Data on WagMedia's Paraverse Content Creators Guild Part II: July 31 - December 9, 2023
I. Overview
This article examines the data on production and payouts within the Paraverse Content Creators Guild (“Paraverse Guild”) from July 31, 2023 through December 9, 2023.
Originally by CSaint (@csaint02), the Paraverse Guild focuses on producing original content on parachains, governance, and general principles in the Polkadot-Kusama ecosystem. The Paraverse Guild has recently been led by Goku (https://twitter.com/0xgoku_).
The Paraverse Guild was approved for funding via Kusama’s OpenGov in January 2023 (https://kusama.polkassembly.io/post/2089). The Guild is a continuation of a unit that was previously part of WagMedia’s Bounty #12, and continues to use tools developed by WagMedia (@thatMediaWag ).
The data on content production and payouts are based on a native spreadsheet for WagMedia’s Paraverse Guild treasury, reported publicly on https://report.wagmedia.xyz/. The data for this article covers the period from July 31, 2023 through December 9, 2023 (based on date of payment award).
For a report on the Paraverse Guild from January through July 2023, see my previous article: https://vampsy.substack.com/p/data-on-wagmedias-paraverse-content.
The data and calculations reported in this article are not audited, and certain numbers are approximate and subject to different interpretations and potential errors. Please let me know (@vampsyfear) if you see any errors.
II. Content Production and Payouts
From July 31 through December 9, 2023, 21 content creators produced 82 original content for the Paraverse Guild. In total, the Guild paid out 190.05 KSMs for these content, with an average payout of 2.32 KSMs per content. In terms of USD values, these payouts correspond to approximately $4,876 in total with an average payout of $59.46 per content. The conversion of KSM to USD is made based on the KSM:USD exchange rate on the date of payment award. Each content takes the form of a post (e.g., Twitter / X), article (e.g., PolkaVerse, Substack), and/or video (e.g., YouTube).
The distribution of payouts is reported in the figure below. For example, content in the top 25 percentile in terms of KSM payout (20 out of 82) received a payout of 3.50 KSMs or more, which implies that 75 percent of content (62 out of 82) received a payout of 3.50 KSMs or less.
The payouts are skewed in favor of top quality content and creators, with content in the top 10th percentile receiving a payout of 5.70 KSMs or more (USD value of $126 or more) while the 50th percentile content received a payout of 1.74 KSMs (USD value of $42.62). The amount of payout is determined by the quality of content (as evaluated by the directors) and the tier of the creator, with higher tier creators being eligible for higher maximum awards (i.e., the upper bound payout is more for the higher tier creators; the lower bound is the same for all tiers).
Each content produced within the Paraverse Guild was evaluated by Goku, Csaint, and Dodow as reported below. For example, Goku reviewed 68 content, and disbursed a total of 156.25 KSMs through the WagMedia tool. Dodow reviewed content produced by Csaint (who is a top tier creator eligible for higher maximum awards).
III. List of All Creators
The list of all creators who received a payout from the Paraverse Guild from July 31 through December 9, 2023, as well as their content production and payouts, are reported below.
IV. Special Topics Bounty
The Paraverse Guild also designed and ran various special topics bounties, designed by the director to entice the timely creation of content focusing on topics that are of particular interest to the Polkadot ecosystem. Content creators can participate by submitting content that addresses the topic and the director evaluates, ranks, and award payouts accordingly. The special bounties can also take the form of additional payouts for content that have achieved particularly high impact after their initial payouts were determined.
The table reflects the first place winners and their content, payout, and Twitter stats. The impact of these special bounties exceed those of the first place winners in the table as most bounties had multiple winners (e.g., second place, third place, etc.)
The X / Twitter links to these content are below.
https://twitter.com/pitcoin_/status/1721736714694058308
https://twitter.com/0x_cryptox/status/1723018079347539982?s=20
https://twitter.com/0x_cryptox/status/1726267419084153021
https://twitter.com/pitcoin_/status/1728440264396816723
https://twitter.com/__open_minded/status/1732086559577350575?s=46&t=7mPPgyIBYOwnPBRhPeenSw
https://twitter.com/mrkusama/status/1727692993103110638?s=46&t=w6Lx2_7W6OffmtSBDHsQwA
https://twitter.com/emilkietzman/status/1730647992917463133
https://twitter.com/stakenode_dev/status/1732736478826873285
https://twitter.com/Cris_Pap8/status/1729501260594733226?s=20
Appendix on Use of Social Media Stats
It is important to note that while data on views and statistics that are freely available on Twitter and other social media are informative and easy to access, content generating higher views are not necessarily more valuable than those with lower views. This is because the value of engagement varies across audiences (e.g., not all views have equal value). For example, content that gets 10 views and generates $1,000 in sales is arguably more valuable than content that gets 1,000 views but only generates $100 in sales. In this sense, content that is highly targeted to a small group can sometimes be more valuable than content targeting a wider audience, and vice versa. A more sophisticated tracking technology is needed to inform the ultimate value of content.
When analyzing data, it is important to keep in mind what you can see in the data versus what you cannot see, and adjust how much weight you place on the data accordingly. In analogy, if you hire two fishermen and receive data that one caught 1,000 fish and the other caught 10 fish, how would you use that data to determine how much to pay them?
If they are both fishing from the same pond with only one type of fish, you can reasonably infer that one fisherman did much better than the other, and pay them accordingly. But if they were fishing in a large ocean, that data is useless because it does not tell you what type of fish they caught.
If you were to set up a reward mechanism that pays the fishermen based only on the number of fish they catch, they would be incentivized to go after fish that are easiest to catch. Your fishermen would be incentivized to only go after small and easily-catchable fish, like anchovies. They would not find it worthwhile to go after bigger and harder-to-catch fish, like bluefin tuna.
In the analogy above, “views” are more like how many fish saw your bait. This statistic may be a good indicator of how well you are doing when fishing in a small pond with only one type of fish (and the fish have a similar propensity to bite), but a very imperfect proxy when there are lots of different fishes in the ocean.
This example highlights the importance of designing a reward mechanism that can incentivize optimal behavior. If the payouts for content are rigidly based only on views and other stats that are freely available, this could sub-optimally incentivize creators to focus mostly on producing things that are popular versus balancing popularity and value.
In light of imperfect data, a better payout mechanism would consider various factors, in addition to the freely available stats (e.g., views, replies, etc.), to determine the payout. To this end, the Paraverse Guild has implemented a scoring mechanism in which content submitted to the guild is reviewed and evaluated by the director to assess the both the quality and impact of content.