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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 partnered with two different third-party
reviewers, Product Hunt 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 certain number of 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, Blockstack calculates the percentage of total votes that are upvotes. If
you got 90 upvotes and 10 downvotes, you’d get a “likability score” of 90.
Secondly, Blockstack 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).
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.
< img src = "images/alf-score.png" alt = "" >
## 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 < a href = "https://forum.blockstack.org"
target="\_blank">in our forum</ a > or by emailing us at < hello @ app . co > !
