How do digital platforms govern their users? Existing studies, with their focus on impersonal and procedural modes of governance, have largely neglected to examine the human labor through which platform companies attempt to elicit the consent of their users. This study describes the relationship labor that is systematically excised from many platforms’ accounts of what they do and missing from much of the scholarship on platform governance. Relationship labor is carried out by agents of platform companies who engage in interpersonal communications with a platform’s users in an effort to align diverse users’ activities and preferences with the company’s interests. The authors draw on ethnographic research conducted at AllDone (a for-profit startup that built an online market for local services) and edX (a non-profit startup that partnered with institutions to offer Massive Open Online Courses). The findings leverage variation in organizational contexts to elaborate the common practices and divergent strategies of relationship labor deployed by each platform. Both platforms relied on relationship workers to engage in account management practices aimed at addressing the particular concerns of individual users through interpersonal communications. Relationship workers in each setting also engaged in community management practices that facilitated contact and collaboration among users in pursuit of shared goals. However, our findings show that the relative frequency of relationship workers’ use of account management and community management practices varies with organizational conditions. This difference in strategies also corresponded to different ways of valuing relationship workers and incorporating them into organizational processes. The article demonstrates how variation in organizational context accounts for divergent strategies for governing user participation in digital platforms and for the particular processes through which governance is accomplished and contested.
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Some scholars use the term “platform governance” to refer to the governance of platform companies by users, governments, laws, and regulations. Here we are primarily concerned with the governance of users by platforms (Gorwa 2019).
The names of the company and associated individuals have been changed.
In the software industry, the term “user” is typically applied to a broad range of parties who may engage with the same platform in different ways (Agre 1995; McKay et al. 2000; Eisenmann, et al. 2009). For example, ordinary people, organizations, and advertisers can all be “users” of social media platforms like Facebook; both passengers and drivers are “users” of ride-hailing platforms like Uber; and restaurants, drivers, and diners are all “users” of food-delivery platforms like Grubhub.
Platform scholars who share this broader view of governance (e.g., Fish et al. 2011; Kelty et al. 2015) have neither identified nor discussed relationship labor, perhaps because they have primarily endeavored to build general theories and typologies of participation rather than systematically investigating how governance processes are implemented within concrete social settings.
We distinguish relationship labor from two associated, but distinctly different, terms. Like “relational work” (Zelizer 2005; Bandelj 2012, 2015), relationship labor draws attention to how economic transactions are imbricated in social relations. But rather than focusing on “the effort by which people try to find appropriate matches between social relations, economic transactions, and media of exchange” (Bandelj 2015, pp. 227–228), relationship labor is concerned with how employees aid and persuade platform users. Like “relational labor” (Baym 2015, p. 16), relationship labor “is meant to emphasize effort that goes beyond managing others’ feelings in single encounters ... to creating and maintaining ongoing connections.” However, unlike the relational labor exhibited by musicians as they cultivate audiences to enhance their income-earning potential, relationship labor is wage-labor that does not require workers to blur the boundaries between professional and personal ties; moreover, the value generated by relationship workers is appropriated by the companies that employ them. Additionally, relationship workers cultivate online communities not only to build customer loyalty, but also to encourage community members to collaborate in ways that will serve the interests of the platform company.
Others have commented on the uses and misuses of the term “community” to describe those who participate in digital platforms (Postill 2008; Fish et al. 2011). Tech companies often deploy the word in ways that elide differences in power, interests, and opinions among and between platform companies and users. (Note, for example, the multiple uses of the term “community” in Zuckerberg 2017). Like other critics, our use of the term acknowledges that inequalities exist even among members of self-described online “communities.”
Relationship labor can be glimpsed in emerging studies of digital labor platforms. Some freelancing platforms employ workers who post to online discussion boards frequented by users to provide advice or forecast upcoming changes to the software (Rahman 2019; Gerber and Krzywdzinski 2019). On one on-demand delivery platform, managers call couriers to enforce scheduling policies (Attwood-Charles 2019). However, researchers have yet to systematically investigate how platform companies organize relationship labor, or the interactional practices and strategies that they use to manage their user populations.
Prior studies employ content analyses of the rhetoric deployed by platform companies (Gillespie 2010) and of users’ social media posts pertaining to governance disputes (Crawford and Gillespie 2016); examinations of user interfaces and their implications for platforms’ control over user activities (Helmond 2015; Rosenblat and Stark 2016); and observations and interviews that surface users’ and managers’ opinions and experiences of platform governance (Bucher 2013; Rosenblat and Stark 2016; Gerber and Krzywdzinski 2019).
The first author gained access to the field site through a friend who had attended high school with one of AllDone’s co-founders. The first author told the co-founder that he was interested in studying everyday life inside a tech startup by working alongside members of the organization. Upon being granted access, he informed colleagues of his dual role as both a researcher and participant. The first author engaged in a variety of mental activities – including contemporaneously reviewing and analyzing each day’s fieldnotes – to maintain a degree of “professional distance” essential to generating insights from data (Anteby 2013). Although he was deeply involved in the field site, the first author did not generate the phenomena described in this article: the company’s account management procedures were already in place when the first author began to work with AllDone’s phone support agents, and its community management activities were implemented by a colleague working in a different department. See Appendix B of Shestakofsky (2017) for further details pertaining to the author’s data-gathering procedures and analytic strategy.
Because the second author’s role in the field involved a lesser degree of participation than the first author’s, his access to managers’ deliberations about platform strategy was more limited. However, the breadth of the second author’s access (both inside of edX and among various users of the platform across four institutions) provided ample opportunities to observe the company’s governance practices.
Managers would sporadically ask email support agents to tally incoming messages pertaining to particular product features, though in practice execution could be haphazard; product designers would occasionally recruit a handful of user testers to gather feedback on potential features and to learn more about how people navigated the website; and AllDone’s marketing team periodically invited small groups of local sellers to the office for lunch or happy hour, which provided occasions in which to learn from sellers about their experiences with AllDone’s platform.
The distribution of AllDone’s phone number was intentionally limited due to the relatively small number of phone support agents on staff. Some phone calls were answered when they were received, but callers would frequently be prompted to leave a voicemail message and would later have their call returned by an AllDone support agent.
In 2014, edX created a product team, which took charge of the company’s institutional and engineering agenda (e.g., the features edX should be building or improving). Its roadmaps were based on input from members of the services team (who provided insight about users), the engineering team (who could speak to the software), and senior management (who were responsible for ensuring the company’s financial security).
Aune had previously worked at edX as a contractor, so he was familiar with both edX’s open-source developers and the company’s employees.
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The authors thank Sharon Zukin, John Torpey, Karolina Mikołajewska-Zając, Tom Gilbert, Devika Narayan, anonymous reviewers, and participants in UC Berkeley’s Algorithmic Fairness and Opacity Working Group for their feedback on this article. Jerry Jacobs, Sigrid Luhr, and Jonah Stuart Brundage directed us to helpful references. Shreeharsh Kelkar’s fieldwork was supported with grants from the Wenner-Gren Foundation for Anthropological Research (no. 8762) and the National Science Foundation (NSF grant nos. 1258640 and 1353714).
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The authors are listed in reverse alphabetical order. Both authors contributed equally to the manuscript.
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Shestakofsky, B., Kelkar, S. Making platforms work: relationship labor and the management of publics. Theor Soc 49, 863–896 (2020). https://doi.org/10.1007/s11186-020-09407-z
- Algorithmic systems
- Algorithmic management
- Digital technologies
- Organizational ethnography
- Platform governance
- Relationship labor