This document summarizes data on patronage networks for digital creators. It finds that over 60% of creators did not provide location data, with the top locations being the USA, UK, and Canada. Most patrons also did not provide location. For countries with over 10 patrons, patronage networks are highly international, with patrons usually backing creators from the USA. The top creative fields for patronage are writing, comics, video/film, drawing/painting, and podcasts. The document raises questions about power dynamics between patrons and creators and the impact of patronage networks on traditional arts funding.
2. Types of Patronage
- Individual patrons
- The Church (particularly in Italy)
- Government patronage (Post WW2)
- Corporate patronage (1980s onwards)
- ‘Crowd patronage’ (2010s)
3.
4. Creator
Hosts video and adds adverts
Advertiser
Viewers
Watch videos and adverts
Counts views
5.
6. Methodology
Data scraping Location All n All % Creators n Creators % Patrons n Patrons %
Not Given
13375 61.28 1632 28.13 11743 73.28
USA 5064 23.20 2643 45.55 2421 15.11
UK 727 3.33 329 5.67 398 2.48
Canada 633 2.90 344 5.93 289 1.80
Australia 304 1.39 108 1.86 196 1.22
Germany 238 1.09 88 1.52 150 0.94
Brazil 139 0.64 72 1.24 67 0.42
Sweden 112 0.51 42 0.72 70 0.44
France 105 0.48 32 0.55 73 0.46
Spain 99 0.45 56 0.97 43 0.27
Denmark 72 0.33 14 0.24 58 0.36
Netherlands 72 0.33 32 0.55 40 0.25
Italy 62 0.28 34 0.59 28 0.17
Russia 60 0.27 35 0.60 25 0.16
New Zealand 59 0.27 17 0.29 42 0.26
Norway 56 0.26 16 0.28 40 0.25
Finland 43 0.20 13 0.22 30 0.19
Mexico 42 0.19 21 0.36 21 0.13
Japan 40 0.18 23 0.40 17 0.11
…
Total 21826 100 5802 100 16024 100
7.
8.
9.
10. % Patrons backing
domestic creators
% Patrons backing
external creators
Biggest recipient
of patronage
Total Patrons
USA 77.2 22.8 USA (77.1%) 8500
Spain 50 50 USA (50.0%) 86
Brazil 33.1 66.9 USA (46.2%) 169
UK 19.9 80.1 USA (61.5%) 1056
Canada 16.5 83.5 USA (66.4%) 847
Italy 12.5 87.5 USA (64.1%) 128
Mexico 11.8 88.2 USA (49.0%) 51
Germany 11.4 88.6 USA (56.2%) 493
New Zealand 10.2 89.8 USA (62.7%) 118
Russia 9.1 90.9 USA (50.0%) 44
France 5.7 94.3 USA (51.6%) 159
Portugal 5.6 94.4 USA (61.1%) 18
Australia 5.4 94.6 USA (66.4%) 652
Ireland 5 95 USA (70.0%) 20
Israel 4.6 95.5 USA (68.2%) 22
Argentina 4.2 95.8 USA (70.8%) 24
Sweden 3.9 96.2 USA (60.1%) 208
Denmark 3.8 96.2 USA (61.0%) 159
Finland 3.7 96.3 USA (51.9%) 81
South Africa 2.9 97.1 USA (60.0%) 35
Poland 2.7 97.3 USA (59.5%) 37
Belgium 1.3 98.7 USA (65.3%) 75
Norway 0.6 99.4 USA (66.7%) 156
Austria 0 100 USA (60.8%) 51
China 0 100 USA (21.1%) 19
Costa Rica 0 100 USA (50.0%) 10
Czech Republic 0 100 USA (70.0%) 20
Hungary 0 100 USA (59.3%) 27
Japan 0 100 USA (66.3%) 83
Malaysia 0 100 USA (80.0%) 10
Netherlands 0 100 USA (63.9%) 133
Singapore 0 100 USA (73.3%) 30
Switzerland 0 100 USA (52.6%) 95
Domestic vs
Overseas
Patronage
(Countries with fewer than 10 patrons excluded)
19. What next…
• Many questions arise:
• power relations between patrons and creators
• role of agents, humans and non-human, in circuits
of culture
• impact on established arts funding
• scopic regimes
Editor's Notes
Hi, i’m Jon and i’m from Northumbria University. I’ve been working on a project examining new forms of patronage for 6 months funded by the British Academy/Leverhulme Small Grant Scheme, and i want to share some of the early insight with you. I’m going to do this through some visualisations.
First, though, i want to briefly outline how patronage have changed through time. Wealthy individuals or small groups of individuals, families, have long been patrons of the arts, dating back to early kings. More recently 19th century industrialists funded the arts either directly or through museums.
The Church, particularly during the renaissance were big sponsors of the arts in Europe. The most high profile example is probably Pope Julius II and Michelangelo’s relationship.
At the end of the second world war the British Government, and others in Europe, sponsored the arts as a public good. We’ve seen this decline over the last decade dramatically, America’s National Endowment for the Arts has long been controversial.
The expansion of neo-liberalism in the 1980s saw governments encouraging companies to become partons of the arts. This often involved sponsoring exhibitions and events at major galleries.
The key thing about these types of patronage is that it is relatively local. Interacting with artists face-to-face is important, particularly when spending large amounts of money on work, and throughout history tangible art has been key for patrons because they want to show it off while maintaining access to it.
Most recently crowd funding systems have allowed different group of individuals, usually younger and less wealthy than traditional patrons of the arts, to support artists they enjoy. The majority of the interaction between creators and patrons is mediated by the web, the range of work has grown and on patreon at least, most of the work is intangible.
This has created a series of new geographies and flows which my research looks at. It also has implications for the production of culture as new agents enter circuits of culture and other are shifted around it.
My focus to understand this new form of patronage is a website called Patreon.
Crowdfunding sites like Kickstarter are about one off projects, usually relatively large scale, and often asking for money in the 10s and 100s of thousands of dollars range. Patreon is about monthly payments to enable content creators (who are usually individuals and doing their cultural work alongside other jobs) to do more of what they already do, or to take their work to the next step - either by buying better equipment, or allowing them to stop their other job. It also allows some to remove advertising from their sites and channels, thus replacing an intermediary they have little or no control over.
Importantly, Patreon encourage creators to avoiding use the site as a paywall. There are bonuses for being a patron, but most content creators make their work accessible whether you’re a patron or not.
Jack Conte, a musician and video maker, founded Patreon with a friend from Stanford University. Conte had become dissatisfied with other web-based monetisation platforms, particularly Youtube.
Youtube has been a key way for content creators to monetise their work through advertising linked to views of videos. The process is outlined on the screen for those not familiar with it.
But as Youtube has become more popular, the value of a view has decreased. Youtube has also changed its monetisation process, which now favours channels posting lots of new content, rather than people who post videos on a weekly or fortnightly basis.
Conte lamented it would be so much easier if he could just get his fans to pay him directly. So he set up Patreon to facilitate this.
Patreon was launched in May 2013, with $2.1m of seed capital and three creators. By the summer of 2014 it had grown to 25000 creators and by October 2014 the site was processing $1m of sponsorship between patrons and creators. With such rapid growth they needed to expand the business so sought further funding at the start of 2015 - Conte was successful in gaining $15m of Series A funding from a set of backers aligned to Patreon’s vision of building a creator-centred community, rather than a business platform.
In March 2015, Patreon acquired Subbable, a similar patronage platform, after the latter’s payment processor - Amazon - changed their product. The result that users would see a drop in revenue of 30-40%. Patreon stepped in and acquired Subbable with most of the users transferring across.
As of last month there were over 70,000 creators using the website. My research examines the geographies of these creators, the relationship they have with patrons, and the impact on established arts funding regimes. Today i’m going to look at some of the broad geographies from the first stage of the research.
The first stage of the research has been extensive data collection and analysis. I’ve been using web scraping tools to glean information about creators and patrons from the patreon website. You can see an extract from my sample on the screen.
I scraped almost 22,000 users: 5802 creators and 16,024 patrons.
This amounts to about 8% of creators - and the sample is representative in certain ways, but impossible to tell completely because Patreon don’t share a lot of detail about the profile of their userbase.
70 countries are in the sample, although not everyone states their location. And as you can see the US dominates the sample.
There average patron supports 3.5 creators, although it varies by genre. The average creator has nine and a half patrons. The median earnings for a creator is $134 a month, but the mode is $5.
Some are hugely successful, however…
These guys make educational videos, have over 6000 patrons and generate over $381,000 a year.
Because I’ve got lots of data, i’ve been visualising it in various ways to try and make sense of it. I want to show you a few of these visualisations to highlight some insights into the dataset.
First, these are the genres patreon uses to categorise content creators. Video and film, comics, and drawing and painting dominate my sample. I had to code the data into these categories, it took ages even using automated processes in excel, and there is still 14% which was hard to determine, not least because many creators work across genres.
About 6% is adult content, although Patreon don’t allow photographic or video pornography.
This is a simplified map of patronage networks. It is a distribution you might expect given what is being created and how it is distributed. But there are a few surprises such as the two people in Antarctica - presumably bored physical geographers wanting some culture between counting ice or whatever they do.
Much of Africa is completely missing.
Looking at these connections in more detail, this table is patron data. As you can see, every country apart from the US and Spain has a net outflow of patronage linkages. It is quite a contrast to traditional forms of patronage which were usually confined to connections within a patron’s country.
In terms of the genres creators of different nationalities are working in, this is data plotted from a principle components analysis. As you can see there are some marked differences between countries.
Canada, for example, has twice the percentage of creators making webcomics than the UK.
8% of German creators are working on games, but no French creators are.
This is all the data graphed in a social network program - nearly 22000 people, and 54000 connections between them.
Creators, in red, have been resized based on the number of patrons they have. I’ve used an algorithm which pulls together nodes with shared connections and push apart those which are unrelated. There are various statistical test you can do to understand the network, but this is a session about visualisation so i want to quickly explore communities of patrons and creators visually.
This is the same data, but with patrons hidden and creators colour coded to show genres. Here you start to see some patterns emerging.
This is writers. There isn’t much grouping happening here which suggests these creators have quite a following who have diverse tastes.
This is comics, and from the tight grouping towards the middle we can tell that patrons who support comic makers, also support other comic makers.
As you’ll see on the next slide there is some overlap with drawing and painting in the bottom part of the network, and this appears to be a style and content thing.
Here you can see the overlap between drawing and painting and comics in the bottom part of the network. And it is in this area you find most of the drawing and painting creators, linked together by patrons who follow a number of other creators working in the drawing and painting genre.
Finally, this is games. There are three distinct groupings here, and again overlap at the bottom with drawing and painting and comics. This was intriguing so i looked into this area further.
One way i did this was to use a measure of modularity to identify communities statistically. You can see the communities in the colours here. In the bottom section we find creators and patrons working in drawing and painting, comics and games who form a single community. Ive not had a chance to fully interrogate this group, it appears that the games, pictures and comics in this group are stylistically similar, which suggests there are particular scopic regimes influence who becomes patrons of whom.
So that was a very brief examination of this first phase of the research. Next i’m going to do a questionnaire and interviews with creators, patrons and various other agents involved in this cultural production.