In the past 6 months, I have been involved in several discussions about the trends in active BOINC users and how this is developing in time. Because these stats are not available on BOINCStats, I decided to use the Wayback Machine to build them myself to check these developments.
Chart 1 presents the number of active BOINC users without ASICS in the last 5 years. Unfortunately there are no daily snapshots on the Wayback Machine, which means the chart looks a bit choppy at times but overall there were enough data points to provide some insides in the developments.
Chart 1 (source: BOINCStats)
While looking at the first chart, I noticed several strange peaks which I couldn’t explain with the seasonality effect. It seemed more like temporary increases of active users that dropped again after a few months.
While analysing the developments in individual projects, it became apparent that a number of projects were responsible for the main peaks. To explain this, I have included the chart of active users for Rosetta@home below (chart 2). You’ll notice a peak in Aug-2014, Mar-2015 and Oct-2016 that corresponds with the same peaks in the overall chart above (chart 1).
Chart 2 (source: BOINCStats)
Long-term user developments
To better understand the long-term user developments, I subtracted the peak increases related to Rosetta@home, Primegrid, malaria@home & Find@home in chart 1 and presented it in chart 3 below. It is interesting to observe that the changes in active users are much smoother now, although there are still some variations caused by other projects.
Chart 3 (source: BOINCStats)
Based on chart 3, I had two observations:
- There is no seasonality effect in active users
- The long term active user-base is declining
There is no seasonality effect in active users
I was under the impression that during the winter period in the northern hemisphere, more users were crunching BOINC projects worldwide than in the summer. Chart 3 suggest that this is not the case and the number of active users is relatively flat.
To illustrate the seasonality pattern (shown in chart 4), I have created a basic model using chart 3 with the following parameters:
- During the winter period in the northern hemisphere there are 100000 active BOINC members more than average
- During the summer period in the northern hemisphere there are 100000 active BOINC members less than average
- During the winter period in the southern hemisphere there are 50000 active BOINC members more than average
- During the summer period in the southern hemisphere there are 50000 active BOINC members less than average
Chart 4 (source: BOINCStats)
If you compare chart 4 with chart 3, you will quickly recognise a complete different pattern.
Long-term active user-base is declining
To demonstrate the decline in long-term active users, I have taken chart 3 and added a trendline (see chart 5 below). The trendline clearly demonstrates that the long-term active user-base has been declining in the last 5 years and the delta between first and last data-point on the chart is -112,013 active users or almost -40%.
Chart 5 (source: BOINCStats)
The results above surprised me because they suggest that the long-term active user-base is much smaller than I thought and moreover it is declining.
Team Gridcoin
With the increasing attention for Gridcoin it will be interesting to monitor whether the downward trend stops in the near future. I would like to finish with the final chart presenting the number of active Gridcoin members in the past 12 months (Solo & GRCPool combined), which has increased 660% during this period.
Chart 6 (source: BOINCStats & GRCPool Stats)
I’m looking forward to receive your feedback in case I missed anything or my observations are incomplete/incorrect.
Thanks for reading. Follow me for more BOINC & Gridcoin related articles.
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I think user decline is due to people joining the pool? And/or also dropping boinc and just mine cryptos
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would also like to see this correlation
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I can’t provide an answer how many people have left BOINC to start mining another crypto.
I can show the impact of active pool members to the chart from 1-Jan-2017 but you'll notice that the impact on the overall active user trend is still very limited. This may change in the near future.
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Thanks for putting together this statistics. What would be interesting is an historic chart of the estimated computing power.
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Should be possible @grider123, I'll have a look at it.
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