Economizing attention: Markets and barter in video advertising platforms

Abstract

Digital video advertising has become the world's largest platform-economized form of visibility, yet it remains strikingly opaque to viewers and underexamined by social scientists. This paper examines how digital video advertising economies are produced and maintained across platforms such as TikTok, YouTube, Meta, and Netflix. Drawing on a multi-method study, it analyzes how impressions are assembled, stabilized, and monetized within the computational supply chains of digital video. The paper argues that video ad platforms are not mere multi-sided markets but stacked economization processes. At their base lies barter, through which viewers exchange attention, behavioral data, and cognitive labor for access and entertainment. To specify the objects exchanged in these asymmetric relations, the paper introduces the concept of the dyad: paired goods that supply the raw materials of digital video advertising markets. Building on this foundation, marketization processes transform fleeting attention into measurable, comparable, and tradable impressions through technical rules, visibility thresholds, and device-level constraints. The paper concludes that digital video advertising is best understood as a set of stacked-economization platforms organizing contemporary visibility, with significant regulatory and environmental consequences.

Introduction

We have become a video civilization. In the United States, for example, adults now watch on average nearly 4 h of digital video every day (eMarketer, 2024). Video now accounts for more than 80% of global internet traffic (Odefey, 2025), and every moment of watching carries an unseen ecological weight. Watching YouTube for an hour a day produces more than 15 kg of CO₂ per year; consequently, an average US adult annually generates an amount of CO₂ equivalent to the weight of a human body just by watching videos (Koetsier, 2025). What appears as an attention-hungry economy of cultural content creates a heavy environmental load. Behind these tiny video clips stands a vast global advertising industry, of which video forms nearly a quarter: the global advertising market is around $1 trillion, of which digital advertising makes up about 73% (Financial Times, 2024).

Digital video economies operate through a core economic unit: the video impression, a micro-temporal interval in which ads are rendered. Rather than pre-existing commodities, impressions are computationally assembled events produced through distributed infrastructures of encoding, measurement, and delivery. To be exchanged, they must meet conditions of visibility, compete in auctions, and trigger protocols that determine whether a viewer looked, for how long, and under what conditions.

To specify what an impression is in economic terms, the paper advances a conceptual formula for the economization of digital video advertising. A digital video ad is not a pre-existing unit, but an emergent configuration defined by the alignment of viewer, screen, and time, formalized as {V, S, t_0−x}. This shifts analysis away from the assumption of automatically stable commodities to an attention to the micro-temporal and infrastructural conditions through which impressions are produced and made marketable. We make three contributions. First, we conceptualize the impression as a contingent and fleeting economized event. Second, we show that it is generated within a supply chain that combines barter and market. Third, we provide a parsimonious material device, an ad economization formula, for tracing how attention, devices, and time are assembled into tradable visibility. This clarifies how platforms transform unstable human activity into stabilized economic value and grounds our broader argument about stacked economization.

Seen in this light, standard economic analyses struggle to capture the process. Many accounts rely on multi-sided market models (Rochet and Tirole, 2003), but markets are only part of the story. The conditions of possibility for platform markets depend on non-market relations, including barter. We argue that digital platforms are stacked economization processes (Caliskan, MacKenzie and Callon 2025) in which multiple modes coexist. Economization here refers to the intentional design of devices, infrastructures, representations, and agencies that participants recognize as economic (Callon, 2021). In video advertising, market exchange rests on a foundational layer of asymmetrical barter, where viewers exchange attention, data, and behavioral traces for access and relevance. Marketization then stabilizes these fleeting interactions into measurable impressions through protocols, thresholds, and auction systems.

Our theoretical argument is, therefore, that the market in video advertising that platforms construct rests on a foundational layer of barter. In asymmetrical and non-negotiable “barter dyads,” viewers exchange attention, behavioral traces, and data for access, entertainment, and relevance. Only once foundational barter layers generate sufficient material do markets emerge. On top of this foundation, marketization stabilizes unstable micro-temporal events into standardized, measurable units—impressions—through protocols, thresholds, verification systems, and auction architectures. These processes unfold within an integrated economization process shaped by infrastructural limits, protocol governance, and device-level control.

The paper draws on a longitudinal research project on digital advertising, employing a multi-method framework capable of engaging technical advertising architectures, material practices, and economic arrangements. Because no single method can capture the dispersed and opaque nature of digital advertising, we combine interviews, documentary analysis, hands-on experimentation, and close examination of industry discourse. The objective is to reconstruct the socio-technical system through which video and other forms of digital ads are produced, circulated, and monetized.

The core empirical foundation of the study draws on a wide range of materials and observations across the digital advertising ecosystem, including publishers of video and other content, supply-side platforms (SSPs), advertisers, agencies, demand-side platforms (DSPs), as well as engineers, sales teams, and technical specialists. This approach provides access to heterogeneous forms of expertise, from detailed knowledge of ad-serving architectures to organizational practices of coordination, strategy, and constraint. The analysis relies on iterative case reconstruction to identify points of convergence, asymmetry, contradiction, and silence across these materials, treating inconsistencies not as problems to be resolved but as indicators of positionality, including differences in access, professional jurisdiction, and infrastructural visibility.

To deepen and verify these insights, the analysis was systematically cross-checked against a broad documentary archive, including legal filings, expert declarations, API documentation, integration manuals, and technical standards. This was supplemented with continuous analysis of the trade press and observation of virtual and in-person meetings (7 in-person and 12 online conferences; 41 industry events), where shifting standards, controversies, and emergent practices could be observed in real time. Further hands-on experimentation within a system that is fragmented, proprietary, and complex, including technical training, observation of certification processes, and administration of controlled ad campaigns, allowed direct observation of bidding responses and ad-delivery behavior.

In summary, the paper first examines video formats as economization devices, scripting how impressions are produced. Second, it analyzes barter as the foundational economization mode through which attention and behavioral data are extracted. Third, it examines the marketization of impressions through “passiva(c)tion” and “qualculation” (terms defined below), auctions, and maintenance regimes. The paper concludes by arguing that digital video advertising is not simply a media “ad market” but a set of stacked, infrastructural, economic platforms with significant implications for regulation and governance.

Literature review

Imagine a teenager scrolling through YouTube or Instagram. For them, a pre-roll ad is a brief interruption. For the infrastructure behind it, it is the endpoint of a vast near-instantaneous sequence: advertisers bidding via DSPs, exchanges competing, servers fetching media, encoding profiles adapting to bandwidth, verification vendors firing invisible scripts, and models predicting attentional posture … Digital video advertising is the world's largest platform-economized form of visibility—and ironically one of the least visible to viewers and social scientists alike.

Research on online video cultures has shown how creators construct visibility, how algorithms shape circulation, and how users negotiate the pleasures and pressures of watching and being watched (see, e.g. Burgess and Green, 2018). This literature establishes that digital video is not merely a set of technical formats, but a social form structured by norms, expectations, and platform governance. Parallel research on programmatic advertising details how algorithmic bidding, data aggregation, and automated optimization reorganize advertising economies (Wu, 2017; Mellet, 2025; Beauvisage et al., 2024), offering insights into how markets become computational and distributed across devices and cloud infrastructures. Studies of datafication and platform power (Helmond, 2015; van Dijck et al., 2018; Couldry and Mejias, 2019; Rikap, 2021; Van der Vlist and Helmond, 2021).

Video advertising as analyzed here is a form of programmatic digital advertising. Programmatic advertising refers to the automated, data-driven buying, selling, and delivery of ads through computational systems that coordinate real-time auctions, targeting, and optimization across distributed platforms (McGuigan, 2023; MacKenzie and Caliskan, 2026). Unlike earlier advertising models based on negotiated placements, fixed pricing, and relatively stable audience categories, programmatic systems operate at the level of individual impressions, dynamically matching ads to viewers using behavioral data and predictive models. This shift is not only technical but organizational: it transforms advertising into a continuous, infrastructurally mediated process in which valuation, allocation, and delivery are tightly integrated. Digital video advertising represents one of the most complex and resource-intensive forms of this system, given its reliance on latency-sensitive delivery, large data flows, and fine-grained measurement of attention.

Within this broader transformation, a first cluster of studies approaches digital video as a media and platform phenomenon, focusing on streaming, creator labor, and algorithmic distribution (Burgess and Green, 2018; Postigo, 2016; Lotz, 2017). These works illuminate cultural and labor dynamics and show how creators navigate visibility (Bishop, 2019; Cotter, 2019) and how platforms shape cultural production (Nieborg and Poell, 2018). They also demonstrate that content production is organized through hybrid arrangements that combine market and non-market exchanges, including revenue sharing, algorithmic visibility, and forms of speculative or uncertain compensation (Riom, 2023). In this sense, creator–platform relations already entail both barter and market dynamics, as creators exchange labor, data, and content for access, reach, and monetization opportunities. These works open important questions about the economic architectures of ad delivery, measurement, and pricing, particularly how attention becomes materially measurable and tradable as value, which we take up here.

In this article, we focus on a distinct analytical layer: the economization of video advertising that unfolds after content production, where attention is captured, formatted, and assembled into impressions that can be measured and sold. While advertisers are central actors in this process and in some contexts participate in shaping the conditions under which data and attention are generated, our analysis focuses on the stage at which these behavioral materials are transformed into standardized, exchangeable advertising inventory. Bracketing creators allows us to isolate the infrastructural and exchange processes through which behavioral signals are transformed into advertising inventory, while recognizing that creator–platform relations constitute an important adjacent layer of economization that similarly combines barter and market forms.

A second cluster of studies, primarily in marketing and computational sciences, examines digital video advertising from a technical perspective. Frade et al. (2021) provide an integrative review of streaming video advertising literature, and Zhang et al. (2023) survey this field using optimization and data-mining approaches. While these studies acknowledge the dominance of video, they do not analyze the economization processes that make it possible.

Beyond these strands, platform studies offer essential context on algorithmic governance (Gillespie, 2018), platform labor (Duffy, 2017), datafication (Beer, 2019), and cultural intermediation (McFall, 2004), but tend to address video advertising only tangentially. Related work on ad-tech infrastructures (Alaimo et al., 2018; Turow, 2017; McGuigan, 2023) provides important insights into programmatic systems, yet rarely engages with the material specificity of video formats. This scholarship provides rich insights into platforms, culture, and data, but rarely examines video advertising as an economic arrangement in its own right. In particular, we lack accounts of how impressions are standardized, measured, and made tradable, and how non-market and market relations are layered to sustain platform economization.

There is no detailed study of the barter–market nexus in platform economies, despite its centrality. Exchanges such as data-for-access, attention-for-content, and labor-for-visibility remain underexamined as socio-technical processes through which platforms engineer and monetize interaction (Mellet, 2025).

Recent work further underscores how data-intensive platform economies rely on conditions that actively constitute value rather than merely measure it. Zook and Spangler (2023), in their analysis of data broker platforms, show how transparency functions less as a mechanism of accountability than as an enabling condition for data extraction and valorization. By reconstructing the aftermath of the global financial crisis as a “crisis of data,” they demonstrate how calls for transparency reconfigure relations between market actors, producing data as an asset through specific technical, legal, and organizational infrastructures. Their analysis highlights that data are not simply raw inputs awaiting market exchange, but are actively manufactured through economic arrangements that precede pricing and circulation. This perspective aligns with our emphasis on barter exchange by showing how value creation in platform economies depends on upstream socio-technical relations that organize access, visibility, and extraction before data can be marketized and monetizable.

Recent work in platform and data studies on gift, reciprocity, and value in digital economies (Elder-Vass, 2015) reminds us that exchange on platforms takes hybrid forms that weave together market and non-market practices. Most directly, Fourcade and Kluttz (2020) conceptualize platform participation as a “Maussian bargain,” in which users enter structured give-to-get relations that resemble gift exchange rather than market transactions. Their analysis shows how accumulation in digital economies can proceed through asymmetrical but reciprocal data-based exchanges that are neither fully voluntary gifts nor priced exchanges, providing an important foundation for specifying barter as a distinct and organized mode of exchange. At the same time, their focus remains on onboarding within an apparently “free” service and on lateral, gift-like sociality.

Gillian Tett argued that platform services presented as “free” are in fact a large-scale barter system in which users give up their data in exchange for access to maps, search, and social networks (Tett, 2021). Building on this insight, we shift attention to the infrastructural mediation through which these relations are organized, specifically through advertising and the production of impressions. This allows us to show how mediation actively shapes how viewers are rendered, categorized, and dyadically connected not only to content but to ads, and how these relations vary across platforms depending on the organization of ad-serving pipelines.

Extending these lines of inquiry, critical platform studies have also examined the blurring, and at times merging, of production and consumption through the concept of prosumption. Analyzing these dynamics through the lenses of digital labor, exploitation, and value capture, scholars such as Fuchs (2014), Terranova (2000), Ritzer (2015), Andrejevic (2007), Jarrett (2016), and Rikap (2021) show how user activity is transformed into economic value, whether as “free labor,” “prosumer commodities,” or forms of surveilled and infrastructurally organized participation. Across this literature, a central claim is that platforms rely on the continuous production of data, attention, and engagement by users, often framed as participation or play, but structured for extraction, control, and accumulation. Debates within this field further question whether such participation is genuinely empowering or instead masks asymmetrical relations of value capture, with some scholars preferring the term digital labor to foreground these inequalities. Our approach complements this literature by focusing not on labor or value per se, but on the exchange forms that organize these contributions prior to commodification.

Taken together, these perspectives open onto a broader set of concerns about how value is constituted, interpreted, and materialized within platform infrastructures. Complementing this perspective, Stanusch (2025) shows how users actively interpret, contest, and reframe targeted advertising on TikTok through memetic practices, revealing how participation in data-driven exchange is accompanied by shared imaginaries and affective sense-making rather than passive compliance or straightforward market exchange. From a political-economic angle, Bolaño and Zanghelini (2025) question the attribution of value to data itself, arguing instead that data appropriation often constitutes a form of accumulation, sharpening the need to examine the non-monetary exchanges through which data become economically actionable. Finally, Pasek, Vaughan and Starosielski (2023) extend platform analysis beyond valuation to infrastructural and environmental consequences, showing how digital economies depend on relational and material systems whose costs and effects are obscured by conventional accounting. Taken together, these studies reinforce our claim that contemporary platforms rely on structured, non-priced exchanges that precede and condition market transactions, while also underscoring the need for concepts that can distinguish between barter dyads and market commodities rather than collapsing them into a single economic logic.

At the same time, this literature points to the material and environmental costs embedded in these exchanges: data-intensive barter relations are sustained through energy-hungry infrastructures, and extractive supply chains that remain largely invisible when analysis begins only at the level of markets or prices. Attending to barter dyads thus also opens a path for tracing how environmental costs are displaced upstream, folded into non-market relations, and rendered external to formal valuation, even as they are integral to platform-based processes of value creation.

In sum, recent research has generated rich insights into platforms, culture, and the centrality of data, but it has paid scant attention to how video advertising actually operates as an economic arrangement. We know comparatively little about how these markets are organized in practice, how their material and infrastructural conditions are produced, or how non-market and market relations are layered to make platform economization viable. This article addresses that lacuna by bringing economization perspective into dialogue with platform and data studies in one of the fastest-growing and most consequential domains of digital media. In doing so, it foregrounds forms of non-priced exchange, such as barter, that are central to data-intensive value creation yet remain under-theorized in existing accounts of video advertising and platform economies.

Video format as an economization device

A video format is the material device through which a platform organizes when, where, and how an advertisement appears on a screen, including its placement, triggers, timing, and interaction rules. Across digital video advertising, three formats have become dominant. An in-stream video ad is fully embedded within the data stream that generates the content the viewer sees, such as a pre-roll on YouTube, a mid-roll inside a TikTok video, or the ad breaks inside Netflix's ad-supported tier. An out-stream video ad—like the video that suddenly starts playing in the middle of a news article— is digitally added to that stream at the last minute. Connected TV (CTV) ads are those that appear on smart TVs via apps like Netflix, Hulu, or YouTube. Together, these three formats organize nearly all video advertising today, scripting how viewer attention is economized. But how? To explain this, we need to analyze the materiality of a video ad.

A digital video ad is often described “simply” as content with an ad attached (Lobato, 2019). Yet in reality, a video ad is not a mere media file paired with another. What looks like a straightforward attachment is actually the outcome of an extended, multi-agent, energy-intensive, latency-sensitive computational production process. In practice, a digital video ad is not {video + ad} but a composite object produced through encoding pipelines, delivery protocols, auction engines, verification systems, and prediction models. The seamless moment on the viewer's screen is the final output of a rapidly executed industrial supply chain.

Furthermore, video ad manufacturing is governed by protocols such as VAST, which specifies how video ads are requested and delivered, SIMID, which enables secure interactive features, OMID, which standardizes viewability and measurement, and OpenRTB, which structures real-time bidding auctions, all developed and maintained by industry bodies such as the IAB Tech Lab (2023). It is delivered across layered infrastructures that include browsers and apps, player engines, content delivery networks, ad servers, device operating systems, and data centers, each contributing to the rendering, verification, and monetization of impressions. These standards and infrastructures do not merely support advertising delivery; they actively structure how impressions are defined, measured, and made exchangeable within programmatic systems (Alaimo et al., 2018; Paparo, 2025).

The video ad does not simply emerge after simple processes of digital attachment. It is produced in a complex supply chain as the materials used to marketize ads are produced and exchanged with customers, or viewers. At the center of this production lies a deceptively simple economization formula:

Digital Video Ad = {V, S, t_0−x}

Unlike analogue advertising, digital video ads do not exist as stable, pre-given units. They are fleeting, reactive, and valuable only within tightly bounded, personalized intervals of time. Their economization depends on the synchronized presence of three elements: a viewer or viewers (V); a screen capable of rendering the ad (S); and a micro-temporal interval between t_₀ and t_x. Only when {V, S, t_₀−x} align does an impression come into being; if any element drifts—if attention falters, the device changes state, the temporal window ends—the economic object dissolves. In digital video, the commodity is not the ad file but the momentary conjunction of attention, device, and time. Without this triad, there is nothing to sell. Every impression is radically contextual and vanishes the instant attention shifts, the screen updates, or the micro-temporal interval expires.

In its simplest form: viewer × screen × time. A person encounters content on a device and remains present long enough to be measured. This triad is the minimal unit from which all other processes—valuation, segmentation, auctioning, optimization, and reporting—are constructed. Video formats are the devices with which platforms capture, stabilize, and convert this fragile triad into tradable inventory, each doing so according to its own material constraints and delivery architectures.

To empirically describe this in In-stream video, consider what happens when a viewer taps a YouTube video. A skippable pre-roll becomes active because the player timeline has reached a cue point. The player calls a VAST tag, which fetches a markup code (like XML) describing the ad, including skip-offset, companion creatives, tracking events, and interaction options. The platform computes whether a user is eligible to receive an ad—based on device type, network conditions, watch history, predicted completion probability, and brand-safety constraints. Several exchanges respond with bids, each calculated in microseconds. An auction selects the winning ad. Only then do the video file streams begin, and only then do the viewability and completion timers begin. In this moment, the viewer × screen × time triad is sliced into discrete economic intervals: the first 5 s (t₀₋₅ high-value), the next 15 s (t₅₋₂₀ medium-value), and the remainder (t_20−x low-value). The ad's position in the timeline becomes a valuation device with agency—a computational industrial clock for producing the ad as an economized object.

Out-stream video reorganizes the formula yet again. Here, the viewer is not watching one video; they are scrolling many shorter videos in, for example, Instagram feeds. The system waits until a video unit comes into the viewport—often just 50% of its pixels for at least 2 s—to activate a viewable impression. The advertisement is not tied to content; it is tied to the surface. Any page—news article, feed, blog, weather app—can be converted into latent video inventory because the DOM itself (Document Object Model, or the page's structure in live memory) is programmable territory. Autoplay initiates silently, obeying browser-level constraints; viewability thresholds kick in when economization begins; and a brief pause in the user's scrolling produces sufficient “time” to count as attention (note the barter exchange took place between the platform and customer). In out-stream, the device is not a player, but the page, and the economic unit is not watch-time but dwell-time. The page becomes an impression workshop, turning viewer + screen + time into salable surface-attention.

The third format of video, CTV, renders the same triad, but at the scale of a household or group of viewers (sometimes including even unrelated people in, for example, a waiting room: that is, “out-of-home,” in industry parlance). Here, the “viewer” can be plural—the source of endless measurement headaches for practitioner interviewees used to the individualization of web or advertising, although individuals can sometimes be identified if a “device graph” includes both the screen they are watching and their phone. The “screen” can be a 55-inch smart TV, governed not by browser policies but by the OEM's (i.e. the TV manufacturer's) operating system, which determines ad-pod placement, home-screen tile auctions, and pause-ad eligibility. Location is often a living room, the viewer is comfortably seated, “time” becomes long-form: a 42-min episode, two mid-roll clusters, a “pause ad” triggered if someone temporarily leaves the room.

Across all these settings, programmatic video integrates these three formats into a shared economic topology. Auctions unify the disparate materialities of In-stream, Out-stream, and CTV, making their differences commensurable. A mobile pre-roll with a skip button, a scroll-triggered out-stream unit, and a CTV mid-roll stitched server-side are radically different objects from a technical perspective. Yet in auctions, they can appear as comparable bids: a CPM (the cost of showing an ad a thousand times), an attention score, a predicted completion rate. The auction mechanism marketizes heterogeneous devices of attention capture into standardized, exchangeable units. Programmatic infrastructure performs a role crucial to marketization: it makes unlike things alike, long enough for them to be priced.

What looks to the viewer like a brief ad interruption, a clip sliding into view, is in fact the tip of an iceberg, a vast computational production process, an assembly line of economized objects. Yet before any ad can be monetized—before it can enter the world of markets—an entirely invisible layer of barter must take place. Users exchange data for access, attention for entertainment, and viewing labor for platform services. This barter stack is always at work before the market stack in digital video platforms, quietly producing the conditions under which impressions can be priced and sold.

Video advertising can be situated alongside other dominant formats such as search and display, which we analyze in detail elsewhere (MacKenzie and Caliskan, 2026). Across these formats, ads exist as contingent events defined by the alignment of a consumer, a screen, and a moment in time. They differ, however, in how inputs are generated and structured. Search advertising is organized around keywords that capture explicit user intent and are produced through highly dematerialized computational supply chains, while display advertising relies on contextual placement across publisher sites with relatively lighter creative and infrastructural requirements (Coromina et al. 2023, Mellet 2025). Video advertising, by contrast, depends on materially heavier processes, including large file transfers, streaming infrastructures, and extended creative supply chains (MacKenzie and Caliskan, 2026). The barter dyad and stacked economization are therefore not unique to video. They operate across formats, including in search, where data are exchanged for visibility, and in display, where attention is traded for access to content (Caliskan et al., 2025). What distinguishes video is the intensity and visibility of these processes: it amplifies the material, infrastructural, and organizational demands of platform economies, making them especially observable.

Barter as the first economization stack

Digital video economies rest on an often-invisible exchange that must occur before any ad can be monetized. The socio-technical life of impressions begins not with the auction (i.e. the market) but with the user's encounter with the platform. This is the domain of barter—the first layer in the stack of video ad economization—where production and exchange collapse into one another. Platforms depend on user behavior to generate the very ad opportunities they simultaneously sell. At this foundational layer, the basic unit of exchange is a barter dyad: two different valuables paired in an asymmetrical economic exchange process where viewers provide attention, data traces, watch-time, and/or engagement signals in return for access to content. These dyads (data vs. entertainment, attention vs. content, etc.) are embedded in the platform's design. Their exchange is made possible, formatted and scaled by programs whose decisive input is user data couples of platforms’ algorithms. Before any video ad becomes auctionable, platforms must format these behavioral materials so that an “impression” can be constructed. Barter thus precedes marketization: dyads must be paired and their barter is stabilized successfully before economic things can be commodified.

Formalist anthropological accounts challenged the assumption that barter was primitive or economically marginal, showing that it emerged in highly structured social, political, and institutional contexts. Chapman (1980) argued that barter appeared when actors lacked either the institutional means or the desire to use money, and that such transactions depended on pre-existing social relations, shared norms of equivalence, and culturally specific rules of obligation, not price-based calculation. Dalton (1982) similarly emphasized that barter was rarely a simple spot exchange; it was embedded in broader systems of hierarchy, reciprocity, and constraint, often occurring between strangers, across group boundaries, or in settings where credit and trust were limited.

Critiquing Dalton and Chapman's “formalist” accounts a decade later, Humphrey and Hugh-Jones (1992) emphasized that barter depends on negotiated equivalence without a general measure of value, making it fragile and context-specific, not universal and formal. Hart (1988) noted that barter persists among, for example, households and small firms in today's economies, although he argues that it remains peripheral because it requires face-to-face negotiation, shared expectations, and situation-specific trust. Zelizer (1994) offers an implicit critique of the assumption that exchange without money is simple: even intimate or informal barter involves boundary work and moral evaluation. Despite these contributions, however, barter is rarely a core analytic object of contemporary social research. Barter is understood either as limited and exceptional, occurring, for example, where money is absent, or as “thinly relational”: a one-off negotiation between parties without obligations.

These limitations leave a gap for understanding platform economies, where barter is continuous, infrastructurally enforced, and central to value creation. Platforms must actively construct equivalence between heterogeneous valuables through interfaces, thresholds, and predictive systems. To address this gap, we introduce the concept of the barter dyad. The dyad refers to the paired set of two heterogeneous, non-priced valuables that are exchanged in a barter relation. The dyad is not the relation itself, but its object-form: it is to barter what the commodity is to market exchange or the gift is to gift exchange. In platforms, these valuables are not held by whole actors but are co-produced and paired within infrastructures. They consist of fragments such as attention, behavioral traces, and watch time on one side, and content, access, and relevance on the other. The dyad thus names the unit through which barter is enacted, making visible how platforms extract, format, and couple dividualized signals into exchangeable forms that can later be stabilized and marketized.

Seen in practice, dyads organize economic participation across platforms. On TikTok, a labor–entertainment dyad emerges when a user lingers on a short video, as micro-temporal behaviors such as pausing or rewatching generate signals that feed algorithmic circulation while the platform returns content and relevance (Bhandari and Bimo, 2022; Maris et al., 2024). On YouTube, a data–entertainment dyad takes shape as watch duration, skips, and hover signals are recorded and translated into personalized recommendations (Banerjee and Pal, 2021). On Facebook Reels, a device–computation dyad is activated as the phone renders auto-play videos, exchanging energy and memory for platform use. On CTV, a household attention–visibility dyad forms as aggregated viewing behavior is exchanged for access to long-form content. Across these cases, dyads make visible how platforms organize barter through the continuous pairing of behavioral fragments with infrastructural outputs.

Dyads are not commodities: they are not necessarily fungible or priced, yet economically valued and exchanged. They are co-produced within architectures that platforms design and maintain, and their terms cannot normally be negotiated by users. A viewer encountering a dyad cannot change the terms of barter, but they can refuse the barter itself by not continuing to watch, thus dismantling the economization formula. When the V of {V, S, t_0−x} steps back, the economization fails.

These dyads structure what we call “prodexchange,” the defining logic of digital video: every user gesture is simultaneously consumption, production, and exchange, processed in the supply chain we are describing. TikTok's recommendation engine produces the next watchable sequence by predicting monetizable engagement from the viewer's last swipe. YouTube's encoding profiles are tuned to reduce buffering to protect the ad-stitching pipeline. Facebook's video player is both a rendering device and a pricing instrument, firing skip-event APIs, viewability timers, and attention signals that determine whether the impression will enter the auction. Even Netflix's emerging ad-supported tier now embeds tracking intervals into long-form content to prepare mid-roll “pods” (groups of ad impressions) for household-level targeting. In digital video, the viewer cannot simply watch; the act of watching generates future prediction, future ranking, and ultimately future auctionability. Prodexchange is this fusion, in which each viewing gesture produces the very object that will later be exchanged in the ad market.

Barter is complex and depends on an acceptable level of commensuration. If watching a cat video required sitting through a 5-min cat-food ad, the viewer would most likely reject the exchange; if it is only 5 s, they may accept it. There is, therefore, an implicit economic calculation of the non-monetary cost of barter to the viewer. Yet entertainment and behavioral data are not easily comparable, so platforms must actively construct their equivalence. TikTok attracts attention by making videos extremely short, transforming micro-attention into a payable unit that can be bartered instantly. YouTube's 5-s skip window defines the minimum attention cost for pre-roll access, making the exchange predictable and tolerable. Meta's out-stream ads trigger only when a video enters the viewport, ensuring users are charged attention only when necessary. Netflix uses long-form formats to extract extended durations of household viewing, converting 30- or 60-min segments into stable barter intervals for CTV ad pods. Across these platforms, commensuration is achieved through interface design, temporal rules, autoplay constraints, and thresholds that determine when the dyad is complete.

These processes of commensuration also point to a further feature of barter that is often overlooked: it does not require explicit recognition by those who participate in it. Barter can operate across a spectrum of awareness. Classic ethnographic accounts show that barter does not necessarily depend on mutual understanding, transparency, or even shared language. Practices such as silent trade and intergroup exchange demonstrate that actors can engage in barter without fully recognizing the terms of exchange or the identity of their counterpart (Humphrey, 1985). This insight is crucial for platform economies. In digital video environments, viewers may not explicitly recognize their participation in barter, as the exchange is embedded in interfaces, timing rules, and background processes. The dyad is enacted without being named. This opacity does not weaken the exchange; rather, it allows barter to be infrastructurally enforced while remaining experientially subtle. At the same time, its stability depends on the limits of tolerance. When the perceived terms of exchange shift, for example, when the duration or intrusiveness of compulsory ad exposure exceeds what viewers accept, the barter relation can weaken or collapse. Barter in platform settings is therefore not only structured but also continuously calibrated, operating within shifting thresholds that define its viability.

Barter is also mediated by qualculative agencies that judge whether the exchange has occurred sufficiently to proceed to marketization: “qualculative” action is simultaneously qualitative classification and quantitative measurement (Cochoy, 2002). TikTok's skip-prediction models determine whether a user is likely to tolerate a future ad, thereby influencing where and when the platform inserts breaks. YouTube's viewability engine assesses whether half the pixels remained in view for at least 2 s, translating this into an economic “enoughness.” Netflix's “household graphs” identify how multiple viewers in a living room barter their joint attention to long-form content. Meta's brand-safety classifiers evaluate whether particular content is “safe” enough to trade attention for ads. These agencies never merely measure activity; they decide whether a dyad has achieved sufficient value to produce an impression.

Barter is enacted in specific encounters that platforms design. On YouTube, the pre-roll moment is high-stakes barter: the viewer must provide at least apparent attention before accessing desired content. TikTok's infinite scroll transforms each swipe into a micro-barter in which attention is exchanged for relevance. Facebook's out-stream videos erupt between paragraphs, turning reading space into bartered visibility. Netflix's pause ads convert the act of pausing—a moment of user departure—into an opportunity for barter. CTV mid-roll breaks are placed at narrative tension points, encouraging viewers to remain seated and complete the barter. These encounters are architected with precision, not mere interruptions; they are designed settings through which dyads become actionable—the barter mode of economization.

Barter valuation determines when attention or behavior becomes “enough” to move the impression into the ad market. TikTok may treat a 2-s linger as a complete barter; YouTube treats full views, partial views, and skips differently; Facebook counts a view only when 1 s of video has been watched; Netflix evaluates commercial breaks by household-level watch continuity. Because these bartered goods are completely demarketized, their valuation must be constructed by thresholds, sensors, logs, and predictive models that convert micro-attention into a barterable input. Barter valuation, much like market valuation, is always contingent, always measured through devices, and always shaped by platform incentives.

The barter exchange system also requires continual maintenance. YouTube must update VAST and SIMID specifications, maintain skip-button logic, and tune video-player engines to support SSAI (“supply-side ad insertion”). TikTok must ensure scroll-trigger scripts fire reliably and that its recommender systems continue to produce watchable sequences. Facebook must keep out-stream rendering scripts compatible with browser autoplay policies. CTV platforms must sustain consistent ad-stitching so that mid-rolls appear seamlessly. Without constant technical, policy, and interface maintenance, the barter relationship collapses, and video ad impressions cannot be produced.

Finally, barter is enacted through a series of economic devices: skip buttons, autoplay engines, scroll-trigger APIs, mute-on-load constraints, rewarded-video interfaces, attention timers, household identity graphs, VAST tags, SIMID sandboxes, CSAI/SSAI architectures. These are not decorative user interface elements; they are devices with agency that structure the dyad, regulate the exchange, and prepare the resulting attention-data object for marketization. On Netflix, even the act of selecting a show initiates a sequence of device-level signals that stabilize future ad opportunities. On TikTok, the pause before a swipe becomes a device-level event used to construct monetizable predictions. On YouTube, the skip button is an extraction device, converting an unavoidable 5 s into a calculable, auctionable unit.

Across TikTok, YouTube, Meta, Netflix, and CTV ecosystems, barter emerges not as a marginal feature but as the primary mechanism through which video ad economies begin. Before the market stack can operate—before auctions, prices, or budgets enter—the barter stack must convert interactions into dyadic exchanges. Attention becomes data; data becomes prediction; prediction becomes valuation; valuation becomes auction; auction becomes revenue; revenue becomes platform power. Digital video economies rest on dyads that constitute the precondition for commodification and, ultimately, marketization. They are the foundation on which ad economization is built.

Marketization as second economization stack

Digital video advertising is often presented as if markets simply “exist” around it: buyers on one side, sellers on the other, and auctions clearing impressions in real time. Yet, as our broader framework insists, markets do not stand ready-made. They must be built, stabilized, and continually repaired. Before prices can form, before bids can be submitted, and before an impression can be sold, something must be made marketable. In digital video, that “something” is not the video file, not the creative ad, nor the viewer's attention in an abstract sense. Materially, it is the impression—a micro-temporal, device-specific, behaviorally contingent value that must first be commodified, then made comparable, and only afterward fed into the process of marketization.

Marketization begins with passiva(c)tion: the transformation of heterogeneous, unstable phenomena into objects—still active, but domesticated, so to speak—that can circulate in markets (Callon, Caliskan and MacKenzie, forthcoming). Video impressions are among the most unstable economic goods ever produced. They may last milliseconds; depend on motion, sound, and scroll position; vary by device, bandwidth, and user gesture; and may vanish before they are economized. They require extensive work before they become commodities. They must be passiv(a)ctivated into measurable, commensurable units; qualified, indexed, and calculated by human and non-human agencies; staged within market encounters that platforms design; priced through multi-layered bidding architectures; maintained through standards, repair work, and governance; and enabled by a dense ecology of devices.

Platforms accomplish this through a suite of formatting rules. The 6-s bumper, 15-s non-skippable, and 20-s standard pre-roll are not mere cultural norms: they are market units. Viewability rules translate a fleeting phenomenon into a stable commodity spec. For example, “skip windows” on YouTube create a standardized minimum unit of compulsory attention, passivactivating visibility as a marketable form of attention. Out-stream video adds additional layers: impressions count only once a video enters the viewport, often accompanied by scroll-trigger thresholds that define the minimal amount of human movement required to generate a saleable unit. In CTV, standardization emerges through ad pod lengths, break structures, and co-viewing assumptions that convert household time into uniform blocks of inventory. Through these formatting rules and thresholds, platforms perform the core act of marketization: turning unstable micro-temporal experiences into countable, comparable, purchasable goods.

Once video impressions have been formatted and thus passivactivated, they must be judged, evaluated, and classified. Marketization also depends on qualculation: the intertwined work of characterization and calculation (e.g. of value) through heterogeneous agencies. In digital video, these agencies include humans (advertisers, publishers, media buyers), organizations (DSPs, SSPs, verification firms), and an array of computational systems (viewability models, brand-safety classifiers, attention predictors).

DSPs qualify impressions by deciding whether they meet the advertiser's goals. SSPs qualify by filtering for deal-specific rules, brand safety, and “invalid” (e.g. fraudulent) traffic, although this last form of filtering is not always as rigorous as it might be. Viewability vendors (such as DoubleVerify) apply their own measurement models, sometimes contradicting platform-native viewpoints. Netflix's ad-supported tier qualifies household-level segments using co-viewing models and account-behavior clustering, while TikTok's ranking engine qualifies user micro-actions (rewatches, pauses, completions) as indicators of future monetizable attention.

Here, viewers are treated as Deleuzian dividuals (Cluley and Brown, 2015)—bundles of behavioral fragments distributed across devices and sessions. A “viewer” on YouTube is partitioned into watch-time segments, click sequences, device types, and skip probabilities. On Meta, the same user is decomposed into scroll velocity, dwell time, and interaction residue. CTV platforms qualify households through device graphs and inferred demographic clusters. Marketization is impossible without these qualculative agencies. They do not merely observe value; they help produce it.

Markets require encounters—moments in which buyers can meet goods under conditions engineered to make exchange possible. In digital video, encounters are tightly designed architectures. On YouTube, encounters occur at precise cue points: pre-roll, mid-roll, and end-roll insertions, each chosen by algorithms optimizing predicted user tolerance and ad-yield. TikTok organizes encounters through continuous swiping: every new clip is an encounter opportunity triggered by user gesture.

In CTV environments, encounters are shaped with even more precision. Ads are structured into pods; break positions are negotiated among multiple actors; and streaming apps enforce rigid pod structures regulated by device-level governance (e.g. Roku's operating system rules). Pause ads introduce encounters triggered not by narrative structure but by turning domestic gestures (getting a glass of water) into economic events. Market encounters are therefore engineered points of contact: timestamps, gesture triggers, viewport crossings, pod structures, and inactivity signals. They are the sites where passivated impressions become available for bidding.

Once impressions have been formatted, qualified, and staged within encounters, prices must be realized. In digital video, price realization is a multilayered process involving real-time bidding, pacing algorithms, soft floors, bid shading, and post-auction attribution. Most premium video now trades via first-price auctions, though soft floors discreetly enforce minimum prices. DSPs employ bid-shading models to avoid overpaying, while SSPs use dynamic flooring to maximize revenue. Out-stream video ads introduce additional complexity: milliseconds of exposure can trigger multiple auctions as the scroll position fluctuates.

CTV platforms layer even more pricing mechanisms. Programmatic guaranteed deals fix inventory at pre-negotiated CPMs, while private marketplaces (PMPs) allow preferred buyers to access premium pods. Netflix and Amazon Freevee integrate dynamic pricing based on household-type segmentation and time-of-day patterns. In many cases, the final price a buyer pays is the output of several nested calculations: auction clearing price + pacing adjustments + frequency caps + attribution rules. Price realization is therefore not a single moment but a distributed process, enacted across multiple systems whose outputs must be aligned for a transaction to count as revenue.

Markets do not run themselves. They require ongoing design, maintenance, and repair. Digital video ads depend on a heavy infrastructure that must be continually updated: CDNs, encoding farms, ad servers, identity graphs, measurement scripts, and fraud filters. Standard-setting bodies update VAST, SIMID, and OMID specifications, which platforms must implement and publishers must test. Player engines require constant maintenance to ensure skip events fire correctly, quartile beacons are sent, and mute states are captured. SSAI systems must keep ad stitching seamless to avoid user churn. Fraud detection must adapt to new forms of invalid traffic—CTV spoofing, out-stream misrepresentation, and viewability laundering.

The maintenance is endless: operating system updates break measurement scripts; app redesigns require re-certification; new creative formats require new validations; privacy rules require rewriting entire components of identity resolution. Markets function only because hundreds of maintenance teams across platforms and intermediaries keep repairing the conditions that allow impressions to be produced and monetized.

Finally, digital video ad markets are constituted and operated by devices—technical, organizational, and cognitive instruments that enable, shape, and sometimes distort market relations. VAST tags specify how ads should load, track, and report. SIMID provides the sandbox that enables interactive ads while restricting what they can access. OMID verifies that an impression was actually viewable. OpenRTB defines the grammar of bidding. Header bidding wrappers enable parallel auctions, redistributing power from platforms to publishers—or, in CTV, provoking new tensions as device manufacturers enforce their own rules.

On Netflix or Hulu, ad servers orchestrate the compatibility between creative requirements, pod structures, and user segments. TikTok's machine-learning recommendation engine acts as a market device that shapes both the supply of attention and the likelihood of future monetization. YouTube's player user interface—skip buttons, mute icons, double-tap gestures—functions as a hybrid device that both delivers content and produces data for future pricing.

In digital video advertising, market devices are agentic: they determine what is counted, measured, and valued, and in doing so constitute the market itself. Video impressions do not precede exchange; they are produced as marketable objects through formatting rules, qualculative operations, encounter architectures, and pricing systems. Through this socio-technical work, impressions become commodities that can be priced, traded, and optimized within the digital advertising infrastructure.

Conclusion

Digital video advertising cannot be understood as a multi-sided market, nor are platforms passive connectors between advertisers and audiences. They are stacked economization processes in which barter and marketization operate simultaneously. A viewer's ordinary act of opening TikTok, scrolling a Meta feed, or watching an ad-supported Netflix show triggers a dense sequence of computational and economic operations that turn gestures, pauses, and glances into tradable visibility.

Barter sits at the base of this stack. Before an ad can appear as a commodity, it must be produced through dyadic barter exchanges in which viewers give attention, behavioral residue, cognitive labor, and identity fragments in return for access, entertainment, or relevance. These dyads are not priced or negotiated, but they generate the behavioral materials from which platforms subsequently operate markets. Barter relations are not a leftover form of coordination from pre-modern times—they are platform economies’ generative layers and structural conditions of possibility for market exchange that funds today's technology companies.

Marketization begins only after this barter stack has accumulated behavioral material. Impressions do not preexist; they are constructed by stabilizing fleeting human behavior into standardized, measurable units via thresholds, timing rules, interface constraints, and formatting conventions. Skippability windows, autoplay parameters, and viewability thresholds are not mere design details but material political choices that define what counts as an impression and what advertisers must pay for. Through these mechanisms, platforms convert volatile attention into stable inventory that can circulate through auctions, pricing models, and reporting systems. Passiva(c)tion—stabilizing unstable behavior—makes marketization possible.

These dynamics unfold within a material political economy structured by infrastructures that define what platforms must, can, and should do. YouTube must compress and deliver millions of videos across global CDNs. TikTok must extract micro-signals—hover-time, repeats, swipes—to feed its recommendation engine. Netflix's ad tier must coordinate ad pods across heterogeneous devices and household contexts. At the same time, platforms can leverage device-level affordances—remote control inputs, buffering states, pause events—to detect engagement and trigger additional operations. Platform practices emerge from negotiations over standards, browser governance, advertiser demands, and regulatory pressures. Non-skippable caps, mute-on-load rules, frequency limits, and viewability requirements are political compromises encoded into infrastructure rather than neutral engineering solutions.

Every impression requires instantaneous orchestration across real-time bidding engines, verification scripts, encoding farms, device operating systems, and distributed storage networks. Every digital ad produces a small “puff of CO_₂” as servers negotiate, compute, log, and deliver content. Video multiplies this load dramatically: a single 30-s CTV ad can involve dozens of auctions, hundreds of log events, contributions from multiple CDNs, and several predictive models assessing identity, engagement probability, and brand-safety constraints. This is part of why an adult viewer may generate annual emissions comparable to their body weight.

Viewed together, these layers show how the concept of “stacked economization” clarifies the production of digital video advertising. A video ad is not “delivered”; it is bartered into existence, stabilized by market devices, governed by infrastructural politics, and sustained by planetary-scale computation. This framework reveals how infrastructures both enable and constrain extraction, grounding digital advertising in the material realities of energy, computation, and global logistics. Digital video advertising is not only the largest visibility market in history—it is a multi-layered industrial formation that produces, organizes, and governs contemporary attention.

This analysis also exposed a conceptual oversight in the social sciences: barter is not external to markets but foundational to them in platform economies. Attention, data, and behavioral traces are co-produced with content and constitute the conditions under which market exchange becomes possible. Recognizing this requires a theoretical expansion. Classical frameworks illuminate price formation and commodification but do not account for the computational, infrastructural, and asymmetric barters that make possible contemporary digital experience. We lack conceptual language for the objects exchanged in these interactions. The dyad—paired behavioral materials co-produced through platform architectures—names these and renders them analytically visible.

This recognition also exposes a regulatory blind spot. Market regulation begins where prices appear; barter sits outside its field of view. As a result, platforms operate vast barter economies in which the public continuously provides attention, data, and cognitive labor while receiving limited or uneven returns. Barter becomes a mode of economization without compensation—invisible private taxation that underwrites platform revenue. If regulation is to become effective, it must expand to treat barter as an economic, and thus publicly taxable event, one that generates obligations, allocates responsibilities, and demands democratic oversight.

Finally, digital video advertising calls for further research through the lens of ecologization. Every economic activity depends on ecological conditions of possibility, and video is among the most resource-intensive forms of digital life. Each second watched activates computational supply chains across data centers, CDNs, ad servers, and machine-learning architectures (Pasek, 2019). As artificial intelligence becomes more deeply embedded in video production, targeting, and delivery, these infrastructures are likely to expand further. While this article has only begun to outline these dynamics, more systematic empirical and theoretical work is needed to understand how ecological costs are generated, distributed, and governed within platform-based video economies, and to establish ecologization as a central analytic and political concern (Callon, Caliskan and MacKenzie, 2025a, 2025b).

Taken together, the argument advanced here is that the marketization of digital video ads is inseparable from barter, dependent on market devices and infrastructures, and embedded within material political economies. To study video advertising is to study the contemporary organization of visibility and economic value that funds today's internet. Barter is its foundation; marketization its apparatus; ecological collapse its horizon. The open question is whether our social-scientific and regulatory tools can evolve fast enough to govern systems whose consequences accelerate with every act of attention—at a moment when mass attention to video has become one of the forces driving planetary decay.