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Understand App Mining
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This section explains App Mining, a program for developers. For Blockstack, App Mining is a crucial factor in the growth of both blockchain applications and users.
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What is App Mining?
{% include intro-appmining.md %}
How apps are reviewed
Blockstack worked with a team of Ph.D. game theorist and economists from Princeton and NYU to put together a ranking algorithm which is fair and resistant to abuse. Blockstack uses three third-party reviewers, Product Hunt, TryMyUI, and Democracy.earth. These reviewers are independent, and generally rely on their own proprietary data and insights to generate rankings.
Product Hunt
Product Hunt is the place to find the best new products in tech. They have a massive trove of user data (upvotes, comments, etc), that they use for ranking. Product Hunt comes up with two different scores for each app — a “community” score and a “team” score.
Their community score is determined only by the number of upvotes an app received on Product Hunt, relative to other apps that are registered. For example, if an app got more upvotes than any other app in a cohort, their community score would be 100. If a different app got 60% as many upvotes, they’d get a score of 60.
Their team score is determined by internal team members conducting reviews on different aspects of an app. They judge based on a few criteria, like execution, uniqueness, and desirability. Each app gets ranked 1-10 on each criterion, and their final score is the average of each criterion. Finally, this average is multiplied by 10, so the highest score you can get is 100.
Once each app has a community and team score, Blockstack converts these scores into z-scores, more about z-scores below.
Democracy Earth
Democracy Earth is a platform for borderless peer-to-peer democracy. They’ve built a platform that anyone can use to gather votes in a trust-less, decentralized way.
Democracy Earth has built a platform for Stacks token holders to vote on how apps should be ranked. Each token holder gets a 1000 votes, and they can distribute those votes however they want. It’s possible to give all of your votes to a single app, and you can also “downvote” an app with one of your votes.
After a voting period, each app has a certain amount of upvotes and downvotes. First, Democracy Earth calculates the percentage of total votes that are upvotes. If an app receives 90 upvotes and 10 downvotes, the resulting “likability score” is 90. Secondly, Democracy Earth calculates a “traction score”, which ranks how many total votes (including downvotes) an app received, relative to other apps.
TryMyUI
TryMyUI’s panelists score using a special survey they developed expressly for the App Mining program: the ALF Questionnaire (Adoption Likelihood Factors). Desktop, iOS, and Android versions of apps are tested as they are applicable.
Answers to this questionnaire will be used to calculate an overall score reflecting the following 4 factors:
- Usability
- Usefulness
- Credibility
- Desirability
Each factor corresponds to 4 questionnaire items, for a total of 16 items that comprise the ALFQ. Users mark their answers on a 5-point Likert scale, with 5 meaning Strongly agree and 1 meaning Strongly disagree. The final result is a score for each of the 4 factors, and a composite ALF score.
For example, consider an application that is both Android and iOS. Each platform version receives 4 tests of each. In total, 8 user tests are created, the highest and lowest scores are dropped. App developers receive the raw TryMyUI scores. The App Mining process calculates Z scores for each category. As a result, the TryMyUI results in the App Mining scores differ from raw scores visible in an app's TryMyUI account.
Reaching the final scores
Once the reviewer-partners generate reviews, each app has 5 raw scores between 0 and 100 for the following:
- Product Hunt community score
- Product Hunt team score
- Democracy Earth likability score
- Democracy Earth traction score
- TryMyUI ALF score
First Blockstack's determine a ‘z-score’ for each ranking category community, team, likability, and traction. This is a statistical technique to account for different distributions of scores within categories. Second, Blockstack computes the average and standard deviation of each category. Finally, for each app’s score in that category, Blockstack determines how many standard deviations it is away from the average score in that category.
For example, let’s say a category has an average score of 60, with a standard deviation of 15. A score of 90 would get a z-score of 2, because it’s 2 standard deviations higher than the average.
Once each app has a calculated a z-score in every category, the average of those 4 z-scores results in a final number. A higher number is better than a lower one, and so apps are ranked from highest to lowest.
Determining how much an app is paid
{% include payout-appmining.md %}
This first release of App Mining uses the initial version of our ranking and payout mechanism. Blockstack has taken care to be thoughtful and fair, but things may change as we learn more and get feedback from the community. Please let us know what you think by commenting in our forum or by emailing us at hello@app.co!
The ranking and payout mechanisms are under constant review and are documented at the app mining's github repository.