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Multi-Platform Content Creation: The Configuration of Creator Ecology through Platform Prioritization, Content Synchronization, and Audience Management

Authors:

Renkai Ma,

Xinning Gui,

Yubo KouAuthors Info & Claims

CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

Article No.: 242, Pages 1 - 19

https://doi.org/10.1145/3544548.3581106

Published: 19 April 2023 Publication History

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Abstract

Online platforms like YouTube and Instagram have enabled the platformization and monetization of creative work, allowing content creators to derive revenue and thrive in a creator economy. While much work has been done to understand content creation on single platforms, the creative practice often involves content creators’ agency and practice to interact with multiple platforms and make strategic decisions to optimize such interactions. In this paper, we use an interview study with 21 cross-platform creators to understand how they negotiate with platforms in their creative practices through the construction of creator ecology. We found that participants developed priorities among platforms based on varied criteria, paid attention to cross-platform content synchronization, and stressed managing and converting audiences across platforms to grow their fanbase. Our findings highlight the complex interplay between creator agency and labor, as well as yield implications for future design possibilities of creator empowerment and support.

1 Introduction

Online platforms such as YouTube, Instagram, and TikTok have given rise to the “creator economy” [75,99,100], where content creators could rely on platforms to reach a large audience and derive revenue from content creation. More than 50 million people across the globe consider themselves as creators, within which more than two million have become professional creators and make content creation their full-time job [55]. With end-user advocacy and empowerment as key disciplinary values, human-computer interaction (HCI) researchers have long investigated creative practices, such as digital fabrication and hacking [5,109] and co-creation of songs [102], as well as technology design for creativity support [30,35,52,127]. It is in recent years that a socioeconomic lens has become adopted, at the convergence of digital labor scholarship [48] and platform studies [34] to explore such issues as digital patronage [124], (de)monetization [78], and platform labor [77]. The platformization of creative labor, in this context, has pushed the conversation further to consider platforms’ dominance over structuring and controlling how content is produced, distributed, and monetized [39,40]. In this paper, creative labor refers to what Craig and Cunningham consider as “commercializing and professionalizing native social media users who generate and circulate original content to incubate, promote, and monetize their own media brand,” online and offline [27].

Indeed, recent HCI research has revealed content creators’ complex interactions and negotiations with online platforms, oftentimes invisible to their audiences. For example, content creators on YouTube need to make sense of moderation decisions such as demonetization and develop practical knowledge about how the platform's moderation algorithms work [78]; adult content creators on OnlyFans have to navigate the platform's limitations and policies through community building with their fellow creators [117], and food influencers on Instagram must wrestle with the stigma of being an influencer while utilizing multiple platform functionalities such as targeted hashtags and Instagram Insights [120]. While content creation research is growing in HCI, most has focused on content creation practices on single, particular platforms such as Twitch [80,119], YouTube [78,79,126], and Instagram [120], identifying platform-specific creative practices as well as unique creator-platform interaction patterns. However, practically speaking, it is common that content creators curate their content and audiences on multiple platforms simultaneously. For instance, Thomas et al.’s survey [110] found that 96% of their respondents used two or more platforms, 82% used four or more platforms, and 21% even used more than six platforms. However, limited attention has been paid to such situation where numerous content creators must rely on more than one platform for content distribution and revenue generation [55,97].

That independent content creators interact with multiple platforms, in essence, resonates with the notion of platform ecology, which is a user-centric view proposed by Ibert et al. that “puts user practices and agency centre stage, accentuates the application of different platforms as an integral part of everyday life, and highlights the complexities of on/offline practices” [65]. While Ibert et al. discuss platform ecology with a focus on general users exerting agency to configure multiple platforms, our study builds on this notion to explore creator ecology by considering content creators as a unique class of platform users. We are interested in understanding how creators configure their creator ecology in their creative practices across multiple platforms.

To answer this question, we conducted an interview study with 21 multi-platform content creators who create content on at least two online platforms. Through inductive qualitative analysis techniques [26], we identified three primary practices that our participants developed to configure their creator ecology: They (1) dynamically prioritized their creative labor for selective platforms over others, (2) creatively synchronized and tailored their content across platforms, and (3) strategically managed audiences by maintaining and transferring them across platforms as well as converting them to dedicated fans. Given these findings, we discuss and elaborate on the notion of creator ecology, through which participants dynamically assessed and managed platforms’ affordances and constraints, as well as audiences, in order to empower themselves. We further discuss the labor for maintaining creator ecology and provide implications for designing better creativity support tools for multi-platform creators.

We make several contributions to the HCI literature: First, we connect with and contribute to HCI research on content creation by empirically documenting content creators’ practices of managing multiple platforms and conceptually connecting creative practices and platform ecology. Second, we articulate clear distinctions that multi-platformness brings to our understanding of creative practices. Third, our creator-centric account of how content creators interact with multiple platforms yields meaningful design implications for creator advocacy and support.

2 Related Work

In this section, we first review previous HCI literature on content creation, where our work is grounded and seeks to contribute to. Then, we discuss how relevant prior work from different fields has conceptualized content creation as digital labor, and finally discuss in detail the theoretical perspective of platform ecology and its relevance to our work.

2.1 Content Creation as Digital Labor

HCI researchers have been interested in creative practices in general and, more specifically, content creation enabled by the Internet for many years. This tradition, manifest in terms such as peer production [9], participatory culture [67], and user-generation content [87], tends to value the liberating potential of social media and Web 2.0 in empowering end-users and amplifying their creative agency. For example, Wikipedia provides the epitome of content creation as collaborative work, where researchers have explored topics ranging from Wikipedia editors’ motivations and practices [2,19,61,70,121], to their community and social dynamics [20,45], to their systems of governance and moderation [11,49,50,54]. Besides the view of content creation as collaborative work, HCI researchers have also explored other aspects of content creation, such as copyright issues that creators must navigate through in interactions with platforms [47], creators’ identity performance in front of audiences [51], creators’ interactions with content moderation decisions [68], and underrepresented groups of content creators, such as older adult bloggers [18], content creators with disabilities [24,43] and youth content creators [82].

In addition to the perspectives that celebrate online content creation as a more open, liberating, and egalitarian cultural industry than traditional ones such as film and television, recent work (e.g., [1,16,56]) in HCI, media, communication, and related fields has started emphasizing that it is an advertising-driven industry, examining content creation as digital, creative labor and content creators as neoliberal workers, and paying attention to the precarity or uncertainty associated with content creators’ labor and working conditions. Content creators are considered as workers in the creative economy who frequently engage in online self-branding [41,101], which is “a form of affective, immaterial labor that is purposefully undertaken by individuals in order to garner attention, reputation and potentially profit” [64]. For instance, content creators need to foster and sustain interaction with their followers as a form of “relational labor” [6] to secure financial support [16], such as responding to the messages and comments from their followers [4].

The connection between content creators’ digital labor and the condition of precarity is profound. For example, algorithmic moderation of platforms shapes content creators’ labor conditions through algorithmic opacity and precarity [78]. Content creators need to tackle such challenges by analyzing, sharing, and applying knowledge about the moderation algorithms, which is considered as “algorithmic labor” [78]. In addition, for content creators, their content being rendered visible or invisible is directly related to their material gains [71]. Thus, their creative labor is structured “by both the promise and precarity of visibility” [39], not to mention such visibility might be unfairly deducted [79]. Duffy et al. found that the volatile nature of visibility in content creators’ creative labor is related to unpredictability across three levels: (1) markets, (2) industries, and (3) platform features and algorithms [39]. Moreover, despite that content creators strive to elevate their visibility, much of their labor remains hidden and invisible “through its lack of crediting, marginal status, and incessant demands for “un/under-compensated” labor [42].

Creators’ invisible and under-compensated labor matters to the platform economy which relies predominantly on user-generated content/videos to drive internet traffic and thus ad revenue [78]. However, creators oftentimes need to learn by themselves, without sufficient learning resources from platforms, to create content that follows content policies [79]. Although creators can join partnership programs to share revenue with platforms, many researchers have criticized the power imbalance where creators are unfairly treated by platforms (e.g., [21,73,74]). For example, platforms as authority usually implement hidden and disproportionate governance structures among creators through creator monetization programs [21] and can distribute career development resources unevenly across creators [79].

Besides such power imbalance between creators and platforms, precarity is also evident in creators’ work [56]. If a platform closes, creators might lose everything. Thus, content creators have to diversify their labor and income streams across multiple platforms (e.g., YouTube, Instagram) to mitigate risk in a rapidly changing and unstable context [56]. They consider themselves as cross-platform and multimedia brands. “Not putting all your eggs in one basket” is a pervasive metaphor in the industry [56]. Existing research [4,41,76,83] has paid attention to content creators’ cross-platform self or participatory branding, meaning that content creators promote on their own or their audiences help such promotion by bringing more viewers to the site.

However, relatively little work has been paid attention to systematically elaborating on the workflows or practices that creators develop across platforms. The prior work discussing the labor of multi-platform branding has broadly focused on how such labor is supported or constrained by certain platform affordances [41,76,83,101] or is effective or not [4]. But we have relatively little knowledge of how such branding practices are organically arranged by creators. Especially beyond purely branding or promotion practice across platforms, what other creative practices do creators conduct? How do those practices matter to their careers or relieve their precarity [38] across platforms? Even growing work has uncovered initial cross-platform practices such as diversifying income [56] or drawing audiences to crowdfunding platforms like Patreon [60]; we haven't fully understood how different platforms and their combinations are viewed by creators and shape creators’ practices. Thus, building upon this body of relevant prior work, our work aims to reveal content creators’ creative practices across platforms.

2.2 Interacting with Multiple Platforms

People nowadays have been increasingly accustomed to an online life where multiple platforms are available to them, weighing each platform's affordances, characteristics, and limits [107,118,133]. Zhao et al.’s interview study with social media users [133] found that their participants would choose which platforms to share content on based on target audiences and norms around content, negotiate between maintaining audiences and content on different platforms to separate and allowing certain audience and content to permeate other platforms, and balance between establishing a stable pattern of interacting with multiple platforms and embracing new platforms and emergent practices. Zhong et al.’s examination of 116,998 user profiles on multiple platforms such as Facebook, Twitter, LinkedIn, and Instagram showed that users adapt their profiles to individual platforms in different but still identifiable ways [134]. Sannon et al.’s interview study with 19 people with invisible chronic illnesses (ICIs) reported that their participants considered audiences on different platforms for sharing their ICI conditions [98]. Davidson and Joinson similarly reported that people maintained boundaries across social media platforms, such as using LinkedIn for professional life, while Facebook and Instagram for social life [29]. Clearly, the affordance view of multi-platform use allows the emphasis on user agency to identify what types of content and audience a platform affords and to act accordingly.

As users specify different platforms’ affordances, they also assign these platforms to different roles in their online social life. Drawing from media theories, Boczkowski et al. explained how users in Argentina attribute unique meanings to each platform, such as WhatsApp as a multifaceted communication domain, Facebook for displaying the socially-acceptable self, and Instagram for stylized self-presentation [15]. In a similar vein, Karusala et al. discussed how Indian women carefully chose certain social media platforms over another based on the meanings they assigned to them (e.g., WhatsApp was most private while Twitter was to share opinions) [69].

While emphasizing the distinctions between different platforms, scholars also become attentive to their interconnectedness and increasingly take on a holistic, ecological view of how the individual user interacts with multiple platforms. Zhao et al.’s work started to describe social media users’ practices of developing and maintaining their social media ecology [133]. Informed by media ecology [114], social media ecology [133], and self-presentation [57], DeVito et al. conceptualized the personal social media ecosystem as “the overlapping set of relationships between an individual social media user, their presentation-relevant social contexts, the user's associated imagined audiences, the platforms these audiences are imagined to exist on, and the perceived technical properties (e.g., affordances) of these platforms” [31], and stressed affordances and audiences as two key factors in such personal social media ecosystem. Using this framework, Nova et al. examined how Hijra individuals from Bangladesh perform self-disclosure through their personal social media ecosystems [90].

While the perspective of personal social media ecosystem has a focus on online self-presentation, Ibert et al.’s conception of platform ecology is more pertinent to our work due to its focus on users’ social practices, and on “the multiple interrelations they create with their on/offline environments” [65]. Ibert et al. view platform ecology as a heuristic that “puts user practices and agency centre stage, accentuates the application of different platforms as an integral part of everyday life, and highlights the complexities of on/offline practices” [65]. The notion of platform ecology has several pertinent conceptual offerings: It questions ‘user’ as an overly general term and seeks to address diverse actors such as designers, managers, and tourists. In this regard, it aligns with our work's goal to focus on content creators as a unique user type that seeks to monetize their content. In addition, while sharing with other ecological approaches the same goal of addressing the multiplicity in user-platform interaction, it has three extensions worth noting: First, it takes into account a broader range of platform-based activities to include both online and offline practices and constraints; Second, it integrates platforms as actors in a socio-technical assemblage, stressing how users and platforms both play a role and influence each other; and third, platforms are co-existent and interdependent in users’ everyday practices. Thus, the platform-ecology heuristic provides a comprehensive framework to tackle multi-platform content creators’ creative practices, which cut across platform boundaries and are deeply interweaved into their everyday life. Lastly, the platform ecology situates the user-platform interaction in the platform economy, where platforms extract value from creators’ audiences.

The platform ecology heuristic thus serves as a theoretical starting point as we delve into content creators’ practices and investigate how their practices uniquely contextualize the heuristic. Combined with our empirical data, we aim to depict what makes up the creator ecology where content creators maneuver different platforms in their creative practices.

3 Methods

We conducted a qualitative study by interviewing creators who post content on at least two platforms and used inductive thematic analysis [17] to analyze the data.

3.1 Data Collection

We conducted 21 interviews with content creators who have posted content on at least two platforms. After obtaining approval from our institution's Institutional Review Board (IRB), we used purposeful sampling [113] through participant criteria, including (1) someone over 18 years old, (2) identifying themselves as content creator making content to audiences, and (3) creating content on at least two platforms (e.g., YouTube, Twitch, Spotify). We made and disseminated a recruitment flyer on social media such as Twitter, online communities on Discord, which are comprised of either creators from different content categories or certain creators’ fan groups, subreddits such as r/Instagram, and the authors’ personal contacts of creators (i.e., convenience sampling). As shown in Table 1, we recruited 21 creators from different content categories and with diverse fanbase. Each participant was compensated with a 20 dollars gift card.

Table 1.

P#	Representative Platform	Fanbase	Category	Age	Status	Country	Race	Gender	Career	Recruit
P1	Twitch	90	Gaming	24	part-time	Nepal	Asian	Male	1 year	+
P2	TikTok	599.4K	Entertainment	30	part-time	Brazil	White	Female	13 years	*
P3	YouTube	35.1K	Music	22	full-time	US	White	Male	5 years	+
P4	YouTube	13.4K	Entertainment	27	part-time	US	Asian	Female	1.5 years	*
P5	YouTube	70.2K	Education	38	part-time	Mexico	Hispanic	Female	3.5 years	*
P6	YouTube	101K	Entertainment	38	full-time	US	White	Male	8 years	+
P7	YouTube	2.61M	Education & Entertainment	59	part-time	US	White	Male	12 years	+
P8	YouTube	31.3K	Gaming	20	full-time	US	White	Male	4 years	+
P9	TikTok	829.5K	Gaming	18	part-time	US	Asian	Female	8 months	+
P10	TikTok	1.3M	Comedy	24	full-time	US	White	Male	1.5 years	+
P11	TikTok	42	Gaming	25	full-time	US	Black	Male	1 year	+
P12	Twitch	48.9K	Gaming	21	part-time	Canada	Asian	Male	2 months	+
P13	Onlyfans	N/A	Entertainment	30	full-time	US	NA	Female	7 months	+
P14	YouTube	290	Gaming	22	full-time	US	Hispanic	Male	10 months	+
P15	Twitch	5.9K	Gaming & Entertainment	18	full-time	US	Mixed	Male	15 months	+
P16	Twitch	382	Variety	20	part-time	US	Black	Non-binary	2 years	+
P17	TikTok	706.8K	Tools & Technology	27	part-time	US	White	Male	1.5 years	+
P18	Instagram	5.33K	Fashion	18	part-time	Mexico	Hispanic	Female	1 year	+
P19	Facebook	1.601K	Gaming	31	full-time	UK	White	Female	6 months	+
P20	Instagram	1.66K	Lifestyle & Business	32	part-time	US	White	Female	5 years	+
P21	Instagram	2.66K	Lifestyle & Fashion	N/A	part-time	US	Asian	Female	3 years	+

Table 1. Creators’ profile information. Representative platform refers to one of the platforms that creators work for (regarding the multiple platforms each participant works for, please refer to Figure 1.). Fanbase is the scale of subscribers on the representative platform. Category refers to the content genre of the representative platform participants identify with. [Work] status is self-identified by creators depending on their time spent on content creation. Career refers to how long creators dedicate their time to create content consistently by the date of interviews. Recruit indicates a participant is either recruited by purposeful sampling (coded as +) or direct personal contacts for convenience sampling (*). “N/A” means our participants did not disclose the information.

Figure 1

We held all interviews as well as recorded and transcribed them through Zoom. The duration of each interview ranged from 30 to 88 minutes, with a median = 54 and average = 54.9 minutes. The interviews were conducted from January to March 2022. We received verbal consent of voluntarily joining this study from each participant before interview. Also, we informed participants that their interview data would be anonymized, and they reserved the right to withdraw from the interviews whenever they wanted.

We created and followed a semi-structured interview/discussion guide to conduct interviews, which included seven sections: (1) warm-up questions, (2) platform or account use, (3) content creation practices, (4) content sharing, (5) monetization or profits-making, (6) interactions with audiences, and (7) creator moderation experiences. Warm-up questions were mostly aimed at ice-breaking in conversations with creators by asking about their demographics, such as what gender and race they identify with, their age, country, as well as platforms, channels, frequency, and duration dedicated to creating content consistently.

All the rest six sections of interview questions were designed based on the fact that participants work on more than two platforms. In the platform or account use section, we asked: “Do you dedicate your efforts to all platforms equally?” Then, depending on participants’ answers, we asked, “why did you dedicate more (or fewer) efforts on [platform]?” We further asked, “do you have one account or channel per platform?” and depending on their answers, we followed up with probes. The content creation practice section, as its name shows, aimed to understand “how did you create content for different platforms?” and could be detailed like “do you script your content before posting for every platform? If so, how do you do that? If not, why?” The content sharing section, inspired by prior work focusing on general social media users’ multi-platform content sharing [103,133], included questions asking about procedures of how creators share their content across platforms. The monetization or profits-making section, inspired by work about partnership programs on platforms [73,93], involved questions about “which platform are you eligible for monetization?” and “how do you make money from different platforms? Is there a composition difference in terms of income you receive from platforms?” The audience section, informed by prior work around parasocial relationships [95,125] and social support between audiences and creators [123], aimed to understand how creators measure their audiences, interact with them, or build up relationships with them. The last section, creator moderation experiences, aimed to understand how creators experience different moderation, such as income or visibility deduction, content removal, or account suspension across platforms. This section of questions was inspired by prior work focusing on creator moderation [3,78,132]. In the process of interviews, once we found interesting points related to our research question that needed to be elaborated, we put forward probes, i.e., asking follow-up questions. Additionally, some participants shared their screens or sent screenshots to permit our use. This supplemented our data collection.

3.2 Data Analysis

We used inductive thematic analysis [17] to analyze the whole interview dataset through NVivo 12, a qualitative data analysis software. The first author first read through and familiarized himself with the dataset. Then, the first author assigned initial codes to all ideas expressed in the interview dataset. In the process of assigning codes to ideas, all authors held weekly meetings to discuss each individual code and its correspondence to each idea – how each initial code could precisely describe a data unit in the interview dataset. Here, a data unit could be a sentence or a whole paragraph, depending on how many details a participant presented to describe an idea. After this, the authors conducted rounds of coding by identifying the patterns (e.g., higher-level themes) among initial codes, grouping similar codes together to be a theme, and further grouping similar themes to form an overarching theme. For example, we placed the initial code, “distilling,” under the theme, Platform-specific Content Curation, and they both conceptually belonged to an overarching theme, Cross-platform Content Synchronization. For another example, we assigned “attracting online traffic from one platform to another,” an initial code to “cross-platform audience transfer,” a theme. Then, this theme was grouped with other similar themes under section 5.3.

All authors also re-examined (1) the codes that had been already assigned to certain themes and (2) the connections between themes and higher-level themes. For example, the quotation, “I couldn't just sprout anything; I was really bad at improvisation….” in Content Type was initially coded as “preferring pre-cording video creation on YouTube over live streaming on Twitch” under the theme, “content type.” Then, in weekly meetings with all authors, they all agreed that this theme belonged to a higher-level, overarching theme, “prioritization,” since the participant fundamentally prioritized certain platform for content creation due to content format differences. This showed our data analysis process was iterative by moving back and forth among data, codes, and themes. We ultimately ended the analysis process by acquiring a sound thematic scheme, including three overarching themes, to answer our research question informatively.

3.2.1 Researcher Positionality

The first author has been an amateur video content creator on TikTok, YouTube, and Bilibili, and has been in personal contact with over 12 other creators across platforms and content categories for over two years. The other authors do not actively post videos on social media but have generated textual content. They have been active and long-term viewers of video content of diverse categories such as education, gaming, and entertainment. Our personal interests in and engagement with content creators motivated and informed this research, supplying sufficient domain knowledge for us to develop engaging interview questions and make sense of our interview data. However, we strived to achieve “empathetic neutrality” [96], whereby we sought to avoid possible biases and to be as neutral as possible in the collection, interpretation, and presentation of the data.

4 Background: Content Format, Creator Tools, and Creator Economy

This study focuses on content creators who primarily create video content. Platforms support different formats of creative content, among which videos are the most popular. A typical format is pre-recorded videos supported by platforms like YouTube and Vimeo. In recent years, a short-form, pre-recorded video format (e.g., 15 or 30 seconds or more) has drawn attention from audiences and creators as well. TikTok, as one of the first several platforms supporting such format of content, became popular in the US [108] back in 2020. Later, many video-sharing platforms started supporting short-form videos. YouTube released YouTube Shorts, a short video platform, in September 2020. Instagram and Facebook also launched reels (i.e., similar short-form videos) in the US back in September 2021 [84]. In addition to the pre-recorded video format, many platforms also support live streaming services, such as YouTube Live, Facebook (i.e., Facebook Gaming), TikTok, Twitch, and Instagram.

Given these content format differences, platforms offer content creation tools with different focuses. For short-form, pre-recorded videos that audiences frequently watch from smartphones, TikTok, Instagram, Facebook, and YouTube Shorts offers mobile creator tools with various types of functions, such as filters, media library, and pre-shooting effects (see an example from (1) in Figure 2), compared to editing tools for longer video (see an example from (2)) that creators might more frequently edit from PC but not smartphones. Besides, living streaming services like Twitch [116] or YouTube Live [105] offer creators clipping tools to extract short, sharable clips from their longer live streams. And this function exclusive to live streaming inherently does not apply to pre-recorded video.

Figure 2

Although there might be some differences in video editing functions across platforms or content types, platforms offer similar tools for understanding content performance. Content performance refers to metrics or analytics that creators could use to understand how successful they are on a platform, such as their views, the amount of money (e.g., ad income) paid by the platform, comment and subscription numbers, and more. As (3), (4), and (5) pictures shown, the main performance metric stressed on the higher position of the user interfaces is audience engagement (e.g., viewing, retention, commenting, sharing, etc.). For example, TikTok (3) stresses views and watching time (e.g., total or average watching); Facebook (4) also prioritizes views as well as user comments and sharing, and YouTube (5), again, presents watching time and views as primary channel performance metrics to creators.

Those platform-provided content performance tools focus on audience engagement metrics because many social media corporations treat monthly active users and time spent on content consumption as their key performance metrics (KPIs) and decide what amount of money they will distribute to creators by audience engagement scale (e.g., Creator Fund on TikTok [111]). For example, YouTube [128] relies on advertising (ad)-supported content in their revenue models, and such ad income is calculated by audience engagement [14]. Before platforms receive ad income, they conduct internal auctions with advertisers and then place platform-wide advertisements (ads). This is the time when creators play a role in having ads placed around their content and then share the ad income with platform. Platforms standardize this income-sharing procedure through creator partnership programs, which are similar across platforms. TikTok's Creator Fund [111], YouTube's Partner program [129], Facebook [85], and Instagram's Partner Monetization [86] collectively share a similar logic that more audience engagement (e.g., views, liking, commenting) leads to higher income distributed to creators. Twitch's affiliate or partner programs focus more on fan subscription than ad income [106], and they emphasize that audience engagement matters to creators to get better chances of gaining more subscription income. Such demand for metric quantification is common in the social media entertainment industry [28]: Metrics such as liking, disliking, following, and more have been seen as validation for creators’ success. As Poell et al. noted, “platform metrics have become central to key fields of cultural production; they trigger anxieties over the perceived loss of creative autonomy” [92].

Creators thus need to conduct a variety of business activities to sustain and grow their creative careers. For example, as audiences accumulate, creators are able to conduct brand collaboration directly with external advertisers by posting promotion content for them, selling merchandise (e.g., t-shirts, mugs), receiving fan donations directly on platforms (e.g., YouTube Giving, PayPal), and selling subscriptions and exclusive content on crowdfunding, third-party platforms like Patreon, or more [66]. However, in a competition with 50 million people identifying themselves as creators [36], creators need to connect closely with audiences to establish their brand that can be distinguishable from other creators [66] in order to make their creator career sustainable [32].

5 Findings

We identified three primary practices participants developed to configure creator ecology, including platform prioritization, cross-platform content synchronization, and audience management across platforms (e.g., maintenance, transfer, and conversion).

5.1 Prioritization

While prior research has found creators promote their channels and content across platforms [41,83,101], we further uncovered that, although creators use multiple platforms, they do not use them equally. Rather, creators consciously prioritize certain platforms based on careful considerations. Prioritization refers to participants’ practice of choosing one out of multiple platforms as the primary for content creation and dissemination. Participants still value other secondary platforms but usually spend most of their creative labor on and derive most of their revenue from the primary platform. The primary is thus perceived as the most important platform in participants’ creator ecology. Participants detailed four primary dimensions that they considered when prioritizing a platform, as summarized in Table 2.

Table 2.

Theme & Sub-theme	Description
1 Professionalization	This describes to what extent a platform can support content creation as a profession.
1.1 Monetization	Platforms’ different monetization models and which platform offers better income.
2 Audience Connection Scope	This describes which platforms offer participants the deepest and widest audience connection (e.g., content reach).
2.1 Community Closeness	This means which platform can afford participants to build up deeper and closer communities with peers (e.g., creators, audiences).
3 Content Type	This describes what content format that a platform supports primarily.
3.1 Content Quality	This describes whether the quality of content on a platform meets participants’ expectation.
4 Cost of Content-related Work	The cost of creating and distributing content or other content-related work on certain platforms.
4.1 Real-life Availability	Participants prioritize content creation on certain platforms that would cost less of their time.
4.2 Labor Cost	Participants prioritize platforms by the labor they can handle for content creation.

Table 2. Personal Considerations of Deciding to Prioritize Labor for Certain Platforms over Others.

5.1.1 Professionalization

Professionalization describes the extent to which a platform could support its creators’ career path to become a professional. Participants prioritize certain platforms given whether they can effectively afford participants’ content creation as a profession. For example, P14 said:

I want to promote [my] YouTube [channel], not just because I want to have everything in one main platform but because there are a lot of offers and opportunities to make this not only a hobby but a career path, and with TikTok, I do make some money off, but it's nowhere near what YouTube can bring you, especially later on to the future. [P14]

P14 prioritized YouTube over TikTok. The fundamental reason that he thought TikTok cannot be like YouTube to support his career is the number of business opportunities he can leverage to earn money.

Like what P14 did, P20 prioritized Instagram because it can better support her merchandise-selling business: “I feel like TikTok and YouTube are just more like views sites but Instagram is more like connecting with customers. I could post a beauty product [and] I test it out.”

Monetization. If P14 and P20’s prioritization reasonings speak about general business conditions for professionalization, other participants prioritize certain platform by the amount of money they could directly earn from the platform's partnership programs (e.g., ad income on YouTube [129], Subscription income on Twitch [106]). For example, P6 said:

My main primary income sources are from YouTube. There's a limitation [of] YouTube [that] we tend to release longer form content, but it's impossible to do that on TikTok, unless multiple parts, and if you post multiple parts on TikTok, you're gonna hit diminishing returns. [P6]

At a surface level, P6 deprioritized TikTok because it cannot host longer videos. More fundamentally, his prioritization action depended on the amount of income he could earn on which platform. Since YouTube allows more ads in a video longer than eight minutes [130], leading to more ad income, P6 prioritized content creation on YouTube.

5.1.2 Audience Connection Scope

Participants prioritize certain platforms based on which ones offer a larger scope of audience connection. For example, P9 prioritized TikTok over other platforms because, as P9 said, “I have the most following on TikTok, and most people, when they find me on Twitter or YouTube, they know about my TikTok first.”

Community Closeness. Participants also decide the prioritized platform by which platform can support deeper and closer communities with audiences and other creators. For example, P8 said:

You're posting a one-minute video on TikTok; they're not going to have that connection with you as a community, such as Twitch or YouTube. (…) I have people come into me and said they were going to commit suicide, and I talked them out of it. But for TikTok, Instagram, Twitter, stuff like that, you're not going to have that connection, where you cannot talk to them, one on one. [P8]

P8 prioritized YouTube and Twitch over TikTok, Instagram, and Twitter. His reason was that the platform affordances on Twitch and YouTube (e.g., comments, longer content format) could motivate more intimate audience engagement, while the audiences on other platforms were less likely to engage with him interpersonally.

5.1.3 Content Type

Content type refers to the primary content format that a platform supports. For example, participants viewed YouTube as primarily a place for sharing long video content, even if it (i.e., YouTube Shorts) also supports short videos like what TikTok does. Our participants explained in detail how they made prioritizations based on content type. For example, P1 said:

I couldn't just sprout anything; I was really bad at improvisation [on Twitch]. It's more comfortable for me to script videos because I feel like I haven't missed anything to sit in that video. So, it's more of making sure that I'm saying everything my point and not misunderstanding. [P1]

P1 prioritized YouTube over Twitch for content creation because he preferred pre-recording video over live streaming, where he was afraid that he cannot explain things completely in a short-time frame and real-time.

Perceived content quality. Participants also prioritize certain platforms if they afford and support their desired content quality. For example, P4 prioritized YouTube for more content creation over TikTok, as she said: “I wouldn't really be proud of my TikTok videos; [they] are short. I feel like there's no effort.” In contrast, some participants prioritize certain platforms because they desire to create the perceived lower quality of content that those platforms support. For example, P17 said:

If someone makes a comment, and I think it's worth making, then absolutely I'll do that on [TikTok], [but] YouTube is not as easy as it is on TikTok because TikTok is very casual, whereas YouTube is not as casual. If you post a video, it has to be a good video every time. You can't post a terrible video of you just saying hey, how you doing, buddy. [P17]

P17 prioritized TikTok over YouTube. The underlying reasoning behind such action was that P17 mentally connected the impression of a casual style of content with TikTok while connecting the impression of higher-quality content with YouTube and he preferred lower quality of content creation on TikTok. While he did not disclose why he developed such impression difference, it impacted his prioritization actions.

5.1.4 Cost of Content-related Work

Participants’ prioritization strategy was also informed by the cost of creating, distributing content, or other content-related work expected on different platforms. For example, P19 said:

When I first started out [on Facebook], I'd already hit my hundred follows. So, I had more contacts on Facebook than I did anywhere. Right now, I am getting more contacts on Twitch, and I'm not far from being affiliated with Twitch, but my contacts were always on Facebook, and that is why it's my primary platform. [P19]

P19 prioritized Facebook over Twitch because she already had built more connections with creators and audiences on Facebook. And she personally did not want to perform more work, such as attracting new audiences and building up subscribers on Twitch.

Real-life Availability. Particularly, participants choose to prioritize content creation on certain platforms that would cost less of their time. For example, P20 said:

The only reason I don't do it [on YouTube] is I just feel there's not enough time, and I have two kids. So that's the reason why I do the short videos [on Instagram] because it's just easier to make a two-minute video than to make a 15-minute video. [P20]

P20 prioritized Instagram over YouTube because she did not have as much time for content creation on YouTube as on Instagram. The reasoning behind such action was that P20 associated the time-consuming impression of content creation with YouTube and connected the one of fast and short video creation with Instagram.

Labor Cost. Participants prioritize platforms by the extent of labor they can handle for content creation. For example, some participants prioritize platforms that require fewer intellectual efforts to make content more attractive. As P5, an education content creator who has prioritized YouTube over TikTok, said:

I have noticed the younger the person, the shorter their attention span. So as a consequence of this difference in age groups, you have less chance to retain users on TikTok unless you are entertaining enough; you need to be very emotional, which usually isn't the way I do. [P5]

Here P5 assumed that TikTok has a much younger user base than YouTube, and thus a different dynamic for user retention. So, P5 deprioritized content creation on TikTok because she assumed that making videos more entertaining and emotional is a typical way to acquire longer audience retention, and she usually would not make such efforts.

5.1.5 Dynamic Prioritization

Participants’ prioritization practice is not static. They dynamically shift their prioritized platforms because their needs and personal interests change over time, usually based on creator channel growth, fanbase, and income. For example, P17, who changed his prioritized platform from YouTube to Twitch, said:

Originally, I only streamed on YouTube because I thought YouTube would be easier to get audiences on. I was kinda right, but there's a problem with YouTube, [where] I don't know if they (YouTube) socially engineered, but on Twitch, it's so much easier to find people to collaborate with, and it's easier to grow on Twitch after you start getting established if you can network with other smaller streamers. (…) I still stream on YouTube, but now I'm streaming on twitch more. [P17]

P17 shifted his prioritized platform from YouTube to Twitch while still streaming on both of them. His reason for such shift was not only about the easiness of creator collaboration but essentially about his assumption that collaborative content creation can attract more audiences compared to individually created content. And P17 can more easily verify his assumption on Twitch than on YouTube, so he prioritized Twitch to get “easier to grow.”

Besides strategically focusing on growing fanbase or content reach, some participants consider their preference of content types as one of the determinants in choosing prioritized platforms. For example, P8, who has prioritized content creation on YouTube, said:

I wanted to be mainly a Mixer streamer, but everybody on there like, why me not go to YouTube and do better scripted videos. So, I switched over to there, and it was so much easier, time-wise; you can edit out interruptions going on, and I wanted to go back streaming but just time kills you in that kind of industry. [P8]

Mixer was a live streaming platform owned by Microsoft, and it was discontinued in 2020 and redirected to Facebook Gaming. P8, in the above case, shifted the prioritized platform from Mixer to YouTube because of content type differences. And essentially, P8 thought scripted content creation offered him better time flexibility and user agency in creating content rather than live streaming, a content format that he was unable to edit.

Taken together, our participants conducted different decision-making on personal interests to prioritize certain platforms over others in their creator ecology. Conducting such decision-making, including professionalization, the scope of audience connections, content types, and cost of content-related work that platforms afford or require, directly impacts whether they could receive the extent of investment return they want from content creation. So, participants felt the necessity of prioritization, and they also might change prioritization given their personal interests at the moment.

5.2 Cross-platform Content Synchronization

Cross-platform content synchronization describes participants’ creative action of synchronizing their content across platforms. They seek to publish variations of content on multiple platforms at the same rate. Such content can be newly created, curated from their old content, or identical across platforms. Participants created variations of content because of platforms’ affordance, characteristics, or limitations, as well as catering to platform-specific audiences’ interests.

5.2.1 Sequential Workflow based on Creator Tools

Prior work has found creators on certain platforms such as Twitch [80,122] and YouTube [79] leverage creator tools such as Twitch Analytics and YouTube Creator Studio to better understand their content performance. Beyond using these creator tools on one particular platform, we found participants created a sequential workflow of content synchronization from one platform to others based on the creator tools they can use. That is, they specified which platform should be used before which platform. For example, P5 described:

YouTube [Studio] tells you which areas of your video are mostly viewed and where you lose people. So, [for] where I see people leave in the video (lower retention), I will cut it [off] for Facebook and Instagram. [P5]

P5 leveraged historical video analytics offered by YouTube Studio dashboard to synchronize shorter videos on Instagram and Facebook. That is because she believed popular video clips (i.e., with higher audience retention) on one platform could do a better job of maintaining audience engagement and retention on another platform compared to non-popular clips. So, such information guided her content curation for other platforms.

Beyond attracting and retaining audiences, participants described that certain platforms’ affordance or limitations shaped their workflows to be sequential. For example, P21, who actively creates short videos across platforms, said:

TikTok is actually more user friendly because I can mix video and pictures together [in] reels, [but] on Instagram; I cannot do that. I can either only do the picture or I can do videos. So, I still use TikTok to create [reels for Instagram]; after I create it, I automatically post [it] to Facebook because it's integrated. [P21]

P21 described her sequential workflow: creating and distributing videos first on TikTok, then on Instagram, and finally on Facebook. Her reason for such workflow was that TikTok offers video editing tools that can better suit her needs for content creation than Facebook and Instagram. And since the videos across these three platforms were the same, the sequential workflow streamlined her content synchronization.

Other participants also stressed that sequential workflow among platforms can be dynamic, depending on which platform's creator tools suit their particular videos the best. For instance, P20 mentioned: “Sometimes, you can also see I'll post TikTok first and Instagram later, [because it] just depends on what kind of video because like Instagram, video editing offers one thing and then TikTok editing offers another, so that's the reason why switch back and forth.”

5.2.2 Platform-specific Content Curation

Platform-specific content curation refers to our participants’ action of distilling or segmenting their content to synchronize on different platforms to suit platform-specific audiences’ interests. Before this synchronization action, participants gauged platform-specific audiences’ interests. They described two ways of gauging: (1) distilling “highlight” moments from longer videos for short video platforms and (2) segmenting content into different subset content topics for audience interests across platforms.

Distilling. Participants empathized with audiences and knew what kind of content would be liked by what audiences, so they distilled highlight clips from their long content that had been created on other platforms. For example, P8, who creates long videos on YouTube and also creates short videos on TikTok and Instagram, said:

What I'll do is to find a good area to break it (video) up; it's a brand new video like I just posted five minutes ago. [So,] I'm not going to really know [from] the dashboard [about] when it's really funny [in the video], where it's not like in the middle of somebody saying something. [P8]

P8 distilled the “highlight” clips he considered would intrigue audience interests on short video platforms from longer videos on YouTube. Since he conducts a fast-paced content synchronization, creator tools like YouTube Studio dashboard cannot, in time, support him to curate funny or entertaining content from longer YouTube videos. So, P8 empathized with and predicted his audiences’ interests to make fast-paced content synchronization on short video platforms possible.

P12, who streams on Twitch and posts videos on TikTok, also supplemented this content curation procedure in detail:

You just have to be honest with yourself and just say, like oh, will this somebody enjoy this if I saw this on TikTok; would I enjoy watching this; will I stay and watch this video, or would I just scroll past it. I like going through all my clips because I'll clip something, and then I'll look back at it later and be like, this is not funny I do; I will not use this. [P12]

P12 carefully distilled certain clips from his live streaming recording on Twitch and posted them on TikTok. He made different cognitive efforts such as speculating and empathizing with audience interests on TikTok, identifying what moments in his live streaming might meet such interests, and deducing audiences’ scrolling behaviors for his curated video. P12 also made behavioral efforts to review both longer live streaming recordings and clipped content to make sure his highlighted clips could successfully attract more audience retention.

Segmenting. Participants also segment their content into various topics to cater to cross-platform audiences’ interests. The difference between segmenting and distilling is whether participants recognized the topics of curated content differed from the topic of original content. For example, P9, who streams on Twitch and posts videos on TikTok, said:

Since I'm a girl playing video games, if someone is being very misogynistic and toxic to me [in my streaming], that's something I might clip because I can show other people, and they'd be interested in watching. [P9]

P9 noticed certain parts of her Twitch content as suitable for a TikTok audience, so she clipped it. Such clip depicting a toxic moment is not directly associated with her streaming content topic, gaming, but she assumed it would be entertaining and attractive enough for audiences on TikTok. P9’s case showed how she curated subset content topics from one platform to cater for certain audiences on another.

Beyond individual content curation, we found participants even curated their channel's content category with different granularity across platforms. For example, P14, who makes gaming content, explained:

All channels are just gaming channels, but they'd have their own smaller category, depending on the platform it got with. On YouTube, people like a little bit longer content, so I'd say it probably is a lot of gameplays or a walkthrough. But then I'll take target TikTok with a really short funny video that that can go viral as just depending on the algorithm. (…) On Instagram, a lot of people like informational videos, so I'll go on Instagram to post any game information I know about it because those seem to do better on that platform. [P14]

P14 understood that his audiences across platforms have different interests, so he curated different granularity of gaming topics of video content for each of his channels. He sensed such platform-specific audiences’ interests by observing which topic of videos received more views than another topic across platforms. P14’s case showed he exerted agency to make customized content that can maximize his investment return of content creation on each platform.

In sum, we found participants creatively crafted their sequential workflows of synchronizing content due to different platforms’ affordances, characteristics, or limitations. They further gauged audience interests cross-platforms to curate customized content for each of them.

5.3 Multi-platform Audience Management

Audience management describes strategic processes of interacting with and managing audiences from different platforms. Extending prior work that has uncovered audience management on Onlyfans [117], Twitch [124], or different live streaming platforms [123], we found how creator participants strove to grow their audiences across multiple platforms by using three specific strategies: (1) maintaining the current audiences across platforms, (2) transferring audiences across platforms, and (3) converting current audiences to dedicated fans. These three strategies are not mutually exclusive because either audiences or dedicated fans could help our participants sustain the creator ecology.

5.3.1 Maintaining cross-platform Audiences

No matter what platforms our creator participants choose to prioritize, they maintain their consistent presence and connections with audiences. For example, P15, who creates content on Twitch, TikTok, and YouTube, said:

If I have these TikTok videos, so, like on days, where like if I can't stream or I didn't upload a YouTube video, I can at least get something out there to keep the engagement going, because one thing you don't want to do is having nothing coming out for a long period of time, because it's the Internet, people can forget about you and move on to a new creator if they think you're done. [P15]

P15 would create new videos on TikTok even though he was not active in streaming on Twitch or creating a new video on YouTube. The competition for obtaining audiences’ attention and consumption between creators, especially those who are in the same content genres as P15, was the main reason for him to actively maintain his presence with audiences.

Besides actively posting content, participants also described the importance of responding to audiences. For example, P16, who streams on Twitch and creates content on TikTok, mentioned:

I always try to be proactive and engaging; if someone leaves a comment on TikTok, I'm going to leave a comment as well for them to realize, “oh, you actually recognize that I've left a comment on your video.” (…) I try to make sure to almost multitask to both play the game, or have a conversation with whoever I'm streaming with or the chat as well [on Twitch]. I feel like I'm a big proponent that you have to engage with your chat in order to build community. [P16]

Either on Twitch or TikTok, P16 actively responded to audiences and other creators. Although P16 mentioned such active interactions were mainly for creating his own audience community, what he actually did was to sympathize with the reactions of other creators and audiences who would receive his responses. After they have such social interactions, P16 can maintain his closeness with audiences across platforms.

Sometimes, participants customized responses to maintain their connections with audiences across platforms. As P20, who is a small business owner on Instagram, said: “Once I see someone comments on my video, I'll click their profile a little bit on Instagram [with more professional responses], and then on TikTok, I just be like “TY” for Thank you.”

5.3.2 Cross-platform Audience Transfer

Cross-platform audience transfer refers to a practice of how our participants strategically transfer audiences who consume their content on one platform to their potential audiences on another platform. Such action not only helped audiences streamline the consumption of our participants’ cross-platform content but also grew participants’ careers. Audience transfer thus becomes an important operation triangulating online traffic for sustaining participants’ creator ecology. Sometimes, our participants conducted selective audience transfer between platforms, but oftentimes, they embraced the possibility that audiences freely choose whatever platforms. For example, P9 said:

I always put my socials on TikTok; I have like a Linktree. That links them (audiences) to all my socials. And the same with my Twitch and on my YouTube. Another thing is you have to have everything with the same name, so it's very easy for viewers to find you. [P9]

P9 made two actions to transfer audiences across platforms: (1) posting her Linktree, a reference page compiling multiple links everywhere, and (2) keeping her channel names the same across platforms to streamline audience transfer.

Participants also mentioned that Linktree cannot always be effective for audience transfer. For example, P12 said:

What I would do is, at the end of my videos, (…) say[ing] I'm live over on Twitch because the more buttons you have to press to get to a place, the less likely someone will pay attention; because on TikTok, your attention span is like really small. If you have to go through a Linktree like sleep on your profile, it's really a pain to go to all [socials]. So, then I'll try to add it (promotion) to the end of my video or my comments section. I also have it in the caption of my videos that I stream on Twitch. [P12]

P12 tried to transfer his audiences from TikTok to Twitch by actively promoting his Twitch channel in his content on TikTok. The reason why he integrated such audience transfer actions in content creation was to streamline the ways that audiences can use to consume P12’s content across platforms instead of exclusively relying on Linktree.

Although creators tried to promote themselves across platforms as much as possible, resonating with prior work about multi-platform self-branding [41,76,83], participants also recognized the constraints of doing so. For example, P3 said:

If I was to put an [YouTube channel] advertisement in a Spotify release, that would be intrusive to the listener experience. So, I promote my Spotify mostly through my YouTube, so if they're already listening to my Spotify, then they probably already follow me on YouTube. [P3]

The reason for selective audience transfer, as P3 mentioned, is to fit the typical user experience of content consumption on Spotify. And essentially, he wanted his Spotify profile to be purely for music content distribution while functionalizing YouTube for both audience transfer and music content sharing, as he implied that YouTube's platform affordance (e.g., video with comment sections) is more appropriate for such mixed purposes.

5.3.3 Dedicated Fan Conversion

What our participants have been consistently doing is to convert their audiences to become dedicated fans who could provide more social and financial support, no matter which platform those fans originally come from. These audiences are not limited to users who generally consume content but also peers who create content. Along the way, when participants strove to cultivate dedicated fans, their audience communities will start to snowball and thus help sustain participants’ creator ecology.

One common initial practice of dedicated fan conversion is to intrigue audience engagement across platforms. For example, P18, who creates content on TikTok, Instagram, and YouTube, said:

I have colleagues on my Instagram, and I put them on my stories; if they can share and save the posts or share them on their stories, Instagram is gonna to show them to more people. (…) Because all the platforms have the same algorithms, if they (other creators) share it with people or save it for later, then there will be more likes and comments. [P18]

P18 asked her peer creators to share, save, and comment on her content across platforms. Such creator collaboration has been tested to be effective for both creators in attracting subscribers and gaining popularity [72]. P18’s case further detailed the reason for this effectiveness: more audience engagement would act as a positive signal to recommendation algorithms to improve her content visibility to correspondingly gain more dedicated user engagement.

However, obtaining engaged audiences is not enough for creators because their career growth is not exclusively supported by platform income (e.g., ads revenue on YouTube [129] or creator fund on TikTok [111]), which is calculated by audience engagement performance. What participants further aimed for was to convert audiences to be more financially supportive. Resonating with a recent work describing how creators on Onlyfans draw audiences from social media platforms like YouTube or TikTok [60], we found that P13 strategically conducted audience conversion for her Onlyfans channel:

It's just that Onlyfans gives you the information of what percentage you are among [all creators] in terms of how much money you make. (…) They (audiences on TikTok) can only know your percentage, but you cannot say the word of it (Onlyfans), then they'll probably search on you. [P13]

Instead of saying the keyword “Onlyfans” in videos, P13 implicitly advertised her Onlyfans channel on TikTok to draw audiences to financially support her on Onlyfans. Due to the platform and content sensitivity of Onlyfans, P13 implied the importance of fan donation to her career and, at the same time, avoided content moderation to conduct audience conversion.

Converting and acquiring dedicated fans are not the ending point for configuring creator ecology. Rather, we found participants strove to maintain the activeness of dedicated fans, like what P6, a full-time cross-platform creator, said:

I'm more available to audiences on Patreon, like [who] give a message to me; I'll respond immediately. If I have like an idea, I'll ask them for input, or I'll tease what's happening to them versus anywhere else, like Instagram, Facebook, or Twitter; that's all like promotion. But with Patreon, it's like making them be more integrated into the [creation] process where I'll say I'm thinking about making a video about this, what do you guys think. [P6]

P6 involved audiences on Patreon in his content creation processes and more frequently and proactively engaged with them than he did on other platforms. The primary reason for such discrepant treatment is that the fans who financially support him are critical to sustaining his full-time creator career, while platform income calculated by the audience engagement is not. So, he tried to maintain his dedicated fans.

Taken together, our participants sustained their career growth and creator ecology by maintaining audiences across platforms. Then, they strategically transferred audiences from one platform to others in order to triangulate online traffic and improve their content performance metrics. Eventually, participants aimed to convert active audiences to dedicated fans who can consistently support them. So, participants’ creator careers can grow sustainably.

6 Discussion

Our study detailed content creators’ practices in navigating multiple platforms to benefit from the platform economy and advance their creator careers. They do not view platforms available to them equally but perceive and maintain priorities based on a set of platform affordances and characteristics. They strive to encourage audience and content to permeate other platforms through content synchronization and audience conversion, which marks a clear distinction from social media users who seek to balance between separation and permeation [133]. This set of findings allows us to reflect upon what constitutes the creator ecology for multi-platform content creation, as well as the labor for maintaining it. Last, we derive design implications from our findings for creator empowerment and support.

6.1 Configuring the Creator Ecology for Multi-Platform Content Creation

Prior literature has accumulated much understanding of how users interact with multiple platforms for the purpose of sharing [62,98,133]. The notion of sharing is social and interpersonal and communicates a sense of community. The emphasis on sharing originated from the early promises of social media platforms to connect people and build online communities. In the context of content creation, however, this communal ethos has given way to the business logic that is metric-driven and profit-driven. In the interviews, our participants attached much importance to the audience engagement performance of their content, and the number of views directly correlates with their ad revenue. The platformization of creative labor, in this sense, is also driven by creators themselves, who exert agency to configure their interactions with multiple platforms.

Against this backdrop, our findings help conceptualize the notion of creator ecology, which captures a creator-centered ecosystem where content creators’ creative practices involve the flexible, dynamic management of multiple platforms and their associated affordances and audiences in order to empower themselves through such cross-platform management. In creator ecology, creators’ practices are different from the practice of a general social media user who shares information across platforms. For example, prior work has found that a general user either disregards the boundaries between platforms by sharing similar, if not exactly the same, content across platforms [103] or reinforces such boundaries by selectively sharing content [133]. Our creator participants are different in their deliberate efforts to dismantle such boundaries by promoting content and transferring audiences across platforms. Especially depending on platform-specific audiences’ interests, participants curated different versions of the content or even channels per platform.

These differences in practices between general users and creators hinge on their different purposes in sustaining an ecosystem of online platforms. General social media users engage in multiple platforms to fulfill their gratifications of self-presentation [107], while creators do so to stabilize and grow their careers. General social media users consider content and audience traits for selective content sharing [133], but creators like our participants must make other decisions to construct their creator ecology, such as prioritization or content curation, as well as consider platform affordances (e.g., creator tools, recommendation, and monetization algorithms) and social relationships with audiences.

Thus, our participants make sure to take advantage of what they can utilize from different platforms (i.e., technical affordances) to configure creator ecology (see Figure 3). Affordance refers to not only the materiality of design features from devices or platforms but also the “imagined” [88] or “perceived” [89] part of it, where users’ expectations about technologies shape “how they approach them and what actions they think are suggested” [88]. This affordances perspective centering on user agency in human-technology interaction has been increasingly adopted to understand the practices of creative labor like content creators (e.g., [76,83,101]). Resonating with this line of work, our findings showed that participants chose to leverage certain technical affordances, such as the content format or the perceived content quality on platforms [101]. But instead of leveraging affordances on individual, separate platforms to support creative practices across platforms [76], our participants detailed how they orchestrated different combinations of sociotechnical affordances from platforms, non-platform tools, and human actors [44]: they (1) dynamically prioritized content creation efforts for platforms that align with their personal interests relatively the best, (2) crafted sequential workflows based on creator tools on one platform to lower cost of content synchronization on multiple platforms, and (3) selectively promoted certain creator profiles or content due to different designs for content consumption across platforms. Sometimes, such action of dynamically leveraging sociotechnical affordances can be an outcome of compromise. For example, P5 prioritized YouTube, Instagram, and Facebook over TikTok due to the mismatch between her efforts of creating educational content on the former three and the effects of how such efforts translated to short videos and retained audience attention on TikTok.

Figure 3.

Then, our participants navigate and leverage the social relationships or affordances that they built up with audiences to further sustain creator ecology. Prior work has uncovered processes of how audiences, or broadly speaking,. peers, including audiences and other creators, offer social support to help creators grow their careers on Onlyfans [117], Twitch [124], Patreon [60], or different live streaming platforms [123]. Instead of viewing such process from the perspectives of support providers, our interviews detailed how creators, from the support receiver's perspective, strategically motivated and maintained such support across platforms. These strategies showed in a funnel style applied to multiple platforms (see Figure 3): (1) building audience awareness of creators and their content, (2) retaining audience attention across platforms, and (3) leading audience dedication. We could view building audience awareness as how participants utilized affordances on different platforms (e.g., content formats, content reach influenced by algorithms) to create a “mirror” of interpersonal relationships with audiences (i.e., parasocial relationships) [58,76,95] as many as possible on different platforms. Then, for audiences who chose to consume content, participants tried to retain their attention by creatively synchronizing and curating content for them across platforms. Eventually, participants aimed to develop a relatively smaller number of dedicated fans from audiences. This aim can be shown in how creators synergistically draw audiences from different video-sharing platforms to Patreon for fan donation [60], as done by our participants. But beyond that, our participants more proactively built intimate, interpersonal relationships with dedicated fans (e.g., receiving their feedback for content creation), no matter which platform they are from, to sustain creator ecology.

Thus, the ways that participants creatively leveraged sociotechnical affordances, which are comprised of technical and social components across platforms, as shown in Figure 3, empowered them to boost the economic or social outcomes that they might receive to what they expected. As such, the creator ecology is individually developed and maintained by each creator, pertaining to their unique way of configuring the aforementioned sociotechnical affordances. It shifts its key components (e.g., which platform to prioritize) their interdependencies mostly due to economic and professional reasons. Creators are eager to construct the creator ecology based on the performance metric offered by the platforms [81]. Ibert et al. [65] are concerned that an ecological thinking might lack critical reflections on the power asymmetries in user-platform relationships and overstate the user agency when general platform users may have a partial understanding of the business models underlying the platforms. In the case of creator ecology, as presented in this study, we start to see creator agency and platform power not just as opposite forces but also a somewhat cooperative pair, where creators strive to be incorporated into and benefit from the platformization process.

6.2 The Labor for Maintaining Creator Ecology

While creators like our participants empower themselves by configuring the creator ecology, it is not easy to maintain. As the characteristic power asymmetry between creative labor and platform exists [8], the ways platforms govern or even “exploit” creators are apparent. For example, partnership programs do not indicate a pure “partner” relationship but a governance structure that privileges some users by different sets of rules and resources over others (e.g., YouTube [21,73]). Or platforms offer better resources to these monetized partnered creators than unpaid amateur ones [39,79]. In a similar vein, even though our participants can prioritize certain platforms over others for more diverse profit-making possibilities, they still tried to maintain their presence and retain audience attention on those less prioritized platforms. There could potentially be two reasons to explain such practice. First, participants did not want to miss chances of increasing audience engagement on multiple platforms since platforms (e.g., [85,86,111,129]) generally consider engagement performance important for distributing income (e.g., ad income, Creator Fund). Second, as our findings showed, participants desired to obtain more supportive, dedicated fans to directly receive money from them (e.g., subscription income on Twitch [106], Onlyfans [117], Patreon [60]) instead of depending heavily on the income paid by platforms (e.g., partnership programs). Thus, maintaining creator ecology indicates labor of both serving traditional platform economy models such as ad-supported content and, meanwhile, fueling creator or creative economy through connecting with individual fans or external advertisers across platforms [22,60,99].

Much prior work has also distilled another theme of labor, self-branding, from creators’ practices (e.g., [23,53,101]). It speaks to a self-promotional strategy, which is necessary but oftentimes uncompensated [37,53,63], to acquire reputation from people to secure employment in the freelance-based creative labor market [25,53]. This labor is apparent in creator ecology: participants promoted their profiles and content as well as transferred audiences across platforms. Beyond exclusively promoting by participants themselves, participants needed to intrigue other audiences to conduct participatory multi-platform branding [76,83] and further asked peer creators’ help for such promotion to sustain creator ecology.

However, due to the piecemeal, precarity nature of creator careers [39,56,91], our participants practiced more than branding. They needed to maintain audiences to sustain creator ecology, which speaks to relational labor, “an investment toward building and maintaining” audiences that helps sustain creator career [7]. Prior work has explored how microcelebrities practiced relational labor to construct intimacy with audiences on particular platforms such as YouTube [10,94], Patreon [59], and TikTok [104]. Our interviews further supplemented: creators practice relational labor on multiple platforms. Participants oftentimes engaged with cross-platform audiences in a consistent way, but sometimes, they needed to customize interactions with audiences to advance their relationships on certain platforms, like what P20 did.

Thus, the labor of maintaining creator ecology is plural; it involves participants’ interactions with platforms’ sociotechnical affordances under different platform economy environments. And one facet conspicuously reflected by such plural labor is participants’ cognitive efforts. For example, they needed to creatively synchronize content across platforms by empathizing and researching platform-specific audiences’ interests, sometimes along with the learning cost for technical affordances such as creator tools and algorithms [12,13,78]. Even, participants needed to conceive ways of avoiding content moderation to obtain dedicated fans from multiple platforms due to content or profile sensitivity, as what P13 did.

But if we view the plural labor of maintaining creator ecology as ideally manageable for each creator, then our participants’ creative practices tell the opposite of this view. Prior work has explored how content creators measure their perceived return on labor investment in self-branding [101] and relationship maintenance [60]. This is also similar to a trade-off process between labor investment and monetary gains that digital workers (e.g., Amazon Mechanical Turkers) need to go through [46]. Our participants’ creative practices helped elaborate on such trade-off process – weighing the benefits gained between selective labor investment and practicing labor as much as possible to maintain creator ecology. For instance, participants chose to selectively build up intimate relationships with a smaller number of audiences instead of trying to convert them all to dedicated fans. This practice might be explained by their personal availability or a mindset pre-defined by them, such as “TikTok, Instagram, Twitter, stuff like that, you're not going to have that connection,” as said by P8. Also, participants prioritized platforms they were more familiar with, instead of all, due to the predicted labor of drawing audiences on platforms they were relatively newer to. Hence, maintaining creator ecology is not easy not only because of the plural labor in it but also because creators need to go through the trade-off on investment return between selective labor across platforms and practicing labor as much as possible.

6.3 Design Considerations for Creator Support

Our findings suggest that our participants empowered themselves by configuring a creator ecology while platforms have different structural characteristics (e.g., governance [28], affordances [65]). However, their creative practices, such as content synchronization or audience management across platforms, did not simply indicate that every creator can exert agency to do so. So, we call for designs that can empower and support creators to continue working across platforms.

First, designers from single, particular platforms could consider a mindset of creator ecology in offering features for content synchronization across platforms. For example, our participants segmented their longer videos or live streaming recordings into several pieces to be posted on short-form video platforms such as Facebook (reels) or TikTok. To better support such practice, platforms can not only offer functions that can help split videos [105,116] but also suggest which moments within videos are appealing for segmentation. Designing this feature is creator-centered and, meanwhile, benefits platforms with more audience engagement by motivating creators’ passion for content synchronization and re-creation. Third parties like researchers could also design tools to support advanced creativity in content synchronization. Such tools could offer content re-creation suggestions by emotional, engaging keywords detection on creators’ speech content, higher audio frequency in audio spectrum visualization, or platform-specific audience interests inputted by creators beforehand. Then, similar to how artists distribute music content across platforms through Distrokid [33], content creators can distribute their curated content across platforms all at once. This design ideation could potentially streamline content synchronization processes and decrease creators’ labor of maintaining creator ecology.

Second, creativity support tools could be designed to help creators know better about their audiences across platforms. To support creators to thrive in the creator economy [56], platforms like YouTube [131], Twitch [115], TikTok [112], and more make efforts to offer content performance analytics as useful and sufficient as possible. However, our participants showed their desire to understand the effects of audience transfer and conversion across platforms. First, this speaks to a design opportunity of showing traffic source compositions leading to the content. As we notice from the creator tools in the market so far, YouTube and Twitch provide such feature, while Facebook, TikTok, and Instagram have not done so yet. Second, creator tools could consider informing creators of which audiences are their dedicated fans by analyzing engagement rate or financial support level (if there is a direct fan donation model on particular platforms like YouTube Giving, or subscription on Twitch) to support creators. This design could benefit platforms as well. If platforms design a “super fans” badge that allows audiences to associate it with creators, it can potentially intrigue more audience engagements on platforms.

Last, our participants’ creative practices indicate possibilities of creator career training to support creators. If platforms advance creator tools, while creators are not aware or lack the knowledge to use them, creators can hardly exert their agency to maintain creator ecology. Also, if platforms want to gain more audiences’ time spent on consuming content while offering creators low-quality onboarding experiences to understand social engagement designs, creators (e.g., P19) might not make a try to draw new audiences on certain platforms. Thus, offering creator career training, namely more information provision on how to thrive on platforms, can help stabilize creators’ income and careers.

7 Limitations and Future Work

Our qualitative study aims to uncover creative practices of how creators configure creator ecology. Thus, the 21 creators we interviewed cannot represent all creators in terms of practices across platforms. We also do not aim to make claims about how creative practices are associated with whatever fanbase size, career length, partnership programs, and content genres. But beyond a qualitative perspective, we did see the possibility for future work on understanding how creators work across platforms through surveys or large-scale analysis on metadata of the content.

Also, we do not aim to specify whether content synchronization violates platform-specific policies or ethical norms across platforms. Even though our participants barely discussed this as an issue, as researchers, we do acknowledge it might be tricky and intricate to view or define the legitimacy of content synchronization. Thus, future work can explore how creators, platforms, and policymakers conceptualize the content synchronization phenomena.

8 Conclusion

Our study enunciates a notion of creator ecology through creators’ practices on multiple platforms. This creator-centered notion describes an ecosystem where creators conduct different creative practices through the flexible, dynamic management of multiple platforms and their affordances and audiences to empower themselves through such cross-platform management. Due to the precarious or uncertain nature of creator careers, configuring creator ecology could help stabilize creators’ income by prioritizing certain platforms over others, synchronizing content across platforms, and managing audiences, and converting them to dedicated fans. However, creator ecology configuration does not refer to a one-time manner practice but the consistent labor for maintaining it. And it further requires creators to go through a trade-off on investment return between selective labor across platforms and practicing labor as much as possible. In the case of creator ecology as presented by our study, we start to see creator agency and platform power not just as opposite forces but also a somewhat cooperative pair, where creators strive to benefit from the platformization process. We thus call for more designs that can empower and support creators to continue working across platforms.

Acknowledgments

This work is partially supported by NSF grant no. 2006854. We appreciate all anonymous reviewers’ constructive feedback to make this work refined and improved. We also thank 21 cross-platform content creators’ support and participation in this study. The first author thanks Dr. Patrick Doyle for the mentorship and internship in SiriusXM and Pandora that allowed him to gain better understanding of digital streaming platforms and creator-fan relationships.

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References

[1]

Crystal Abidin. 2016. “Aren't These Just Young, Rich Women Doing Vain Things Online?”: Influencer Selfies as Subversive Frivolity: Soc Media Soc 2, 2 (April 2016).

Abstract

1 Introduction

2 Related Work

2.1 Content Creation as Digital Labor

2.2 Interacting with Multiple Platforms

3 Methods

3.1 Data Collection

3.2 Data Analysis

3.2.1 Researcher Positionality

4 Background: Content Format, Creator Tools, and Creator Economy

5 Findings

5.1 Prioritization

5.1.1 Professionalization

5.1.2 Audience Connection Scope

5.1.3 Content Type

5.1.4 Cost of Content-related Work

5.1.5 Dynamic Prioritization

5.2 Cross-platform Content Synchronization

5.2.1 Sequential Workflow based on Creator Tools

5.2.2 Platform-specific Content Curation

5.3 Multi-platform Audience Management

5.3.1 Maintaining cross-platform Audiences

5.3.2 Cross-platform Audience Transfer

5.3.3 Dedicated Fan Conversion

6 Discussion

6.1 Configuring the Creator Ecology for Multi-Platform Content Creation

6.2 The Labor for Maintaining Creator Ecology

6.3 Design Considerations for Creator Support

7 Limitations and Future Work

8 Conclusion

Acknowledgments

Supplementary Material

References

Cited By

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