Proposal description
UPDATE
We've added some more graphs to the proposal and removed the rather contentious bit regarding voter concentration.
OVERVIEW
While the Dash DAO is a unique and radically transparent governing body, there has been very limited data-driven analysis performed to evaluate its function.
We would like to provide the Dash community with a deeper look into the inner workings of the Dash Governance and Budgeting System by thoroughly analyzing masternode voting patterns, proposal attributes, and many other network parameters to gain additional insight into how the treasury system behaves and how this behavior changes over time.
This information will provide value for the MNOs - by giving them a much deeper understanding of how their governance body functions, while also being incredibly useful for those submitting proposals - by providing them with analytics that will help understand the network’s needs and thus structure proposals that are more likely to deliver value to the network and thus pass with ease.
DELIVERABLES
Our work will consist of two primary functions:
As MNOs, we have a genuine curiosity about the way the DAO operates and have already begun collecting and analyzing network data. While limited by our ‘bootstrap’ budget, we have been able to develop a basic database and extract some interesting insights. Here are a few examples of our initial findings.
FURTHER DEVELOPMENT
Our objective is to use the additional funding from the Dash Treasury to accelerate the gathering and analysis of data, as well as making our research publically available to the network. More specifically, we would like to further explore the following areas:
BUDGET
Using the 30 Day SMA moving average price of $510 USD/DASH from yesterday (3/8/18), the total comes to 50 DASH/month.
* Any increases in Dash price will be used towards further development and expanding our data sources.
Pre-Proposal Link
We've added some more graphs to the proposal and removed the rather contentious bit regarding voter concentration.
OVERVIEW
While the Dash DAO is a unique and radically transparent governing body, there has been very limited data-driven analysis performed to evaluate its function.
We would like to provide the Dash community with a deeper look into the inner workings of the Dash Governance and Budgeting System by thoroughly analyzing masternode voting patterns, proposal attributes, and many other network parameters to gain additional insight into how the treasury system behaves and how this behavior changes over time.
This information will provide value for the MNOs - by giving them a much deeper understanding of how their governance body functions, while also being incredibly useful for those submitting proposals - by providing them with analytics that will help understand the network’s needs and thus structure proposals that are more likely to deliver value to the network and thus pass with ease.
DELIVERABLES
Our work will consist of two primary functions:
- Data Collection and Analysis
Ongoing development of a comprehensive governance database containing proposal, votes, categories, pricing information, and additional info and insights.
- Build-out of user-facing website
- Easily digestible visualization of the collected data, updated live using D3.js and other data-viz tools
- Public access to API, containing the raw data.
- Open-source release of data-collection code (after much refactoring)
As MNOs, we have a genuine curiosity about the way the DAO operates and have already begun collecting and analyzing network data. While limited by our ‘bootstrap’ budget, we have been able to develop a basic database and extract some interesting insights. Here are a few examples of our initial findings.
- Here is a basic stacked bar graph showing what day of the month the votes came in for the January 2018 budget period. It gives Proposal owners an idea of when MNOs are most active. Additional insight can be gained by looking at how this distribution has changed over time across budget periods, as well as further examining anomalies, such as the vote spike in the middle of the month.
- This graph gives additional insight into masternode activity, by showing what time of day and day of week votes come in on (shown in PST)
- This graph shows how many Unique Masternodes voted in each budget period. Evaluating the changes in MNO engagement over time is a powerful tool in assessing the health of the overall ecosystem.
- MNO voting patterns: From this graph, we see that in this particular budget period, 502 MNOs voted YES on 100% of the proposals they evaluated, while 65 MNOs voted NO 100% of the time, with a somewhat standard distribution for the rest.
UPDATE - Original Proposal Version
- After much deliberation and several conversations with vocal community members, we have decided not to continue our research into voting concentration. Our initial research when clustering by votetime was prone to false-negatives as all of the community voting tools use randomized offsets to prevent clustering by votetime alone and improve anonymity. The only voting tool which doesn't utilize random offsets, is the Dash Core wallet.
- This graph gives a good indication of the cognitive load placed on voting masternodes who have to cope with evaluating an ever increasing amount of proposals.
- This graph shows how many active proposals there are in any given period (the data isn't perfect yet, multi-month proposals are tough to deal with)
- This graph shows what a lot of us already expected in that we voted on a lot of Marketing proposals in 2018
FURTHER DEVELOPMENT
Our objective is to use the additional funding from the Dash Treasury to accelerate the gathering and analysis of data, as well as making our research publically available to the network. More specifically, we would like to further explore the following areas:
- Network Analysis - we will seek to find insights on how individual nodes operate, how the network behaves as a whole, and how consensus is reached. These are core components to understanding the behavior of any network, from an ant colony to an election. Our research will begin with the examination of the following:
- Looking at voting patterns to determine how nodes influence each other
- Identification of nodes that act as “opinion leaders"
- Identifying tipping points during a voting process where the outcome can be predicted.
- Sentiment Analysis - using tools like Watson Tone Analyzer to gauge comment sentiment on proposals and pre-proposals will give us further insight into how the MNOs and the broader community react to various types of proposals. This research will be focused on determining:
- Who are the most vocal/influential members of the community?
- How does the community react to various categories of proposals, such as development, marketing, and integration?
- Which proposals are the most contentious?
- Statistical Analysis - we will use a regression based models to test our hypothesis and determine which factors are statistically significant, which will be particularly useful for:
- Examining correlation vs causation relationships
- Identifying outliers that require further qualitative examination
- Mathematically validating or discrediting our hypotheses
BUDGET
Using the 30 Day SMA moving average price of $510 USD/DASH from yesterday (3/8/18), the total comes to 50 DASH/month.
* Any increases in Dash price will be used towards further development and expanding our data sources.
Pre-Proposal Link
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Discussion: Should we fund this proposal?
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Governance Analytics & Business Intelligence by Dash_Intel
https://dashwatch.org/files/1527513189414.pdf
B: Good on you for using the 30-day SMA even though the price is down lately.
solarguy
solarguy
We will be looking into our data to see whether this may be a recurring pattern with other proposals in other budget periods. Looking forward to presenting our findings on this topic and many others!
Voting yes
Spoke with a Dash Watch representative yesterday about working together and sharing our data. This has always been the goal and we encourage other groups to reach out with research goals and questions we might be able to answer.
We've also done some preliminary analysis on the success of the GetFreeDash giveaway program in response to a suggestion by Walter. Early results indicate that approximately 75% of those given free Dash keep it in their wallets and don't spend it, while about 25% have 'spent' 100% of what they were given.
It's entirely possible that the reason these people aren't spending it is because most of the giveaways have occurred during the recent downturn in the crypto markets and people would rather wait to sell it when it's worth more. Or, it's possible that they don't have a very good way to go about exchanging it or spending it.
It warrants further research and our next course of action would probably be to look at how long those who received Dash and then spent it waited to do so. Was it immediate? or did they wait until the price was higher than when they received it?
your proposal has demonstrated that the MN can not be analyzed.
Thanks for that.
I do not see any interest in analyzing what is not.
This might just allow some to use these numbers for information manipulation purposes.
It's a no
First of all, your informaction about DashMasternodeTool in the context of voting anonimity isn't really accurate. I don't blame you for this - you probably don't use the application, so you may not know how it really works. In fact, during the voting, the application adds a random offset to the vote time of each of the votes cast and in this way it separates votes/masternodes from each other. In this way, as much anonimity as possible is ensured in this context - in my opinion when we deal with large amounts of $$$ in this crazy world, this kind of thinking is crucial for the people's safety and for this I'm ready to sacrifice transparency. I'm probably not alone with this opinion, because other tools like dashmnb or DashCentral, use similar methods.
Putting aside one's perception, whether the voting anonimity is good or bad, there are some other drawbacks I see for this particular research. As we know, only 10% of masternodes take part in the voting. Some of them (I hope a lot) are really aware and take care of their anonimity, by adding the above-mentioned time offset, separating MN payment transactions and so on. The consequence of this will be a lack of knowledge of the actual amount of masternodes that affect the results. We can learn, for example, that 250 masternodes are certainly in the hands of five people, but it's the lower bound and you won't be able to know the upper bound. Besides, what about shared masternodes? For them you will show a large ownership concentration, while in fact hundreds of people are the owners.
I think, that we will not be able to use this research in any debate with our opponents, because we will immediately be pointed out, that at least 90% of masternodes were out of the scope of the study. I'm afraid that as a result of this research, even fewer masternode may vote - some of them can put their privacy/safety above than advantages of the participating in DAO.
In my opinion, by slightly changing the scope of the research, you can get much more enthusiasm from the MNOs and even help to increase the resilience of the network in the long-term. For this purpose, the "Mastenode Groupings" research should be replaced with the "VPS providers & geographical centralization" studies. How important they are we could see after the power failure of the OVH Strasbourg datacenter in November 2017. Research doesn't automatically solve the problem (if it exists) but it could give rise to a discusion on how to mitigate this issue.
Probably such studies have already been conducted, but it would be good to have results updated on a regular basis.
Our intent with the clustering was always to try and understand whether or not the Treasury had enough different voices voting in it to effectively benefit from the "wisdom of the crowd" and to see if voting power distribution increased or decreased as time went on. You're right in that it's rather hard to nail down empirically though and I see the argument against doing so as well.
In my opinion, the better we understand the composition and function of our governing body - the more we can do to improve it.
Voting yes
If Masternodes don't like the fact that their vote isn't as private as they'd like, then it's time to get Core to push harder on vote blinding.
Walter
We started by looking at proposals and then we started looking into voting because there have been about 500k votes cast in our DAO and that's the kind of data that gets geeks like us excited to analyze.
solarguy
Hopefully y'all can also work with the community and focus your analytics on other things of interest as well. For example, if the community asked you to do an investigation to track large giveaways to make sure said giveaways are not being gamed with large sums of Dash immediately being consolidated to one polo account and cashed out.
Can y'all help with stuff like that or is this just a masternodes only thing?
We've been talking with John Kindel and some others on the Core team as well about taking this data analysis beyond just the governance data and this is something we could potentially look into.
We have some code for looking at the transaction layer for our proposal payout calculations (thanks Insight API :) ), and it should be possible to transfer some of that work over to looking at giveaway wallets.
Voting yes.
I'm really glad this analysis was done, as it is invaluable in our fight against detractors and more importantly it serves as a perfect advertisement for Dash's healthy ecosystem to any potential user and/or investor out there.
It goes without saying that this proposal has my full support as the additional planned features are exactly what our network needs. It will be a beautiful display of our living network to see the data & stats evolve over time.
This is the kind of independent developmental proposal I was hoping for for a long time.
LESS MARKETING PROPS, MORE OF THIS!
I would also be curious to know if exchanges are setting up masternodes. Which is fine, as long as their clients are made aware.
I would imagine many exchanges do set up masternodes but it could be tough to track the movement of those funds in a manner where we're certain that they're held by an exchange vs just sent to an individual's wallet from an exchange address.
With enough analysis you should find a couple big MNO's probably using a voting script to submit votes rather than just one big vote.
We can ask Rango for this but I don't think he's running analytical code to that degree and I'm not sure if it's something masternodes would really want to subject themselves to.
We could draw some interesting insight from that.
You have my support.
This is more the type of information I have been looking for, "to help masternodes make more informed decisions."
More types of data I'd like to see, that perhaps you might provide in the future:
What kinds of proposals are being submitted each month? (dev, biz ints, ads, ed, community, etc.)
What proportion of those categories are being approved?
What proportion of the budget is being allocated to those categories per month/quarter/year?
What is the avg/median size of proposals submitted vs being approved?
How likely are proposals to be approved that are submitted by first-time proposers vs a 2nd-time proposer, 3rd+ or more "experienced" proposal owners? and what is the "experience-distribution" of proposals being submitted/approved?
i.e. what proportion of the budget is being allocated to first-time proposers vs more experienced?
I'm also interested in your "Sentiment Analysis," particularly the data that answers "What types of proposals are the most contentious?" I'd be fascinated to see what types of proposals are more/less contentious (e.g. development has 96% "approval" votes, marketing-type proposals on average this month have 84% "approval" votes, education-type proposals on avg have 43% "approval" up from 35% last month, etc...) and also what proportion of the budget contains proposals that are "contentiously" passed (e.g. 30% no votes) or that have broad support (e.g. under 5% no votes)
Looking forward to the approval of this proposal and more of your work!
We have already begun looking into some of the questions you mentioned and will be able to provide visualized data, as well as analysis and insights within a few weeks.