In relation to the post on Vox Day’s comic being pulled from IndieGoGo and whether there were financial shenanigans, I thought I’d grab some data. Unfortunately, because the dodgy comic has shelved, the contribution data is no longer available at the IndieGoGo site. However, a different “Arkhaven” (aka Castalia House, aka Vox Day’s vanity press) comic still has a live campaign. This one is being run by Timothy’s number 1 client, Jon Del Arroz. https://www.indiegogo.com/projects/the-ember-war-graphic-novel#/
Contribution data is available by looking at the list of backers. Not all backers are named (which is fair enough) and not all backers reveal how much they contribute (also fair enough – not trying to invade anybody’s privacy). For those backers who don’t reveal how much they gave publically, the overall total can be inferred by subtracting the amount raised by people who do show their contribution from the complete amount raised. For convenience, I’ve shared that between all the backers who didn’t list an amount (of course, in reality, some may have given a lot less or a lot more).
NOTE: I’m using this just as an example of crowdfunding data. I’ll point out interesting or notable features but 1. I’m not saying they are evidence of anything dodgy and 2. to make any such claim would require looking at many other campaigns to get a sense of what was typical v unusual. Also, while many names are given publically at the site, no names should be referred to in the comments etc aside from the organiser. Lastly I may have made errors 🙂
There were four donations that were set as “Private” and they occurred “24” and “23” days ago (the data on the site is given in that format – I’ve inferred dates). Together they amount to $70 or $17.50 each i.e. unremarkable*.
The graph looks like what I might expect. I guess some campaigns might be more S shaped with a slow start and then a steeper climb before tapering off. Yet, campaigns with a big burst of contributions in the first few days and then a slow increase after makes sense also. I would imagine campaigns that run a danger of just falling short of their target goal might show a big blip near the end as the campaign makes one last push. For comparison here is a graph I drew of a different style of campaign: https://camestrosfelapton.wordpress.com/2018/03/03/looking-at-some-crowdfunding-data/ (it looks smoother because I spread some of the day-by-day data out artificially).
The biggest contributions were from five people who gave $515 each. That’s a curious amount, particulalry as the tier reward is at $500 and there’s no other donation values around that size i.e. everybody who gave a lot of money gave exactly the same amount. How weird is that? I don’t know, hence my caveat above. That maybe something that happens a lot with crowdfunding campaigns or maybe it’s really weird. Drawing conclusions about what’s weid requires data from more campaigns but also models to compare data against. For example, there’s no tier reward between $150 and $500, so it is not actually surprising that there’s no contributions at around $200 or $300.
Even so, around the $150 tier there is a lot more variation. Like I said, I don’t have a theoretical distribution to compare this against but while there’s more kinds of values they are still oddly clumped to my eye:
- 2 at $172
- 3 at $170
- 2 at $167
- 1 at $165
- 18 at $162 (?!?)
- 6 at $160
- 0 at $150
I’ve no idea why exactly $162 is so popular. Perhaps it is a round number contribution in some other currency (don’t know what though – doesn’t match Euros or Canadian $) It doesn’t seem to match a combination of tier rewards either.
This graph shows the frequency of each of the 23 different sizes of amounts that were contributed and how much money was raised by that category. Bars are numbers of people and green dots are totals amount of money. ($18 is actually $17.50 and that’s actually the “Private” amount and hence should be taken with a pinch of salt).
I’d have expected something a bit more Pareto like I guess.
So, no big conclusion just that there’s stuff to look at and with enough background data of similar campaigns it would be plausible to spot campaigns that were distinctly unusual.
*[Speaking of errors, in the first graph I drew I’d calculated these ‘Private’ amounts incorrectly by using the Goal of the campaign instead of the total raised. Luckily I spotted my error before making a fool of myself.]