Selected Papers of #AoIR2024: The 25th Annual Conference of the Association of Internet Researchers Sheffield, UK / 30 Oct - 2 Nov 2024 Suggested Citation (APA): Jokubauskaitė, E., & Peeters, S. (2024). Visibility in the shadows: Tips in mainstream vs. niche streaming on Chaturbate. Paper presented at AoIR2024: The 25th Annual Conference of the Association of Internet Researchers. Sheffield, UK: AoIR. Retrieved from http://spir.aoir.org. VISIBILITY IN THE SHADOWS: TIPS IN MAINSTREAM VS. NICHE STREAMING ON CHATURBATE Emilija Jokubauskaitė University of Amsterdam Stijn Peeters University of Amsterdam Webcam sex platforms have grown into a multi-billion industry over the past few decades and host large populations of performers. Succeeding on these platforms is often framed in terms of appearing higher in the algorithmically ranked performance list on their homepage (Jones, 2015; van Doorn & Velthuis, 2018; Velthuis & van Doorn, 2020; Jokubauskaitė et al., 2023). This visibility correlates with attracting substantial viewer numbers, in turn increasing the potential for tips. Performers, however, frequently claim that due to the prevalence of freeloading, more viable income strategies revolve around cultivating a smaller but loyal customer base, commonly called 'regulars'. Streaming to a niche, therefore, is a recognized approach among webcam performers, often advised to beginners as a way to “stand out and build a dedicated fan base” (Sah, 2024). This suggests that there is more to financial success on these platforms than ‘ranking higher’, and that it can manifest in multiple forms. From the platform’s perspective, the algorithmic management of creators’ visibility is embedded in a large non-monopoly market (Jokubauskaitė et al., 2023), with numerous sites competing for limited traffic. Various platform affordances, such as the algorithmic ranking system, tag and categorization systems, whitelabel sites, and other affiliate program elements serve to maximize both traffic to the platform and potential spending by viewers (of which the platform receives a percentage). For performers, though, they afford alternative modes of visibility, which may generate tips beyond the top of the front page of the platform. Nevertheless, little is known about the concrete earnings of webcam sex streamers in relation to both homepage ranking and other forms of visibility. This paper focuses on Chaturbate, one of the highest-traffic and largest- performer-base webcam sex platforms, examining the income of performers on the platform as related to modes of visibility, reliance on regulars, and the size and frequency of incoming tips. Previous research has underscored the opacity of algorithmic ranking systems in webcamming and the fiercely competitive environment they foster. For example, Velthuis and van Doorn (2020) assert that these systems are “constitutive of competition” (p. 168) and transform “the world of webcamming into a winner-take-all world” (p. 176). They further argue that “the algorithm is a strategic tool in inter-platform competition” (ibid.), with its opacity serving as a safeguard against performers attempting to 'game' the system. Despite the opaqueness of these algorithmic ranking systems, some patterns have been observed regarding their outcomes. Angela Jones (2015) found that “black and Hispanic performers have disproportionately lower camscores” (p. 789) on Myfreecams. Similarly, Lorena Caminhas (2022) documented that “rankings rely on axes of difference, centrally gender, race, and age, foregrounding young white cisgender women” (p. 1) in the local webcam industry in Brazil. Furthermore, Jokubauskaitė et al. (2023) empirically scrutinized the outcomes of ranking systems of five webcam sex platforms. They note that Chaturbate, the object of our study, hosts a high-risk, high-reward competitive environment, where a select group of high-visibility performers had significantly greater viewership of their shows compared to less visible counterparts. Nonetheless, mainstream visibility is not the only successful income strategy, taken into account that online sex workers are known to resist platform affordances (Rand & Stegeman, 2023) and use various strategies to earn money in a highly competitive environment. Large-scale studies focusing on ranking alone, therefore, are necessarily limited. Furthermore, even though some data about performer earnings has been reported in ethnographic studies (e.g. Jones, 2020), and anecdotal evidence has been presented in news media (e.g. Isador, 2019) and industry blogs (e.g. Graham, 2023), previous research does not directly connect visibility metrics with earnings. Additionally, income data has not been collected systematically at a larger scale before. We thus focus our inquiry on earnings from tips collected on Chaturbate and their relationship to visibility beyond the front page of the platform, made available via various technical affordances such as whitelabels, tags, or gender labels. Our systematic, large-scale data analysis is grounded in an array of performance metrics, including ranking, tip, viewership, tags, and other data collected from public streams via a custom scraper on Chaturbate over a two-week period in July 2022. We explore the distribution of earnings from tips and analyze their correlations with ranking on the front page, and show viewership. We then triangulate the findings via a co- donation network with gender-label and tag data to delineate apparent niches that performers stream in. Doing so, we interrogate the algorithmic visibility management on the platform and its consequences for performers’ income from tips, as well as different ways performers succeed financially on the platform. The analysis helps untangle the complex and opaque socio-technical conditions that webcam performers operate in. However, our case study does not come without ethical concerns, especially because of the continuous stigmatization and marginalization of the sex worker community. We are particularly aware of concerns related to automated online data collection. Nevertheless, we believe that a comprehensive analysis into the functioning of powerful platforms can bring beneficial outcomes to worker communities if conducted with an 'ethic of care' (Tronto 1998). While ethnographic studies of worker experiences are indispensable, they alone may not suffice to counterbalance the hegemonic influence wielded by large platforms through "sexual datafication" (Saunders, 2020, p. 58). Our research followed a strict ethics protocol, continually reassessing the potential risks of harm throughout the process. No visual data was collected, and only aggregated findings are presented without any identifying information. Besides scrutinizing the algorithmic management of Chaturbate, the paper offers insight into the scale and distribution of performer earnings along the lines of different strategies for generating tips. This can give actionable information to performers without requiring marginalized workers to perform “intellectual, practical, or emotional labor” (Phipps, 2015). We also estimate the earnings of a platform within a highly secretive industry, which has not been independently or systematically done previously. Three preliminary findings emerge: firstly, we find a pronounced winners-take-all distribution of tips on Chaturbate, with the top 10 percent of earners collecting more than 69% of all tips. These tips strongly correlate with show viewership and homepage ranking. Secondly, we identify instances where performers, despite not attaining high rankings, still accumulate substantial earnings, suggesting viable paths to sustainable income beyond seeking front-page visibility. Thirdly, we uncover niche-visibility areas linked to gender labels and specific tags. While some performers in these niches earn a significant income from tips, their audiences tend to be smaller and more often consist mainly of loyal customers, who tip generous sums of money, otherwise known as “whales”. Our findings reinforce previous academic observations concerning the competitive environment in webcam sex as well as creator industries at large. Yet, diverging from the focus on mainstream visibility in prior work, we discern various income-generation strategies performers employ when subjected to the algorithmic rule of the “engines of anxiety” (Espeland et al., 2016). The alternative modes of visibility afforded by the platform provide ways for more performers to monetize their content, and for the platform to receive niche traffic. However, the strong income reliance on whale tippers within more niche areas of content underscores the financial precarity in the industry – a performer remains dependent, either on the algorithmic ranking system to consistently bring in a large audience, or on a select few loyal fans for regular donations. Notes The design of this study was reviewed and approved by the Ethics Review Board of the University of Amsterdam, Faculty of Social and Behavioral Sciences, project reference 2021-AISSR-13818. References Caminhas, L. (2022). The politics of algorithmic rank systems in the Brazilian erotic webcam industry. Porn Studies, 0(0), 1–17. https://doi.org/10.1080/23268743.2022.2083661 Espeland, W. N., Sauder, M., & Espeland, W. (2016). Engines of Anxiety: Academic Rankings, Reputation, and Accountability (1st edition). 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