“If You Like This Video, Support me on Patreon”: An Investigation of Content Creators’ Experiences with Patreon’s Membership Model

University of Amsterdam

M.A.- New Media & Digital Culture

Thesis

“If You Like This Video, Support me on Patreon”:

An Investigation of Content Creators’ Experiences with

Patreon’s Membership Model

Cem Akça

12532517

Supervisor Second Reader

Niels Van Doorn Natalia Sánchez-Querubín

Abstract

This thesis analyzes Patreon in the context of platformization and discusses Patreon’s influence on the labor of content creators. (GAFAM) platforms, Google, Amazon, Facebook, Apple and Microsoft dominate the web and put content creators in a position of dependency. As platformization of cultural production (Nieborg & Poell) discuss, platforms influence cultural production with economical and infrastructural power. Creators shape their production based on platforms guidelines and structure, and their labor are precarious: they have unpredictable, low income from ad-revenues on partnership models like on YouTube, and they face opaque moderation guidelines. Patreon is a membership-platform with over 182.000 creators. It works by creators receiving monthly payments from fans, as creators offer them benefits and perks. The first aim of this paper was to analyze what Patreon offers as value and how it is similar and different to other platforms. The second aim was to discuss how Patreon influences the labor of creators that operate across platforms. This research employed a walkthrough and online semi-structured interviews with 7 content creators that operate on Patreon. The findings showed what Patreon offers as value is what is lacking on GAFAM platforms: niche communities without algorithms and trolls, predictable monthly income, creator support. However, findings showed Patreon is not distant from the rest of the platforms. For success on Patreon, creators need to be successful on other platforms which pushes them to engage in visibility labor exist. Creators' success depends on the happiness of their paying fans, so they engage in emotional labor, and their workload is increased to fit Patreon in their cross-platform strategies. The large majority are making less than what they make on YouTube. Thus, while Patreon affords certain values for creators, it is not enough to solve the wider problem creators that occur out of platformization.

Acknowledgements

First of all, I am thankful to the interviewees who took their time to share their experiences with me and made this research possible.

I would like to thank Dr. Niels Van Doorn for his constructive feedback and encouragement throughout the research process.

I would like to thank my parents for their unconditional love and support since day one. Finally, I would like to thank my girlfriend Öykü, for inspiring me with her work ethic and for always believing in me.

Table of Contents

1. INTRODUCTION………...…....5

2. THEORETICAL FRAMEWORK……...……….10

2.1 Web 2.0 & Platformization of the Web.…..……….10

2.2 Platformization of Cultural Production ……….…. 13

2.3 Affordances of UGC Platforms………...………….15

2.4 Professionalizing UGC……….17

2.5 Content Creators and Their Labor………19

3. METHODOLOGY………..……….24

3.1 Case Study: Patreon………..24

3.2 Interviewing………..25

3.3 Semi-Structured Interviews……….……..26

3.4 Participants and Recruitment………....……27

3.5 Conducting Interviews.….………...……….……30

3.6 After the Interviews: Content Analysis……….………....31

3.7 Walkthrough Method………...……….……33

4. ANALYSIS…..…...……….………..…….34

4.1 Ad-Based Model vs. Membership Model……….34

4.2 Mass Audience vs Niche Community……….……..42

4.3 Fans Turning into Patrons……….48

4.4 Governance, Moderation & Support……….52

5. CONCLUSION…..……….………..…….60

1. INTRODUCTION

It came as a quite bit of shock to users when it was trending on social media that 13-year-old YouTuber Ryan Kaji made 28 million dollars on YouTube in 2019 (Berg). Kaji is only one of the thousands of YouTubers who earn money through producing videos. Many creators make use of the ‘partnership program’ of YouTube, in which they make use of the tools and services YouTube offers to them, and they are able to monetize their videos. Monetization refers to users earning money by enabling YouTube to show advertisement on their videos (Welsch). Being a YouTuber became a prominent thing especially in 2010’s with many creators rising to fame and generating income (Arnold).

Not only YouTube, but there has been rise in people who use different platforms to earn money, and they are named differently, such as ‘influencers, streamers, bloggers’ etc. Digital platforms like YouTube, Twitch, Instagram, Facebook, Snapchat and others, created economic and social opportunities for users. What started with only a few creators like Casey Neistat, Logan Paul or PewdiePie has created a huge wave of creators that rose to stardom and generated revenues (Berg). These users who produce content on digital platforms are widely referred to as content creators. From gamers to podcast creators to freelance journalists, digital platforms have been popular among people looking for ways to earn money via creating content. Many surveys show that teens prefer becoming creators than pursuing traditional careers (Locke).

However, there is another side to this content creation economy. Millions of creators that rely on platforms to produce and distribute their content, and many of them does not make enough money to pursue it as full-time jobs. As creators rely on advertising-based income and brand partnerships, their income is unpredictable and not sufficient. YouTube and Twitch requires certain view times and number of subscribers to even be eligible for partnership programs. For creators who seek brand partnerships, there is a large competition with other creators for having more likes, followers etc. Therefore, creators develop cross-platform strategies and work on multiple platforms to increase their income via reaching wider audiences. However, every platform they create content on, they also have to deal with the ever-changing and opaque guidelines of that platform. For example, demonetization is a recent issue

that comes up in YouTube (Robertson). YouTube could demonetize videos and channels, which means YouTube management banning a video or channel from earning advertising money. (Robertson) Creators also criticize platforms for not being transparent enough with how their algorithms work, which determines the visibility and income of creators (Bishop). Therefore, content creators are looking for new ways for income besides ad-based income that platforms offer which is highly precarious, unpredictable and not transparent.

It is not easy for creators to find alternative platforms to produce or distribute their content. There are only a few major platforms, (Google, Amazon, Facebook, Apple, Microsoft) GAFAM, and they influence the cultural production and distribution. These platforms, from how they organize their metrics, algorithms, interface, tools to how they arrange the payment structures, influence the labor of creators. It is difficult for creators to escape these platforms, since these few platforms are the few platforms with highest user numbers. This puts the content creators in a position of dependency, and it forces the creators to adapt their production strategies based on the platform’s models (Nieborg & Poell, 2019). Nieborg & Poell contextualize this as the platformization of cultural production, where cultural production is dependent on a few digital platforms, owned by a few corporations (pp.1). As creators are put in a position of dependency, they shape their production and distribution to fit the guidelines of platforms. Furthermore, it is best to think of platforms as not individual things but as an ‘integrated platform ecosystem’, where few powerful platforms are connected in an interrelational and dynamic structure. (van Dijck et al., 2019).

Creators employ different methods to increase their income on this ecosystem of platforms. One popular thing is to join another platform called Patreon. Patron has been gaining popularity, as many YouTubers started to make Patron visible at the end of their videos. Youtubers call out their subscribers to go to their Patreon accounts and they ask them to support them on Patreon. Since then, many creators from different platforms joined Patreon, boosting the platforms popularity. Patreon is a platform that is found in 2013 by Jack Conte, also an ex-Youtuber who was unhappy with the ad-revenues. Patreon offers creators to earn money not from ad-revenues, but creators receive monthly direct payments from their fans. Patreon could essentially be considered a ‘crowdsourcing’ platform, similar to Kickstarter or Gofundme.com, however, instead of people supporting a one-time campaign or a project, they support a creator continuously (Robertson). Patreon is ‘loosely modeled’ on the Patronage system that goes back to the Renaissance, where rich art lovers such as the Medici family would support the artist

financially and make them create art (Robertson). Thus, Patreon turns subscribers or fans into patrons. Patrons financially support the content creators through paying monthly fees to them by selecting a tier that creator offers to them. As they select a tier, they pay monthly fees to creator and get exclusive benefits such as early access to videos (Patreon). Patreon thus not have algorithms, trending sections or explore sections, as it is made for membership and exclusive relationships.

Founder of Patreon Conte discusses that Patreon aims to change the system and bring creators out of the ‘dark ages of the attention economy and into the next phase of the web’ (Conte). As Patreon founder openly criticizes the attention economy and the ad-based platforms where creators and their income are at stake, he argues the membership model will ‘democratize creator salary’ and help ‘manage and grow your community’ (Conte). There are now over 184.000 users on Patreon (Graphtreon). It has been widely popular since 2013, as it proposed a sense of ‘disruptiveness’ to the ecosystem of digital platforms. Patreon garnered notable media attention: demonetized and deplatformed figures have joined the platform (Gilbert), NSFW creators were able to monetize their content (Plaugic). In 2020, platforms popularity is rising especially during the Covid-19 pandemic (Perez), where people are increasingly looking for ways for additional income. As Patreon has the promise of ‘funding the creative class’, it becomes necessary to discuss where Patreon stands in this ecosystem, and what it actually enables creators to do.

Many scholars in the field of media studies have been interested issues related to platforms and user-generated content. In terms of taking a political economy approach to the study of digital platforms, many have studied how platforms act as intermediaries that manages multiple parties (Gillespie), how platforms code connections and how they generate value out of user activities (Van Dijck, Poell, Sadowski), or how platforms maintain a privileged position with the data they control (Srnicek), (Zuboff). Furthermore, scholars have studied how platforms features enable different things to different to users through what is called affordances (Taina & Bucher), and the cross-platform strategies of creators through how they engage in self-branding activities (Abidin), (Heart). In relation to these dynamics and rising influence platforms, scholars have raised attention to how platforms are turning into infrastructures (Plantin), how there is an ecosystem of platforms that are technically and economocially integrated and controlled by a few big corporations (Van Dijck et al), and how platforms technically platformize the web with their decentralized data collection (Helmond). Most

relevantly to this thesis, scholars have paid attention to the platforms influence on the cultural production and distribution (Nieborg & Poell). This thesis makes use of these literatures, but also aims to make a contribution to this field by discussing something new.

Platformization of cultural production (Nieborg & Poell) creates the base of the thesis’s argument and lays the ground for theorizing the dominance of platforms in cultural content production. Nieborg & Poell and many other sources discuss the advertising-based model, data collection, usage of algorithms, and all of these characteristics that platforms employ when they talk about the structure of the platforms. Both in press and in academia, many people call out platforms for discriminative guidelines, not-transparent moderation, and demand better revenue systems for content creators (Alexander). However, no one have yet analyzed the most influential platform that have promoted itself as a solution: Patreon, a platform that is actually used by over 184.000 content creators who are subject to this platformization. Thus, I believe Patreon needs to be included in the wider discussion of platforms and platformization.

In my research, first I aim to lay out what Patreon really is as a platform and understand what it proposes to creators as value. Second, I aim to analyze what Patreon affords for creators who are subject to platformization of cultural production, by discussing creators experience with the platform. Analyzing what Patreon changes positively for creators and what it also does negatively could lead to new insights on creators’ labor and in the discussion in the platformization of cultural production. Thus, I ask two research questions.

• What is the value proposition of Patreon and how does it fit within the wider ecosystem of platforms?

• How does Patreon influence the labor of content creators that operate across different platforms?

To answer my research questions, I will conduct a mixed-method approach, which includes a walkthrough on Patreon and interview 7 content creators who use Patreon and other platforms. 5 of the interviewees are YouTubers, the others are podcaster and investigative writer. Walkthrough method was conducted to analyze what Patreon really is as a platform and what it offers as value, and how it presents itself to the public. This method entails visually breaking down most important features of the platform through its interface and conducting a

step by step usage of the platform (Light et al.). Second methodology I conducted is semi-structured interviews. Interviews was conducted to understand the experiences of content creators with the platform. It is also conducted to learn their personal opinions and insights about using Patreon within their cross-platform strategies. The second research question was something I could not answer because I would not be able to speak on creator’s behalf as I do not have the experience. Thus, 7 content creators were recruited as interviewees, and online semi-structured interviews were conducted online.

In the upcoming chapter, I will do a literature review and elaborate on the relevant materials about platforms, content creators and platformization. This will allow me to connect Patreon, the object I have picked, to the relevant literature. Only then I will be able to analyze where Patreon stands in relation to the platform ecosystem and discuss how it connects and contributes to the relevant debates in academia. Furthermore, to be able to understand what Patreon changes in labor of content creators that operate in the platform ecosystem, it is first necessary to elaborate on how creators currently operate. This could also be done with looking at relevant literature on content creators labor on platforms. Thus, theoretical framework will be conducted for these reasons in the upcoming chapter.

In the methodology chapter, I will elaborate on my mixed-method approach. This will include discussing the steps of walkthrough. Also, it will include the steps for semi-structured interviews. I have interviewed 7 content creators from different age groups: British, American, Turkish, and Dutch. 5 of them were YouTubers, one podcaster and one writer-journalist. Each had differing number of subscribers, from 4K to 160K at the time of the interviews. In the analysis chapter, I will conduct my analysis that is guided by my theoretical framework and my research question. This analysis will aim to present the most significant parts of the interviews in sub-sections and connect them to both relevant literature and the secondary material, which I will include such as web articles, blog posts etc. In this chapter, I will use all the relevant and significant material that I have from my literature review, walkthrough, interviews, secondary sources. Then, I will make connections, find conflicts and make arguments relevant to my research question. In the conclusion section, I will discuss how the analysis replies to my research questions. I will discuss the key findings I have obtained as a result of my research and show the relevant and important outcomes in connection to my research questions.. Then, I will connect my research to academia and argue how this research contributes to a wider discussion. Finally, I will discuss possible future topics that this research might inspire.

2. THEORETICAL FRAMEWORK

In this chapter, first, I will discuss what platforms are and how they are structured, and how they generate value out of data and manage multiple parties. I will discuss how the rise of platforms have caused platformization of both web and cultural production. After that, I will discuss how platforms have turned amateur user-generated content into systematic and professional content creation. This will allow me to discuss the ad-based revenue partnerships. After elaborating on opportunities and struggles of content creators, I will then be able to make a connection to describing Patreon as a proposed alternative income model for creators.

2.1 Web 2.0 & Platformization of the Web

With the popularity of Web 2.0 in the 2000’s, web has transformed in influential ways. Web 2.0 is a term that roughly refers to how web is structured, and it was popularized by Tim O'Reilly and Dale Dougherty at the O'Reilly Media Web 2.0 Conference in late 2004 (Auchard). Web 2.0 is described as an infrastructure to build applications on, a ‘distributed operating system that could deliver software services’ (Helmond). Web 2.0 created the basis of the web we use today, programmable, interactive and dominated by platforms and user-generated content. The architecture is rooted on a social software where users generate content rather than only consuming it, and on open-programming interfaces that enables developers to add a web service or get at data (O’Reilly). This enabled user-generated content to dominate internet and to practices like blogging and online communities, and social media platforms. The rules of the game have changed, and internet has become a place for collaboration and participation, which users are treated as co-developers and co-creators of content. Scholars emphasized this era with terms as ‘participatory culture’ (Jenkins). Web 2.0 is popularly defined with words such as ‘interactivity’ and ‘participatory’, as these words refer to the Web 2.0’s character allowing users to ‘talk back’ and send messages instantly compared to the old media which was one-way or had broadcasting channels.” (Van Dijck, 10).

The technical structure and philosophy behind Web 2.0 created opportunities for everyone, new services were created. These services were more often than not, built within communities such as college students, group of photography enthusiasts etc, “who adopted a specific niche of online interaction and developed a “mediated routine practice” (Van Dijck, 6). A good

example is Facebook, a platform created by a college student in his dorm room, enabling fellow students to meet and socialize. From mid 2000’s and onwards, internet became dominated by platforms: Myspace, Facebook, Twitter, Instagram, Reddit, Youtube, Google, Amazon and others. These platforms have changed the nature of internet and how we communicate online. Platforms are “digital infrastructures that enable two or more groups to interact”, which enables them to “position their selves as intermediaries” (Srnicek, 25). Platforms bring multiple parties together such as advertisers, users, banking partners, legal parties and others, and gives these that enables them to “build their own products, services or marketplace” (Srnicek, 25).

Van Dijck discusses that web 2.0 led to making society more technical and enabled platforms to render user activities “formal, manageable and manipulable” influencing the sociality in people’s everyday lives. (Van Dijck, 12). In other words, platforms “bind pre-defined communicative acts to an economic logic, such as liking or sharing providing both expression for the user and also facilitating data for the platform” (Plantin, 297). Therefore, socializing, connectedness and human activities are all turning into economic value. O’Reilly discusses that the web 2.0 is not only about social networking and blogging and wikis but it is about the data that’ is created by those mechanisms and the businesses that data will make possible (Tweney). Platforms are those businesses that is made possible with the data. As people use platforms for different activities, they have moved their everyday activities to online environments.

In platforms user activities “were not simply channeled by the platform, but they were programmed with a specific objective” (Van Dijck, 6). Because users are not willing to provide data about their preferences and habits, platforms develop algorithms and system to track user activities and learn preferences that could be of value. O’Reilly discusses that not many users will add value explicitly, so web 2.0 companies set systems for generating value out of ordinary user activities (O’Reilly). Thus, the key lesson of web 2.0 is indeed treating data as the value generator. In order to platforms to generate value, they need data. To acquire data, platforms create systems and models that enable users to generate content.

In a business model which requires extracting value from users, platforms engage in different activities to maintain these negotiations. Platforms are situated as ‘multisided markets’ because of how they bring different parties together (Nieborg & Poell, 4275). Van Dijck defines platforms as a “set of relations that constantly needs to be performed” because of the ‘continual

friction’ between users’ goals of expressions, and on the other side, platforms’ profit seeking aims and the legal surround that define legitimate use (Van Dijck, 26). Gillespie also brings attention the multi-party structure of platforms to critically discuss how this managing of multiple parties influence the agency of users as he mentions that “platforms are specific enough to mean something, and vague enough to work across multiple venues for multiple audiences” (Gillespie, 349). These multiple audiences are users, advertisers, developers, or legal parties. Especially after the increasing demand for transparency in platforms, there is a constant negotiation going on within parties. As platforms positions itself 1) between users and, 2) as the ground upon which these activities occur, platform gives itself a “privileged position” (Srnicek). The platforms’ position is privileged because of the power and information it holds against the users. Users have limited knowledge on how their activity is commodified and sold to advertisers or turned into value in other ways. While platforms promise their users certain aspects, they make sure their offering are in line with their business.

The extension of platforms into web infrastructure is best discussed by Helmond as the platformization of the web. Platformization of the web refers to the rise of the platform as the dominant infrastructural and economical model of the social web and its consequences and refers as the “extension of social media platforms into the rest of the web and their drive to make external web data “platform ready” (Helmond, 1). This refers to the programmability: it is about how platforms enable the collection of data from the web with the programmability of their API’s and plug-ins. Helmond discusses API and programmability as the central differentiator when talking about a service as a platform, and argues that in order to become a platform, one needs to “provide an interface that allows for its reprogramming, the API” (Helmond, 2). The API, or the software interface in less technical terms, allows the website to be programmable “by offering structured access to its data and functionality and turns it into a platform that others can build on” (Helmond, 2).

This generates value for the platform as developers can add additional features or services that could be used within the platform by users. However, this programmability is also highly problematic in terms of data and user privacy. Helmond gives the example of Facebook, and when one user logs in to an external web site with their Facebook login, how Facebook is able to collect the data of the users activities, therefore, creating a web structure where a platform is able to trace activities and collect data of the activities that is happening somewhere else on the web but the platform itself. This enable platforms to ‘decentralize data production and

recentralize data collection’ (Gerlitz & Helmond, 5). This is important to discuss since the data platforms collect are essential to their business, and essentially, turning the web into a ‘platformized web’ means platforms being able to trace, know or predict user activities more accurately, constantly and in a decentralized way, in order to generate more data and turn that data into economic value for their platforms.

2.2 Platformization of Cultural Production

The other type of platformization that I discuss is the platformization of cultural production, and it refers to the “change in the political economy of the cultural industries through platformization: the penetration of economic and infrastructural extensions of online platforms into the web, affecting the production, distribution, and circulation of cultural content” (Nieborg & Poell, 4276). The platformization of cultural production is situated as a problematic issue in two ways: “(1) the inherent accumulative tendency of capital and corporate ownership and its subsequent effect on the distribution of power and (2) the precarious and exploitative nature of cultural and immaterial labor of both producers and end users (p. 4279). Cultural production happens mostly on a selected couple of platforms, and these platforms shape cultural production with their business structures, network effects, intermediary roles. This theory argues that with the current ecosystem of platforms, the cultural production has become dependent on a select group of powerful digital platforms, which are namely (GAFAM), Google, Apple, Facebook, Amazon and Microsoft (p, 4276). Platforms aim to increase their control and power on cultural practices, as they represent a ‘centralized, proprietary mode of cultural production’ and advance on “the project of control” and its two pillars of “commercialization and corporate concentration” (p. 4279). Platforms influence the industry of cultural production and distribution as they control the channels and infrastructure. Many of the platforms are owned by same few big corporations, and their aim is hosting advertising and making profit out of the cultural production.

Nieborg & Poell discuss the influence of this platformization and the capitalist structure on the cultural work, which is argued along as “commodification of content, exploitation of cultural labor, and immaterial labor of users (p. 4279), as cultural producers and their labor are vividly influenced by this structure. Thus, platformization “fundamentally changes the economic and institutional configuration in which cultural production takes shape, as content producers are always in a position of dependency” (p. 4279). Cultural producers are dependent

to the platforms to be able to produce content that would reach wider audiences. Creative work and cultural industries blend to each other, as scholars interested in cultural industries ‘point to the growth of the particular industries that produce cultural outputs’ (Gill & Pratt, 2), as a result, ‘creative industries’ become the rebranding of ‘cultural industries’ (Gill & Pratt, 2) Artists, new media workers, cultural workers, musicians and others who produce creative work are considered cultural producers.

Content creators are users who create content online whether it is videos, songs, comments, photos, drawings, adult content etc., by using the technical infrastructure and the opportunities that platforms afford them. While content creators are usually framed as the new generation workers with entrepreneurial tendencies, they share the similar struggles that traditional cultural producers are subject to. Cultural producers are discussed as ‘model entrepreneurs’, they are the symbol of moving from stable careers to informal and insecure employment, they are the representatives of ‘brave new world of work’ in which risks must be borne solely by the individual, and this type of work is seen as precarious: “insecure, contingent, flexible, illegalized, casualized, temporary employment, freelancing etc.” (Gill & Pratt, 3). Thus, the cultural production online, which I discuss as ‘content creation’, is discussed as a highly precarious type of work as similar to other cultural work.

In the platform ecosystem, which could be described as big five platforms being connected to each other economically and technically, ownership relations and data flows are integrated to each other (Van Dijck & Poell). Major GAFAM platforms dominate this ecosystem and there are problems for creators, as Nieborg and Poell discuss, “as cultural production is becoming increasingly platform dependent, the autonomy and economic sustainability of particular forms of cultural production is increasingly compromised” (Nieborg & Poell, 4277). As the cultural production becomes dependent to these platforms structures, policies and decisions, platforms have the power to influence the arrangements and dynamics of content creation that takes online. With the transformation of markets into multi-sided markets which “triggers new economic mechanisms and managerial strategies” cultural producers are “impelled to develop publishing strategies that are aligned with the business models of platforms” (p.4281). Creators are forced to create content publishing strategies around a few intermediary platforms with ever-evolving business management and different business models, technical structures and interfaces. Such as when a creator creates content on

YouTube, they go to Facebook, Instagram, Snapchat, Twitch to reach more people and this cross-platform work requires taking account multiple things shaped by platforms.

Second, platforms use “political economic and infrastructural control over relations between complementors and end-users” which results in platforms governing and moderating the cultural work (p. 4281). Thus, creators are subject to guidelines and moderation by these platforms and their labor are governed by the platforms management and strategies. As a result, the cultural production happens through the enabling of ideologies and business models of couple of platforms. Creators operate on platforms which offer partnership models, and they are the main business that creators go to create content since it enables them to distribute their content to billions of users, giving them an opportunity to expand their visibility. I will expand on this and understand how creators are influenced by this structure.

2.3 Affordances of UGC Platforms

Platforms rely on its users as platforms arrange the economical, technical and social structure to enable users to generate content, as it employs “web and mobile based technologies to create highly interactive platforms which individuals and communities share, co-create, discuss and modify user-generated content” (Kietzman et al. 241). Users depend on platforms structures to produce and distribute content, enabled through what platforms offer to them, which I discuss as ‘affordances’ (Bucher & Helmond). Different platforms and different features in each platform afford things to users based on their motivation and perception.

Affordances theory roots from ecological psychology, argued by James j Gibson as “what the environment offers the animal, what it provides or furnishes, either for good or ill” (127) (Gibson). Affordances is defined as “the range of functions and constraints that an object provides for, and places upon, structurally situated subjects” (241). Thus, affordances can provide the limits and opportunities for users and their understanding of what they can do with a certain technology. As affordances refer to what “media artifacts allow people to do” (Bucher & Helmond) it means users giving range of meaning and purposes the tools and services offered by platforms and they can use them based on their perception. ‘Perceived affordance’ is very important when discussing affordances in the sense of digital platforms, as ‘the perceived and actual properties of the thing, primarily those fundamental properties that determine just how the thing could possibly be used’ (Bucher & Helmond).

YouTube provides the same tools to everyone, but users perceive these differently: some make use of the Partnership program and become professional content creators, and use liking, subscribing and video sharing features as metrics in a business model, others could only consume the content for entertainment the same tools these people use to create professional content. Twitter could be empowering in social protests for some, and it could be a way for personal branding for others. (Postigo, 335) Technology allows certain things, but people perceive services and features differently based on what meaning they give to them and why and how they use them: what something affords to them. How people use, talk about and how they view ‘what the technology was meant to do’ is defined by “individual and community needs, social problems, and life histories” (Postigo, 336). Expanding into the affordance’s notion, I will discuss the boundaries between a user and a professional content creator and argue that platforms afford users to be professional creators for their corporate gains.

Affordances could be split into two: technological affordances and social affordances (Postigo, 335). Technological affordances is what technology makes possible, such as making long-distance phone calls with the invention of the telephone or being able to send e-mails on a smartphone; whilst social affordances are ‘social structures that take shape in association with a given technical structure’, such as phone changing the perception of distance and reshaping markets (Postigo, 336). Expanding from the YouTube example, the market system becomes a ‘strong driver’ in YouTubes affordance structure as it demands of designers to “make a space where people can share video and socialize around it, and where the owners of system can turn a profit from it with minimum work in doing so” (Postigo, 336). Thus, the key technological affordances for YouTube are those that allow for profit maximization, but from the users’ perspective, “those same affordances (social and technological) can mean similar or entirely different things” (Postigo, 336). Thus, platforms create the technological models, services, tools, features in a way that would allow them to maximize their profit and generate value. Those same technological artifacts, whether it is a button or a service, affords different things for different users.

Evolution from cat videos to having a few major platforms that offer partnership models to users who want to establish creative careers is big, and I refer to it as ‘professionalizing’ content creation. Platforms designed a structure to turn the content creation into a sustainable, data-generating, governable business, instead of decentralized and unstable production:

affording users to turn into professionalized content creators. While this turns into value for the platform, mainly through advertising models, this system creates economic and social opportunities for the content producer as well.

2.4 Professionalizing User-Generated Content

The shift from amateur to professional was systematically structured by platforms. YouTube started out as a video-sharing site for user-generated content “only produced by amateurs without commercial interests” (Gerhards, 517). Within the frame of participatory culture and users as ‘produsers’, the first videos on YouTube were uploaded randomly, and there was no system to monetize videos. When YouTube was bought by Google in 2007, it turned into a ‘hybrid commercial space’, where “user-generated content production is efficiently tied to forms of monetization” (Arthurs et al., 7). As YouTube introduced features after it has been bought by the corporate giant Google, they employed an ‘advertising model that facilitates new forms of monetization based on the engagement of users” and YouTube’s technical affordances “enable a smooth translation from distribution of videos and channels into shared revenues through the affective-based monetization enabled by features of the platform architecture” (Arthurs et al., 7). YouTube has built revenue systems where content creators could earn cut from advertising revenue. As for platforms user participation is the ‘central function of service’, value creation happens via user activity and participation (Bechmann & Lomborg, 772). Thus, sustainable content creation and a pool of quality content where engagement, participation and advertising are built around becomes necessary for platforms.

For this purpose, YouTube employed different strategies as an intermediary to turn amateurs into professional content creators. Gradually, YouTube and its video creators “follow a process of professionalization that makes the video sharing site and its content more compatible with the interests of advertisers”, thus harnessing ‘user-led cultural production’ into ‘profit generation’. (Gerhards, 517)” This includes implementing new models, services, tools etc. The aim was to acquire consistent and high revenues through advertising, and it required higher quality videos, consistent and professional video production, which did not include any copyright violations unlike the amateur videos (Gerhards, 518). Thus, in 2007, Google launched content management tool (Video ID) and its YouTube ad revenue sharing Partner Program (Gerhards, 518). Both were aiming to increase the amount and quality of the professional

content on the platform and prevent copyright violations which resulted in videos being taken down.

As YouTube set opportunities for professionalizing and monetizing content creation, and with the increase in user numbers, at 2009, first content creator reached a million subscribers and content creation became a profession for individuals. (Gerhards, 518). After a period where mass media outlets used YouTubes partnership program, individual creators also started to establish follower bases and monetize it. Then, individuals who create content on platforms and found ways to monetize their content, reached followers and they made brands for themselves as content creators. As most creators start as amateurs, they are able to build careers thanks to the affordances, and platforms aim to skil-up these creators (Cunnigham & Craig, 1). Through offering creator, a network of highly active users, and offering tools and features for creators to be able run it as a bueiness, platform affordances turned users into professional content creators.

To be able to be a partner on YouTube and monetize content however, there are certain barriers and guidelines for creators. Creators need to accept the policies and guidelines of YouTube’s content production, live in a country where the program is available, have more than 4.000 valid public watch hours in the last 12 months, have more than 1.000 subscribers and have a linked AdSense account (Google Support). Thus, as in the case of YouTube, partnership programs require eligibility and they are not usually available for small or new creators. After creators are eligible to be partners, YouTube places ads automatically on videos of the creators, giving them share from the ad revenue platform makes, which was 15 billion dollars in 2019 (Verge). Also, through partnership guidelines that creators agree to, platforms able to govern and moderate the content of the creator, remove it, demonetize it, etc.

YouTube is not the only platform, though it pioneered turning amateur creators to professional creators, and created a new class of creators, which could reach millions and micro-celebrity status, as running popular channels is “no longer the business of only a few video creators, but become a widespread practice” (Gerhards, 519). For example, someone interested in gaming and streaming can join Twitch, Twitch is owned by Amazon and it is the largest gaming platform with 2 million streamers and 15 million users (Influencer Marketing Hub). By making use of Twitch affordances, and if eligible to join, a creator can join Affiliate program or the Partner Program and choose a plan to get revenue from advertising that is going to be

placed on his or her content (Twitch). These affordances would make the user than evolve into a content creator, who has more influence on a platform than the next user.

Thus, making use of platform affordances; partnership programs, creator support, and other features and tools, content creators can professionalize and generate income and try and maintain this as a profession. Therefore, being a creator should be defined with certain entrepreneurial opportunities, as these creators collaborate with brands through promotional campaigns in the form of sponsored posts, videos, or product placements., as they build relationships with brands or third-party networks (Stold et al., 2). They are seen as “opinion leaders” and have a “predisposition to affect other consumption decisions” (Schwemmer & Ziewicki, 2). Thus, content-creators could generate value for their selves as they can engage in brand collaborations, sponsorships, advertising etc. Furthermore, they have an influence on their community which gives them a new status.

On the other side of the trade, platforms now have a steady line of supply where they are able to govern and moderate content, monetize it, avoid copyright or other violations, and have a quality, consistent and professional content where user activity could be built around and where data could be generated. In line with the platformization of cultural production, most of the cultural production online is dependent to these few platforms systems, and creators are dependent to go to these platforms and shape their content accordingly to each platform, if they want to reach more users (Nieborg & Poell). Besides each platform having their own guidelines and structures, platforms continuously change and re-negotiate their tools, services, programs based on its own profit and business model, which makes the creators labor precarious.

Furthermore, creators need to create their own self-brand to be successful among millions. As platforms only provide the ground for creators to create a business, creators need to be their own self-brand, find and reach their own followers, and consistently aim for engagement and activity to have sustainable advertising income, which is dependent on numerical metrics: view numbers, watch time, clicks etc. Thus, the professionalization influences how creators maintain their livings, and there are forms of labor they engage in to be successful in this platformization.

Everything online requires attention: increasingly fast scrolling timelines on Twitter, countless videos that are recommended to us on YouTube, new songs released every day on Spotify etc. “Michael Goldhaber argues that in new media as we watch, click, link and forward, we switch from being consumers to being producers of the most valuable resource of all: ‘attention’ (Senft, 5). After content creators are able to capture the attention, they create ‘engagement’ among the audience to enable the audience to participate through liking, sharing, commenting and subscribing or through other platform features. Thus, for content creators, attention and visibility and engagement emerge as the “core properties for accruing status and perceived influence”. (Senft, 2). As content creators are capturing the attention of users, the aim is to create long-term relationship and engagement with them, which than could mean improved metrics and opportunities for the creator. However, the sustainability of this model is tied to creator’s relationship with followers, as their income is influenced by the metrics and engagement.

Content creators are also defined as ‘micro-celebrities’, and this definition includes the self-branding activities that creators must engage in to build themselves an authentic reputation to be consumed by the audiences (Senft). Micro-celebrity place “particular emphasis on the construction of identity as a product to be consumed by others, and on interaction which treats the audience as an aggregated fan base to be developed and maintained in order to achieve social or economic benefit” (Page, 182). Thus, creators maintain an authentic self-brand to present to their following. Looking back to its origins in the field of media studies, micro-celebrity were first being used in a book about camgirls who were broadcasting their lives and it referred to the ways in how “camgirls utilized still images, videos, blogging and crosslinking strategies to present themselves as a coherent, branded packages to their online fans. (Senft, 1). Thus, while they aim to “get attention and popularity” (Lewis, 2013), they brand their selves to the audience to be followed, liked and valued, which will give them a status where they can build on as a self-brand. The strategies usually revolve around the “strategic development of intimacy with audiences, as well as the treatment of viewers and audiences specifically as fans” (Lewis, 203). The idea of a micro-celebrity resonates with Warhol’s idea in a different way, as “being famous to fifteen people”. (Senft, 4), each follower tries to build its own follower base and engage with them, and they try to present themselves as authentic, real, and intimate through self-branding.

Self-branding and authenticity are forms of immaterial labor undertaken by users who want to achieve visibility and influence (Page, 182). Content creator needs to continuously level up and maintain its digital reputation and be visible. So self-branding is an affective immaterial labor that is taken by users to earn attention and reputation (Hearn, 427). Theories of Immaterial labor demonstrates a “new relationship between the production and subjectivity” and suggest that “activities that contribute to the production of value are not restricted to paid employment” (Farrugia, 514). As creators work continuously on their image, their relationship with fans, besides creating content, they do forms of labor which are not always tied to an income. Immaterial Labor suggests that the ‘dissolution’ between what is work and what is not, between production and consumption and between the time of work and the time of leisure, “constitutes a key characteristic of post-Fordist economies and since immaterial labor ‘encompasses’ activities not recognized as work, the entire life, day to day activities, leisure time, all become a form of labor (p. 514). Anything that a content creator does to level up and develop its authenticity and self-brand could fall under the category of immaterial labor.

Content creators are also engaged in forms of emotional labor. Emotional labor is described as “regulating or managing emotional experiences as part of the work” (Hochshild). It means people presenting certain emotions in their professional interactions. For creators, keeping your follower base happy is part of the work as creators are constantly shaping and re-shaping their communicative messages and attitudes to be able to build emotional connections with them. While in the context of taxi driver or stewardesses, emotional labor could be in the form of bringing a smile and displaying positive emotions (Hochshild). For content creators emotional labor becomes a constant work needs to be performed as it is important to build relationships with fans.

As all social media platforms use algorithms, algorithms become crucial in creators’ labor as it influences their visibility. Our participation in public life since they show what information is considered most relevant to us (Gillespie, 167). Therefore, in many platforms algorithms are co-curators of content in terms of ranking and showing relevant results to users. Basically, algorithmic ranking decides what and who is visible on social media (Bucher). Thus, the visibility of users is influenced by these algorithms, since algorithms determine visibility through ranking systems, recommendations, for example picking videos for the trending section (Gorbatch). As algorithms play a part in determining the number of views a video will get for example, they also influence how much money a creator can make. YouTube for example uses

algorithm for giving users recommending relevant videos, ranking search results or placing videos in the trending section. YouTube determines what is visible to who (Bishop, 2590).

While platforms constantly tweak their algorithms that determine creator visibility, creators have no information about it, but they engage in algorithmic gossip, which could be described as “communally and socially informed knowledge about algorithms and algorithmic visibility” (Bishop, 2590). As there is no information on how these algorithms work, creators share gossip and information regarding the ways to be more visible. As a result, creators entangle with practice and re-shape their strategies based on platforms algorithms (Gillespie, 168). Therefore, algorithms and algorithmic management are one of the most important struggles for the content creators in the current system, and it becomes part of their immaterial labor, as dealing with algorithms becomes one of the key tricks if one wants to become visible.

Besides algorithms, moderation and governance schemes of platforms is another problematic aspect for content creators which influence their labor. While there is endless content being uploaded to every digital platform every day, there becomes a certain need for moderation of content to prevent harmful content to circulate, such as illegal pornography, copyrighted content, or violence or terrorism. Platforms moderate content in human and non-human ways: through moderators and artificial intelligence (Gorwa et al, 2). While this ideally presents a simple process of filtering and clearing out content that is against the rules and guidelines, the process is not always straightforward, and has consequences for creators.

While platforms make changes and adjust its policies to serve its own corporate interests, content moderation is also applied in a line with platform policies and decisions (Cunningham & Craig, 2). After what is called ‘Techlash’, which involved fake news, election hacking, privacy violations and more, platforms are started to be held accountable for their moderation and policy making (Cunningham & Craig, 2). Against the demand for openness, it is revealed that content moderation of digital platforms are hidden processes happening behind closed doors: content moderation is a precarious labor, as even in Facebook’s moderaters suffer mental health issues (Gillespie). Furthermore, artificial intelligence systems moderate content based on pre-determined codes, unknown to users. As these code change, why a video could be removed of the platform or denied advertising revenue change too. The content moderation systems of platforms remain “opaque, unaccountable and poorly understood” (Gorwa et al, 3).

Thus, content creators’ labor is dependent on human and non-human actors employed by the platform that moderate and govern content.

A recurring problem that happens because of poor content moderation is demonetization. Demonetization refers to when content creators are “denied paid advertisements in their video, thus denying them revenue and reducing their income from the video-hosting platform” (Thomson). Thus, platforms hold the right to demonetize a video because it goes against platform policies and guidelines, therefore, creators’ income and sustainability of their profession is dependent on these vague guidelines which are controversial and not consistent. It could be for so many different reasons: copyright, hate speech violation etc. When content is demonetized, it is still on the platform so it produces value for the platform by generating views. However, the creators are not able to earn money from it.

Demonetization gained popularity in what was called as Adpocalypse in 2016. Adpocalypse refers to YouTube “aggressively demonetizing videos that might be problematic, in an effort to prevent companies from halting their ad spending” (Alexander), and this gave advertisers power to opt out of videos that they found distasteful (Robertson). There are also words listed as against guidelines, and they automatically demonetize a video when included in a videos title. However, youtubers proved that this word list consists of words such as ‘gay’, ‘lesbian’, ‘666’, ‘adult’ etc., words which does not mean any wrongdoing by itself (Dodgson). The word list is constantly changing, and it is kept secret from creators, but only a few YouTube creators test this randomly. For example, a history teachers’ video on Nazi policies was demonetized for ‘hate speech’ because it contained speeches from Nazi propaganda (Waterson). Furthermore, LGBTQ content creators sued YouTube for discriminative demonetization instances (Alexander). Thus, demonetization is one of the biggest problems which influences YouTubers income, as it can prevent them from any ad revenue from their videos, leaving them with no income from a content they produced.

Another issue I would like to mention is deplatforming, which means removing someone’s account from the platform. It has been gaining popularity as a proposed solution to ‘toxicity of online communities and mainstreaming extreme speech’ (Rogers,1) Many right-wing or extremist figures such as Alex Jones, Milo Yiannopoulos etc., have been deplatformed, based on the grounds of promoting exclusion, segregation, discrimination, extremist speech, harmful misinformation and others (Hern). While deplatforming and its effectiveness is part of

a bigger discussion, platform moderation and governance on YouTube and other GAFAM platforms is not transparent and these opaque management decisions that constantly change.

Throughout this chapter, I have discussed relevant literature and built the theoretical framework that will help me answer my research questions. Theories discussed and laid out in this chapter aims to present a lens that will enable me to contextualize Patreon and creator interviews in a wider frame of platforms and cultural production. In the next section, I will elaborate on how I have decided on methodologies and how they were conducted.

3. METHODOLOGY

3.1 Case Study: Patreon

As my research questions and my main interest pertain to Patreon and content creators who use Patreon together with other platforms, I will analyze Patreon as a case study, as a proposed alternative to the problems for creators’ problems in the platformization of cultural production. My research question is interested in both the platform, and the experience of creators who use the platform, as my research questions are: 1) What is the value proposition

of Patreon and how does it fit within the wider ecosystem of platforms? 2) How does Patreon influence the labor of content creators who operate across multiple platforms? Thus, these

questions required me to generate qualitative knowledge.

First, I am interested in analyzing Patreon platform from a software-studies perspective: how it works, what kinds of tools, features, services it offers and it’s interface. Only analyzing these, I will be able to discuss what Patreon offers as value to creators. Therefore, to be able to answer this first research question, I have conducted a Walkthrough Method (Light, 2018). Walkthrough is more of a visual and technical breakdown of the platform that expands on its everyday usage. Conducting this analysis of how Patreon works enabled enable me to see how Patreon functions, and also enabled me to discuss the promoted distinctiveness of Patreons model in the platform ecosystem.

Second, I am mainly interested in the experiences and insights of content creators who are active on Patreon. This also requires me to generate qualitative knowledge since I want to find out the personal experience and opinions of creators. Thus, while the first question is to study the platform, the second question is to study the relationship of creators with this platform.

For this purpose, I will conduct semi-structured interviews with seven creators who use Patreon to generate income. The main purposes of using semi-structured interviews is to be able to understand content creators’ motivations for using Patreon, and their insights about the advantages and disadvantages of using Patreon. Also, since creators who use Patreon are also using other platforms, interviews will enable me to generate insights that to get a wider sense of the dynamics of being a content creator in this platform ecosystem. Thus, I will be conducting a mixed-method approach in my analysis with walkthrough and semi-structured interviews.

Throughout my analysis, I will also be making use of secondary sources such as news articles, magazine articles, blog posts and videos. The reason I will use these sources in my analysis is to be able to have a wider understanding of Patreon since these sources cover the popular and current debates, issues, controversies and discussions on Patreon. This will overall create a more educated knowledge about Patreon and being a creator on Patreon. The selection of these materials was done through first conducting a google search on keywords Patreon and

content creators. I have analyzed 5 most popular sites that covered tech and platform issues and

contain the keywords. and they were: Verge, Techcrunch, Polygon, Wired, New York Times. I have selected the sites and done the same search with same queries within those sites. This gave me a chance to analyze the recurring issues and popular debates that were covered throughout the years about Patreon. As the articles referenced other sites as well, this provided me with useful secondary resources in different sites. The sources were selected in according to how related they were to the research questions, theory framework and interviews.

3.2 Interviewing

There are different qualitative methods which aim to develop an in depth understanding by textual interpretation and observation and interviewing are the most common ones (Jamshed) Because what content creators do is digital work and there is no chance for me to physically observe them. I have decided to conduct interviews. While there are other methods of data collection I could have employed, I believe Interviewing is the best option as it enables the researcher “to uncover information that would probably not be accessible through questionnaires and surveys” (Alshenqeeti, 42). Interviewing is not only seen as a data collection tool, but it is a way of natural social interaction with the interviewees, where open exchange is possible. It provides more ground for conversation and exchange than other methods. The presence of the interviewer could help creating a clear communication with the interviewee, as

the interviewer “may rephrase or simplify questions that were not understood” which results in more appropriate answers and accurate data (Alshenqeeti, 42). Moreover, the interview data could be recorded, and played several times by the researcher “to help producing and accurate report” (Alshenqeeti, 42). This is also an important advantage, since accuracy in transcribing interviews into text is key for the research.

Therefore, interviewing is a good way of interacting with the interviewee, enabling to have a clear communication. This method fits my research since I necessarily do not look to get direct answers to strictly direct questions as if in a survey, but aim for an open dialogue with the content creators.

Interviewing could also bring some limitations. One of the most common notions to this is that people’s answers in an interview would be shaped by the questions and what the interviewee thinks the interviewer wants to hear (Alshenqeeti, 43). I have tried to avoid this by using neutral wordings that does not guide users to an answer, as observed in the Appendix. Furthermore, some scholars believe that what the interviewee give out as perceptions could not be sufficient to study social life, as it is a small-scale study (Alshenqeeti, 43). This limitation applied to my research too, since out of the many people I could have selected, I had seven interviewees. However, I believe this is a challenge that I have tried to overcome as possible, by trying to select interviewees that would be representative to the group I am interested in, which I explain later in detail. And by selecting creators from different nationalities, ages and genders, I have tried to improve diversity in my research too. Another limitation of interviews is the amount work it has to go into it to be completed. Some scholars view it as time consuming, “as the data collection and analysis is both transcribed, coded, and possibly translated” (Alshenqeeti, 43). This limitation is one that a researcher needs to face, since even with a small number of participants, the collection and analysis require time, effort and attention. In this research, I have used a qualitative data analysis software called Maxqda, which allowed me to conduct a thematic analysis on the interviews. Thus, despite the limitations, interviews provide opportunities for me as a qualitative research method, and I have chosen semi-structured interviews for the flexibility and openness it allows.

Semi-structured interviews are conducted through the interviewer not only sticking to the pre-determined questions, but conducting the interview with spontaneous questions in in an open way, enabling two-way discussion. The character of semi-structured interviews is about both the format and the style of the interview, thus, while I will be preparing a certain set of questions, I will also be making sure that I will be conducting the interview in a style that is “flexible enough for interviewees to be able to raise questions and concerns in their own words and from their experiences” (Brinkmann, 285). The semi-structure of this interview will allow the creators to raise issues, since semi-structured interviews can enable the interviewees to raise their own insights. I have created a ‘guide,’ which is a schematic representation’ of the questions I plan to ask the interviewees, and also possible topics of discussion that I could raise during the interview (Jamshed).

The guide I created included questions which are shaped by theoretical framework and research questions. I was interested in finding out the experience of creators. This means, from why they joined the platform, to how they use it, what they think over their own usage and experience etc. I have tried to avoid bias by telling them there is no right or wrong answers, and what I am interested is just their own individual experience and opinions.

While content creators and influencers are discussed vividly in academia and press, I believe they are not given enough voice to share the struggles they face on a personal level. Therefore, while having Patreon as the main object to discuss, interviews aim to get a wider understanding of the dynamics for content creation that creators have to face on a daily basis. While I already have an understanding of Patreon as a platform, I have never used it before. Thus, I aim to to avoid speaking on creators’ behalf by listening to the people who have used Patreon, and who have been subjects to the ecosystem.

3.4 Participants and Recruitment

At the time of the recruitment and selection of interviewees, the number of users who were registered in Patreon and who had at least one Patron was 182,714 (Graphtreon). They could all potentially be reached out for the interview. However, with the scope of my limitations, there had to be a selection process of interviewees. Thus, in a big pool of content creators, there are a few criteria’s I have employed to select participants. Throughout, I have made use of Graphtreon, a site that shows detailed statistics on Patreon. This website, built by

an independent computer engineer named Tom Boruta, provided me with useful knowledge such as the list of all creators, number of patrons they have, estimated earnings for creators and the categories with the highest number of creators.

Ideally, my selection of interviewees would be representative of all creators on Patreon as much as possible. Thus, I have filtered the categories for selection into 3: namely video

creators (48.438 creators), music creators (13.650 creators), podcast creators (13.406 users)

(Graphtreon). These 3 categories I have picked are the top 3 categories with the highest number of creators on Patreon, so the interviews would be more representative of creators who use Patreon statistically. This would enable me to interview samples out of the 3 most popular segments on Patreon.

However, even after I filtered out relevant categories, I had to still decrease the number of creators that I could contact. Thus, I have decided to reach out to creators that are comparatively ‘small’ on the platform. For that, I have decided to reach out to creators with more than 10 and less than 500 patrons, by looking at the data in Graphtreon. I have decided to do so since I believe small creators are in an entrepreneurial phase where they would depend on the Patreon income economically more than major creators, so they would have more experience on depending on Patreon for income. Another reason is the responsiveness. I have assumed, while a creator with for example a million subscribers on YouTube and 1000 patrons on Patreon would be less responsive because of the high number of messages, I believe smaller creators would be more responsive to my messages since they would actively be in self-branding and working to expand their reach. The accessibility was a limitation, since a user on Patreon could send a direct message to a creator only if the user is a patron for that creator. Since being a patron means paying monthly fees to a creator, and since this is an academic research, there was no way for me to pay creators to participate in an interview. The purpose of this research is not hearing what is in line with my theory or research questions, but it is listening to their real experience. Thus, I believe, paying would influence my interviewees to give answers that they think I would want to hear. Thus, I was not able to reach out to creators directly from Patreon since I did not want to pay them. So I contacted creators who provided contact details to their social media accounts such or creators provided their emails. This was the only way to contact Patreon creators without paying them.

After I have selected the relevant categories and filtered out participants, who had more than 10 patron and less than 500 patrons, and who were in the category of either video, podcast, or music, I had a new number of participants to filter out. The list now consisted of 15.397 video

creators, 5017 podcast creators and 4065 musicians (Graphtreon). Out of this total number of

24.457, I had randomly selected 25 creators out of each category on the list and contacted 100 creators in total. To those that provided their e-mails, I have sent them a standard info sheet, giving details about this research, me and consent issues. Out of the 100 people I have contacted, I managed to get a positive reply from 7 creators saying that they would be willing to participate. To those creators, I have sent a page where they can book interview spots, through

cemakca.youcanbook.me. I was able to conduct interviews with 7 content creators that actively

use Patreon to generate income.

Below is the list of content creators I have interviewed, with other details. I have given each participant a pseudo name to keep their identities secret. Out of the 7 creators, 2 of them were British, 2 of them were Turkish, 1 one of them were Dutch, and the other was American. The type of content they create vary, while 5 of them are mainly YouTubers, 1 creator is a podcaster, and the other creator is a writer and a podcaster. I have provided the subscriber counts for each follower on their main platform that they create content, and I provided the number of patrons they have.

Name

Nationality

Platform

Content

Subscribers

Patron

Count

Patreon

Earnings

1 Trevor Dutch YouTube

Comedy & Entertainment & Lifestyle Videos

55K 30 188 $

(per creation)

2 Alex American YouTube

Digital Art Videos & Painting Tutorials 162K 162 unspecified 3 Ali Turkish Twitter & Personal Website Investigative Writer & Journalist & Podcaster 4K 17 91 $