an advisor to those seeking to monetize content, YouTube presents itself as the legislator, judge, and executive authority that decides who to punish and who to reward (Kopf, 2020).

SMP recommend that creators tailor their content to audience trends to gain visibility and equate work worthy of payment with viewers gained. This means that, based on what they can measure, they encourage production under more profitable standards for their business. The instructions given are quite normative. Facebook, for example, says things like “post regularly,” “make longer videos,” “use readable text, bright colors, and faces,” “improve searchability with precise video tags and attractive thumbnails,” and “prioritize responding to comments and encourage viewers to interact” (Primo et al., 2021, p. 68).

Frequently updating policies, guidelines, monetizing rules, educational materials, and tools can lead to worker insecurity and re-learning through trial and error (Arriagada & Ibáñez, 2020). Compensation terms can change without warning, exposing even successful influencers to sudden demonetization, as in YouTube’s infamous advertiser apocalypse of 2017. When more than 250 multinational companies revolted against their ads appearing next to extremist videos, Alphabet ramped up moderation, demonetizing content and channels deemed unfriendly to advertisers and making it harder for creators to join the YouTube Partner Program (YPP), which raised the number of subscribers, views, and hours shown for a channel to qualify for compensation. The change also affected creators without extremist content, who lost revenue and had their videos suspended by the new advertiser suitability filter. This case highlighted the vulnerability of YouTube creators and the asymmetry between effort and reward (Burgess & Green, 2018; Cunningham & Craig, 2021). The minimum viewing time for a YouTube channel to be compensated is counted in years, and the ability to attract viewers is directly linked to earnings (Hertzog, 2019).

In addition to producing for multiple SMP, creators must adapt their production and distribution processes, marketing strategies, interaction, and creation as platforms’ communication styles and tools evolve. In this ever-changing technological, social, and commercial ecology, increased competition has replaced the creative ideal (Arriagada & Ibáñez, 2020). Thus, overworking is inevitable in the pursuit of rewards based on visibility. On the one hand, curation recommends creators who publish content regularly and consistently. On the other hand, mastering the recommendation system is often acquired by trying different solutions and approaches.

2) Curation influence: Algorithm curation defines the success or failure of content, but its operation remains a mystery, so creators build mental models of how it works (Bucher, 2018). They then orient creative practices to increase metric visibility, and quantification shapes their culture (Abidin, 2018), prioritizing what is measurable over zeal for reputation (Siciliano, 2021). Although curation and its criteria have a significant impact on visibility, the educational content on the platforms treats it as a pure reflection of public preference. For the creators, curation determines their visibility. For the platform, it serves to attract more users and capture more data (Siciliano, 2021). Instagram influencers strategically navigate the platform’s standards, norms, and algorithmic architecture by cultivating seemingly genuine audience relationships to optimize visibility and engagement, basically playing a “visibility game” as described by Cotter (2019). On Facebook, creators form an algorithmic imaginary: beliefs, experiences, and expectations stemming from imagination and perceptions of what the algorithm is fill the hypothetical understanding that guides content production, according to Bucher (2018). As Bishop (2019) reports, YouTube creators share experiences about algorithms and build collective knowledge and optimization strategies to align their content with the platform’s supposed logic and circumvent its restrictions. They learn which content and subjectivities the curation prefers through improvised experiments and comparisons and then orient and structure their production for visibility (Duffy & Meisner, 2023). Even when they try to “beat the algorithm,” they are defeated: their strategy entails producing increasingly frequently, just as the organizations desire (Arriagada & Ibáñez, 2020, p. 9).

The creators experience permanent insecurity and necessary overwork while responding to the stimuli of the platform and attempting to anticipate them. Therefore, we see curation as a strong organizational control tool that promotes self-management, self-control, and self-exploitation in their work.

3) Moderation influence: Together, curation and moderation are established to ensure users comply with regulations. Although platforms assert that moderation benefits their community, it is actually intended to satisfy advertisers, according to Poell et al. (2022). For example, after extremist videos outraged advertisers in the so-called apocalypse, YouTube implemented a new policy, but this ended up demonetizing LGBTQI+ advocates and domestic violence reporters because they were considered advertiser-unfriendly (Cunningham & Craig, 2021).

Minority creators report a sudden drop in their content’s visibility, leading to decreased reach and engagement, a practice known as shadowbanning (Cotter, 2019; West, 2018). The groups that most denounce this concealment are non-white individuals, LGBTQI+ individuals, women, and those without a large following (Duffy & Meisner, 2023; Ma & Kou, 2021). While SMP deny the existence of shadowbanning (Cotter, 2019), creators speculate to make sense of moderation in the absence of explanations. Most speculation attributes content removal for complaints from other users who stalk producers whose themes, beliefs, or identities they dislike (West, 2018). In other words, some people deliberately use the platforms’ features to silence minority groups.

Online communities of support sharing among YouTubers discuss self-moderation practices, including editing video metadata to avoid triggering automatic moderation and blocking comments to prevent punishment for hateful audience messages (Ma & Kou, 2021). Moderation also punishes the use of visibility optimization strategies, such as bots and automation software, to perform repetitive tasks (O’Meara, 2019). Some strategies are on the edge of acceptability, like search engine optimization (Primo et al., 2021) and clickbait, which employs intriguing titles to entice clicks (Poell et al., 2022). Equally condemned are “engagement pods,” groups of creators established to “like” and comment on each other’s posts, imitating organic engagement to deceive the algorithm (O’Meara, 2019).

As new strategies emerge, platforms shift their perspectives on what is acceptable. They frequently identify practices that violate their policies as algorithmic manipulation or gaming the system, denounce the authors as morally bankrupt, deviant, and dishonest, and position themselves as impartial parties fighting for authenticity and integrity, according to Petre et al. (2019). SMP employ paternalistic language and fills it with metaphors such as contamination, crime, and cheating to mask their motives and encourage creators to pay for advertisements to gain additional visibility. This exacerbates inequalities between emerging creators and those who can afford advertising to enhance visibility (Petre et al., 2019). As we see, moderation is a disciplinary tool that condemns and penalizes nonconforming actions.

Finally, work management through governance strategies influences the perpetuation of the supply of free labor, and, in this, the creators who succeeded play an active role. They are accountable for spreading the “creativity dispositif” that disciplines and incites creator behaviors and practices, establishes models, norms, and standards, and cultivates expectations of achievement (Duffy & Wissinger, 2017, p. 4464). These internet celebrities spread myths about creative careers by portraying them as fun, free, authentic, viable, and entrepreneurial while hiding negative aspects. These mythologies play an ideological function in the creative economy. Believing that online creative work is easy and potentially profitable, aspiring creators are encouraged to invest time, energy, and resources in exchange for autonomy, excitement, and visibility, thereby contributing to the digital capitalism cycle (Duffy & Wissinger, 2017).

Although most users are unpaid, a successful minority captures the attention of thousands. Champions of data productivity are financially compensated and effectively respond to SMP wishes. Figure 2 illustrates how governance directs workers through the promise of rewards and the threat of punishment. The practices of digital celebrities and their public discourse serve as a model for career aspirants, feeding back into the pool of free workers who meet the organization’s interests while expecting future rewards.

Figure 2
Content Creators’ Behavior in Response to Governance

FINAL CONSIDERATIONS

We built a conceptual framework (Figure 1) portraying SMP as an organizational form of production, management, and work by articulating current studies to bring the main argument of this essay: All phenomena that arise on SMP have an organizational substrate because these platforms manage users’ behaviors, actions, and activities to match the business’ values and goals. Be it social, political, cultural, psychological, or economic, every one of them is a platform-driven phenomenon. Ignoring this overlooks the fact that corporate power, based on its organizational structure, is inextricably linked to the impact these media have on our lives.

Kenney et al. (2021) identify two key aspects of platform power: the artifactual, inherent in software and algorithm, and the contractual, defined by terms of service, guidelines, policies, and instructions. We see artifactual and contractual aspects intertwined in governance strategies to satisfy business needs in two ways:

1. Ensuring self-government without external interference. Platforms have unprecedented autonomy because they lack the accountability and regulation that legacy media companies have and are not responsible for user-generated content or formal employment relations obligations to their core workforce. However, stakeholders’ concerns about criminal and harmful user behavior must be addressed. This is accomplished by establishing rules and prohibitions (regulation strategy) and promising to punish those who break them (moderation strategy). However, harmful content remotion is restricted by economic imperatives that require the use of as much algorithmic moderation or low-cost human moderation as possible, as well as the maintenance of users’ sense of freedom of expression to avoid losing them to more lenient competitors.

2. Increasing data productivity. Platform growth and profitability are driven by user retention, data producer engagement, and advertiser attraction. This is done by improving the assertiveness of the algorithmic recommendation system (curation strategy) and conditioning content creators’ rewards on their metric performance. Curation and analysis of audience data became a parameter for creator decisions, and complying with regulation became mandatory to avoid punishments (moderation).

Platforms manage content creators’ work more explicitly, so we used them as an example. The company’s mission impact them in two ways (Figure 2): the threat of invisibility for violators of regulatory policies and the promise of visibility through algorithmic boosting and adherence to recommended best practices.

Through experimentation, creators learn what curation chooses and develop creative and artifact-specific visibility strategies. Because SMP prohibit certain optimization strategies but require quantifiable performance to reward work, creators prioritize popularity and risk gaming the system. This gives rise to the practices, values, and discourses that shape the new occupation.

As this essay aimed to explain SMP as workspaces and platform-driven phenomena, we suggest that future research examine their dynamics of work management and content creation as a new occupation. In particular, it seems important to analyze their ethos as professionalism, defined as a system of normative values used to organize and control work (Freidson, 2007). Especially relevant is organizational professionalism, an ideal type defined by Julia Evetts (2013) as the management discourse to standardize work procedures and practices, including the definition of goals and performance indicators, to achieve the corporation’s objectives. Therefore, we suggest that future research delves into how invisible work management presents professionalism discourse and how workers negotiate their creative autonomy and identity in response.

• Evaluated through a double-anonymized peer review.
• The Peer Review Report is available at this link.

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Edited by

• Associate Editor:
  Adebukola (Bukky) E. Oyewunmi

Publication Dates

• Publication in this collection
  29 Nov 2024
• Date of issue
  2024

History

• Received
  29 Sept 2023
• Accepted
  28 June 2024