Life, Death, and Exile (SDMB stats, extremely long)

That’s right, I’m back to inflict yet another mind-crushing run through the board’s statistics on everyone. On the slim chance that anyone was paying attention to me, this is the “larger study” that I’ve referenced on a couple of occasions previously. For those who don’t find data to be intrinsically interesting, I’ll try to make the topic as lively as possible – there are even pictures this time! But if that doesn’t work, perhaps you’ll be comforted to know that this will be my last thread on the subject for a while[sup]1[/sup].

Before getting into the thick of discussion, I should say that much inspiration came from Algernon’s Reckoning, kabbes’s Second Hypothesis, and everyone involved in the thread to estimate an active user population. What prompted me, though, was the persistent question of how the subscription plan will affect board activity levels[sup]2[/sup]. The answer, even after all this work, is: I don’t know. But perhaps if I share the data with everyone, some smart person would be able to figure out what the patterns and trends are.

So, the data files are available (and contain a bunch more information than will fit in this post, BTW):[ul]
[li]Basic_Data.xls (148 KB .ZIP) Raw sample data collected for user registrations, posts made, and threads started.[/li][li]User_Analysis.xls (270 KB .ZIP) Sorts users by post count, post rate, and active lifespan.[/li][li]Posts_Threads_Forums.xls (69 KB .ZIP) The average number of posts annd threads made per day. Sorts threads by the number of posts in each.[/li][li]Subscriptions.xls (411 KB .ZIP) Tracks subscribers through the discounted sign-up period, and a tally of more recent subscribers.[/ul][/li]And for reference, my previous two threads on this subject:[ul]
[li]Some SDMB Membership Data[/li][li]Useless SDMB Statistics (and long, too)[/ul][/li]
In way of terminology, member or user will be used interchangeably. Registration refers to the process where one first creates a username, and subscription is a separate process whereby one pays to receive continued posting privileges.

Okay, let’s get to the numbers.

Is the subscription plan going to cut off new blood to this board?
If we look at the number of users and subscribers as well as the ratio of subscribers to members from each month, we’ll see that the two populations mirror each other fairly well until the Winter of Our Missed Content. A bit less obvious of a pattern is that until March this year, while the absolute subscriber count has a slight upward slope, the subscriber-to-member ratio has been on a slight decline (dashed trendlines); whether this is because newer members are less inclined to see the value of subscriptions, or some other reason, I can’t say. It’s interesting to note that while there is a tremendous upsurge of subscribers from the March and April membership (30% of all April registrants subscribed, and they make up 5.6% of the total subscriber population – compared to an average of 1.6% a month between March 1999 and May 2004), the total number of member registrations in those two months more or less stayed flat with the previous months[sup]3[/sup].

This brief subscription boom is easy enough to explain as the result of long-time lurkers who wanted to take advantage of the reduced annual fee offered from March 22 to April 26; it is also not surprising that after this rush, both registrations and subscriptions took a great nosedive in May. But is this a trend? Does this mean new blood has dried up? Well, I can’t tell. If we look at the 2004 registrations in greater detail, we’ll see that it has, on the whole, been declining, and the subscription plan does not seem to have made much of a difference in this general trend. There is a leveling-off or slight increase in registrations since the middle of May, but I don’t know if this is indicative of a new trend, caused by the commonly-held notion that membership influxes coincide with school holidays (which appears to be fallacious – see below), or just normal variation.

How has the subscription plan affected board traffic?
Let’s look at the number of posts made and the number of threads started per day, from May 2000 to around June 10, 2004[sup]4[/sup]. A moving-average curve (thick black line) has been laid over the raw estimations (light blue) to smooth out the variability a bit. I’ve also placed markers to indicate the day the subscription plan went into effect and, for the posts chart, the date the LotR thread was slashdotted. On a very broad scale, I notice (and I may very well be wrong here) a general pattern of a sharp increase in both postings and thread-starts followed by a long decline that repeats on a roughly 15-month interval. This is especially notable because the slashdot/LotR phenomenon did not produce a postings spike as one would have expected. The LotR thread was started on Oct. 10, 2002, and while it may indeed have contributed to the steep postings increase in late 2002, that climb peaked in early December 2002, a full month before noted the thread on Jan. 7, 2003.

Moving 15 months ahead from December 2002 places us in March 2004. The sharp dropoff in activity in Jan./Feb. 2004 is likely due to the Chicago Reader’s decision to throttle our bandwidth. The activity soon picked up again, though, until the subscription plan was introduced. If we ignore this trough (can we? I don’t know), activity levels since March are almost perfectly colinear with with general trend seen throughout 2003, and one may interpret our current downward movement as nothing more than an extension of that line. On the other hand, if the upward movment in Feb./Mar. this year is an indication of the rise predicted by a 15-month periodicity, then it appears that implementing pay-to-post has effectively cut that climb short.

Although the number of threads started has been in decline since introducing the subscription plan, it appears (from the “Useless SDMB Statistics” thread noted above) that each thread now receives a few more replies (mean = 21 vs. 20)), more views (548 vs. 491), and stays active for longer (mean time between thread start and last post, 9.1 days vs. 7.2 days) than before.

21 replies?!? My threads never get that many! Everybody must hate me!
Ha! Watch this thread sink like a lead brick. Seriously, realize that the average (mean) is skewed up by a few runaway monsters such as the LotR thread and current CS favorite Diablo2 talk. Half of all threads, in fact, receive fewer than 10 replies[sup]5[/sup], and more than a quarter get fewer than 3.

Similarly, the mean lifespan of a thread is skewed up by a small number of long-running threads. Instead of the 9.1 and 7.2 day mean shown above, the median (half of all threads have a shorter life than this) is 0.9 days for all threads. If you’re not popular, that’s just because you’re like the rest of us.

Okay if nobody’s replying to threads, why is this board so #&$%*@ slow?!?!?
Beats me! But if it means anything, I can show you when the board is the busiest, based on posting rates. There is no way to retroactively determine viewing rates, and we will have to assume that there is a close correlation between the number of posts made and the number of views in any given time span.

Over a one-week period in mid-May, then, the number of posts made each hour was tabulated. From this, we calculate that, as an overall average, weekend posting traffic is only 68% as busy as weekday traffic (109 vs. 161 posts/hour). When the data are plotted as a function of the time of day, we see that there are two peak posting times each day. During the week, the first occurs between 9 and 10 a.m. CST, and the second between 8 and 9 p.m. During the weekend, maximum traffic occurs at around 2 p.m. CST and again from 8 to 9 p.m. It is no surprise that traffic during the weekend is slower than that during the week, though I was a bit surprised to see that weekend traffic peaked at a later time – but of course, it makes sense that people will rise later on weekends.

Before going any further, I must remind everyone that the calculations above are based on only one week’s worth of numbers, and we should be careful about extrapolating them towards broader patterns.

Well, how much traffic can the board handle?
From looking at the history, we see that the maximum number of posts made in one day is estimated to be around 6,200. Compare this to the ~3,800 average posts made per weekday in mid-May. Although there is headroom above today’s traffic level, we’d also just suck the Reader’s pipes dry if given the chance, which is Not Nice.

A related question: how many new members can the board take on each day?
From a rough estimate of the daily registrations, we see that the greatest number of new members were added in early January 2003. A bit more data excavation reveals a similar (but not so long-lasting) spike just as the board returned online after the Winter of Our Missed Content. A detailed review of these two periods shows that post-WOOMC registrations peaked at 147 for one day before quickly settling down into a steady weekly rate. On the other hand, post-slashdot registrations peaked at 154 and did not decline significantly until the weekend. Registrations remained above normal for 3 or 4 weeks before settling back to a steady state. Assuming that the initial flood rate from the slashdot effect is essentially infinite, it appears that the maximum number of new members for the SDMB’s current setup is about 150 per day. We should remember here, however, that there was not a concomitant increase in posts made at that time, so perhaps theses extra registrations drained away the resources for needed these new members to make posts.

Speaking of new members, is there really an influx of newbies each summer?
Ah, school holidays. Time for trolls and idiots to be let loose on the boards. That’s the conventional wisdom, anyway – but is it true?

From looking at the member registrations, new posts, and thread starts for each month (alternatively, see the individual graphs for members, posts, and threads), it’s hard for me to discern any rise in activity that’s specifically associated with the summer months. From this, then, I’d have to conclude that the “idiot influx” is more fiction than fact. With high-speed Internet connections available at universities, I also can’t see any compelling reasons for a student to wait until school is out to register here. Now, this notion may still contain a small kernel of truth in that, on average, a large percent of members register but never post, and the summer registrants may be more likely to post (and more obnoxiously – therefore getting undue notice) than those from other times. But I don’t have the data to show whether this is really the case or not.

So really, how many people sign up but never post?
From the entire user base, samples were taken at an interval of once every 50 UserIDs. Out of the resulting 912 data points[sup]6[/sup], 354 users show to have never posted. This calculates to be 38.8% of the sample group; if the sample is an accurate representation the full population, then at nearly 47,000 members (as of this writing), we can estimate a total of about 18,000 users who have never posted. In fact, the sample is heavily skewed towards members who either never or rarely post:

**Post Count  Users   %**
     0       354  38.8%
   1–10      336  36.8%
  11–100     113  12.4%
 101–1000     87   9.5%
1001–5000     18   2.0%
5001–10000     3   0.3%
    >10000     1   0.1%
     *Total*   912   100%

The pattern is similar for post rates:

**Post Rate   Users   %**
<0.01/day    553  60.6%
0.01–0.10    234  25.7%
0.11–1.00    103  11.3%
1.01–5.00     20   2.2%
5.01–10.00     2   0.2%
    >10        0   0.0%
     *Total*   912   100%

Regarding the members who post with the greatest frequency, we know there are those whose post rates exceed 10/day, but they are not captured by the sample, and one may perhaps assume that they make up just a minuscule proportion of the overall membership.

That’s a lot of lurkers! Altogether, how many posts do they make?
The 912 users in the sample made a total of 92,123 posts. Taking the same template as above:

**Post Count  Posts    %        Post Rate   Posts    %**
     0          0   0.0%      <0.01/day     399   0.4%
   1–10      1011   1.1%      0.01–0.10    4753   5.2%
  11–100     4223   4.6%      0.11–1.00   37091  40.3%
 101–1000   29625  32.2%      1.01–5.00   32508  35.3%
1001–5000   27207  29.5%      5.01–10.00  17372  18.9%
5001–10000  19100  20.7%          >10         0   0.0%
    >10000  10957  11.9%
     *Total*  92123   100%           *Total*  92123   100%

Convesely, how many people are active?
What, you don’t like this previous heroic effort? Okay, okay, all kidding aside, since it’s probably healthy to inspect the data from other perspectives, it should be instructive to go through with this exercise here. First of all, we need to define what active user means. Algernon’s reckoning is based on two observations of users who participated in threads over a two-week span; by this method, then, the active user population comprises users who have posted within the past two weeks. Applied to the sample[sup]7[/sup], we find 70 users[sup]8[/sup] (7.9% of sample) who fit this definition. Extrapolating to the full member population of 45,660 users[sup]9[/sup], this calculates to equal 3,587 active users. This is lower than Algernon’s estimate of 3,806 active users, so is one of the numbers wrong? Perhaps not, if we take the following factors into consideration:[ul]
[li]At a sample size of around 900 users, the margin of error at a 95% confidence level is around 3.3%. This means that my sample will yield a population of 3,705 active users at the upper end of the estimation range.[/li][li]With Algernon’s sample size of around 2,200 users[sup]10[/sup], the margin of error is around 2%. Applied to his results, this means a population of 3,729 active users at the low end of the estimation range.[/li][li]The two estimation ranges are close, but don’t overlap. However, the time lag from Algernon’s sampling (ending March 23, 2004) and mine (ending April 17, 2004) may have contributed to this slight difference, as board activity has been on the decline (see the post rate graph, referenced above) in this period.[/ul][/li]
In Ed Zotti’s announcement for the subscription plan, he mentioned an active population of 7,000 users over the previous 30 days. So if we look at the sample again with a 30-day timespan and use the same “posting users only” definition for activity as above, we find 93 users in this group, which extrapolates to 4,663 users out of the total member population[sup]11[/sup]. If, on the other hand, we include everyone who has logged in, regardless of posting activity, within the 30-day period from March 18 to April 17, 2004, we find 146 users from the sample who fit this broader definition of activity. This extrapolates to 7,482 users out of the total population. This result is somewhat higher than Ed’s published figure, but I believe we can reconcile the two if we take into account the surge in activity as users logged in to subscribe[sup]12[/sup] during the timespan covered by my sampling.

We can see that different definitions produce greatly different estimates of the active membership. In my view, perhaps a more accurate depiction of this population would include posting users and recent registrants who may not have yet posted, but exlude the “invisible” members who log-in but don’t post. Applying these criteria and a time horizon of 30 days to the sample, we find 99 users in this group. Extrapolating to the full population, the resulting 5,073 are what I (yes, rather immodestly) call True Active Users.

What is still unclear to me, though, is whether active members, however defined, make up a percentage of all registered members (and therefore will always increase in number) or consist of a fixed number of users, with the influx of new members balancing those who have dropped off the boards. It is also unclear, as yet, the effect that subscription will have on these figures.

Well then, how many people have dropped off the board?
If we define lapsed members as those who have shown no activity – not even log-ins – since the subscription plan began, then there are 752 users[sup]13, 14[/sup] (84.4% of the sample) who fit into this category. This extrapolates to 38,537 users, based on a population size of 45,660.

An interesting statistic we can learn from looking at the lapsed user population is the length of time that one remains active on the board[sup]15[/sup]. Analyzing these 752 users reveals that 87.5% have a board lifespan of 1 year or less. This heavily-skewed pattern is repeated for shorter timespans as well (breakdown of population within the first year and first month), until we see that over one-third of all lapsed users are active on the board for one day or less. An even more striking fact emerges if we drill in on users with zero posts (lifespan distribution, first year, and first month): nearly a quarter of all lapsed users registered, never posted, and stayed on the board for just one day or less. One wonders why they even bothered.

Another way to view lapsed memberships is to plot the number of users in terms of their last-login dates. When compared to the number of new members each month, we see that the registration (or birth) rate and last-login (or death) rate have only a loose correlation. What this means, I don’t know. From plotting this data as a cumulative quantity over time, it appears to me that the rate of increase has three distinct slopes, shown as blue lines on the graph, separated roughly 15 months apart (there it is, again). The most obvious break occurs between December 2002 and January 2003, and can also be seen as a large change in the average monthly last-login quantities before and after this date. There is, of course, the possibility that I am imposing a pattern onto the data that doesn’t actually exist.

And how many people have been kicked off the board?
From the sample, we find 38 users who show BANNED as their status, or 4.7% of the population[sup]16[/sup]. By extrapolation, then, we calculate that more than 2,000 users have been banned up to this point – which, over the 5-year history of this board on the web, works out as an average ban-rate of slightly greater than one per day. For what it’s worth, 5 out of the 38 users in this group were banned before getting to post, and 6 were banned after just one post.

Can you predict how long a user will last on the boards based on how often they post?
In a word, no. A post count can be used as a marginally effective retrospective indicator of a user’s board age (“how long ago did he register?”), but that’s only because it takes time to rack up a large number of posts, and there are many longtime members with few posts to their credit; so, we don’t really learn anything from this one piece of data, and it certainly doesn’t have any predictive power. As it turns out, one’s post-rate (number of posts made per day) is no indication of lifespan, either. The correlation coefficient (r) between post rate and board age for all members in the sample is a tiny 0.06. As may be expected, the correlation improves with active members, but only to 0.17. Interestingly enough, for subscribers, r is a mere 0.08.

How has subscription affected participation in each forum?
See the number of threads active in each forum as a percentage of the total number of threads in all forums over specific time periods:

**         2004-03-22/   2003-03-23/   All Dates
         2004-06-14    2003-04-22**
**ATMB**        2.25%         1.51%         2.22%
**CoCC**        0.79%         0.92%         1.14%
**CoSR**        0.28%         0.38%         0.55%
**GQ**         34.02%        35.71%        35.38%
**GD**          6.72%         6.42%         6.68%
**CS**         17.86%        17.17%        11.40%
**IMHO**       13.67%        12.78%        11.39%
**MPSIMS**     16.76%        17.23%        23.64%
**BBQ Pit**     7.64%         7.88%         7.62%

From the above data, by comparing the time period since subscription started and one year prior to that, we can see that relative participation levels for each forum, in terms of threads active, hasn’t changed substantially. If we look back to the beginning of this board, though, it’s interesting to note the nearly symmetrical drop in MPSIMS activity and rise in CS activity, which suggests that the creation of Cafe Society offloaded traffic from MPSIMS but no other forums. Also, seeing the offloading effect that CS had on MPSIMS, and noting that the combined traffic from these two forums is roughly equivalent to GQ traffic, I wonder whether any benefit would be derived from fine-tuning GQ and perhaps creating another forum to relieve it of some topics.

Anything else?
What, that wasn’t enough? Yes, I realize some of the information is not all that recent, and I should be able to post a follow-up with the more easily-updated data – but I’m not going back to look at all those member profiles again, no way.

[li]An item that remains unresolved from the “Useless SDMB Statistics” thread is the composition of members who post to each forum. It is casually accepted that not all members participate in all forums, and a glance at the gamut of post-counts and view-counts shown on the SDMB homepage would seem to indicate the truth of this notion. However, it has not yet been satisfactorily established if it is more common for a member to browse (and we’ll need to use actual posts as a proxy) only one or two of the forums, or to browse most of them. It will also be interesting to see if there are correlations in member participation across forums, and if population clustering exists (e.g., is a CoCC participant likely to be found in CoSR? How often does that person frequent MPSIMS?). But since I haven’t figured out a good way to collect samples, I won’t be tackling this question any time soon.[/li][li]Did the pay to post change the activity rates?[/li]Effects of paid subscriptions to SDMB
Differences on Straight Dope since going “pay for say”
[li]Then again, staying flat may be construed as a substantive increase because of the bandwidth restrictions that the Chicago Reader placed on this message board earlier in the year.[/li][li]For posts and threads started before April 28, 2000, the timestamp data is unreliable – in other words, a higher PostID doesn’t always correspond to a later posting timestamp – and thus had to be discarded. There are also a large number of users who show last actitivies on that day, which leads me to believe that that’s the date of a major software or hardware migration (from UBB to vB, perhaps?) for this message board.[/li][li]Similar results are seen from both a complete survey of threads active within the last 12 months (cf. “Useless SDMB Statistics”) and a sample of all threads started since the beginning, captured in the file Basic_Data.xls. The quantities shown in Basic_Data.xls is the total number of posts in a thread, which is the number of replies plus one (for the OP).[/li][li]Because most of the user profiles were tabulated from Aptil 14 to April 17, 2004, only data collected from these dates will be used for population calculations. Otherwise, time-dependent quantities (e.g., post counts) from this data set cannot be reconciled with those collectd from (much) later dates.[/li][li]For unknown reasons, not all user profiles contain last-login dates. Removing these profiles reduces the sample basis to 891 users.[/li][li]The sample base of 891 users is sorted by last-login date, and we eliminate those that fall outside of the two-week period between 2004-04-04 to 2004-04-17. From these profiles, we first sort by post count and remove users who have never posted; for the remaining population, we then perform a manual search of the actual posting history and further remove users who did not post within these dates. We find 70 users to remain; this is 7.9% of the sample base (70/891).[/li][li]At the end of April 17, 2004, the UserID stood at 45,660. There is a slight discrepancy (around 100 or so – it varies over time) between the number represented by the UserID and the number of members shown on the SDMB homepage. I am guessing that this is due in large part to removed users, and we can use the UserID as a fairly accurate representation of the actual number of members who have registered for all time.[/li][li]Actually, I need some help here. Algernon’s method captured 2,139 and 2,240 users during his two observing sessions, with 1,259 names found common to both samples. I don’t know if the classic sampling error formula can be applied to populations captured over multiple passes or not, and (if it can be) whether the number to use is the size of each sample or the size of all unique users from all observations (which calculates to be 2139 + 2240 - 1259 = 3120).[/li][li]Remember, the sample population used here is 891, and the “full population” is 45,660. The time period involved is 2004-03-18 to 2004-04-17.[/li][li]Not everyone who logged in to subscribe wrote posts. Of the roughly 3,800 subscribers at the end of the discounted-fee period (April 26, 2004), 7% had a post count of zero. Activity from these non-posters goes towards explaining the divergence of my estimates from the figures published by Algernon (posting users only; my estimate is lower) and Ed Zotti (all log-ins; my estimate is higher) – in other words, in the sample period, more people logged in, but fewer posted.[/li][li]The sample period ended on April 17, 2004, which I realize makes the data very dated.[/li][li]Because the cutoff dates used to define active and lapsed members overlap slightly, their numbers (752 + 146) will add up to be larger than the 891 users shown in Note 8.[/li][li]What we learn from the lifespans of lapsed users will be applicable to the board population as a whole if the board has constant turnover – in other words, if we know that every member will drop off at some point. I realize that eventually everyone will die a physical death and thus cease participating on the boards, but that can be treated as being infinitely far into the future in terms of Internet time, and I don’t know if we can say with any certainty that every member will leave the board within some shorter period of time. Put another way, the members from early 1999 who are still with us (the right-hand tail of the board age distributions chart) may either indicate a certain percentage of members who will be active essentially forever, or these members may too fall away in a few more years; it’s too soon to tell.[/li]Similar to last-login dates (see Note 7), not all profiles contain a member’s status. From the original sample of 912 users, there are 100 such omissions; this, then, reduces the sample population down to 812 for calculations where this classification is a factor.[/ol]

: applause :

Nice job Earthling. I only had time to briefly skim this. I’ll be back later with observations and questions (but others will likely beat me to it anyway).
While I appreciate the nod that you’ve given to me and kabbes, you’ve taken membership analysis a quantum leap forward. To reference a famous quote, you’ve seen further not because you’re standing on the shoulders of others, but simply because you are taller. [size](more ambition and more patience to name a couple ways you are taller).[/size]

That 15-month periodicity you notice (and which I notice too) is puzzling. Any speculation as to a mechanism for that? And while we’re on the subject, do you have a Fourier analysis of the post and thread curves? I’d like to be better convinced of that periodicity, and possibly also find others.

The best guess I can think of for a 15 month period is that it corresponds to the schedule on which Jerry and the Reader perform major hardware upgrades for the Board’s servers. I wouldn’t have expected there to be a particular schedule for that, but I can’t think of anything else that could account for it. I’d expect to see some periodicity at 1 day, 1 week, and 1 year, and possibly 1 month, due to human activity patterns, and I might be willing to accept an emergent-phenomenon period on the order of a few days, as conversations wax and wane, but there’s not much that happens every 15 months (especially considering that that’s competing with one of the “natural” periods, at 1 year… I would expect anything with a weak periodicity at around that level to be forced into a 1 year periodicity).

I want to have your babies.

OK, I still haven’t read closely, but I had to comment on this:

Heh, heh. Amen brother! I know exactly how you feel.

Great job with the stats, but I have a question: How in the hekk can you get banned without a single post? Did someone say “I’m gonna use a sock named X” and the mods ban X immediately, or what?

I think the way it works silenus is that a new registrant can be recognized as a sock based on the IP address. If it matches the IP address of an already BANNED member, then the new registrant gets BANNED also.

TubaDiva may be by to correct me. Or not. I have a faint recollection that our beloved Mods and Admins don’t particularly want to reveal their methods.

Well, there are lots of ways to get banned by a single post. Frinstance,

  • “Hey, here’s a website where you can see naked women with big tits!”
  • “Come to my website and buy my CD!”
  • “Do you want improved performance in bed? This website offers astounding new medical advances…”
  • “Us white Protestants got to get together and take the country back from those [Irish, Jews, blacks, Asians, Texans, liberals, whatever]”
  • “Here’s a cool way to steal money from your neighbor’s bank account without any one finding out…”
  • “I used to be XXXXX and I got banned, and I don’t think it was fair, just because I ignored sixteen warnings from Moderators not to call my opponents ‘dumbass’ in Great Debates…”

Earthling, those are amazing statistics, and I’m in awe of you. I haven’t poured through them, but I do think there are cases where median is more useful than mean – like, the “average” number of posts to a thread. We get a few threads with many, many posts and that overwhelms a hundred threads with one or two posts. Hence, median (or even mode) might be a more useful statistic.

No, I hadn’t thought of doing a Fourier analysis on them. I worked on it a bit last night but (my limitations are showing) couldn’t quite figure out how to approach it, given that the samples were taken at fixed intervals of PostIDs, rather than fixed intervals of time; plus, there’s the big hole during the Winter of Our Missed Content.

Scrutinizing the data last night, though, I noticed a mistake – on the chart, the moving average curve is labeled as having a delay of 7 days. This is incorrect. Instead, the delay is of 7 sampling points. Yar.

Sometimes, that’s exactly what happens. As an example, one of the inglorious bannees came in with the name uncleboorsucksthreeeggs and got zapped pretty much instantaneously.

Wow. What does one say? Nice work Earthling!

Wow. Someone’s bucking for a promotion. It’s probably that pederast Hanrahan.

And recall that such “highly valuable” posts are often OP’s of new threads, and get transported out of public view. (I do not know, and am not asking, whether SDMB retains a visible-to-Mods.-or-Admins.-only archive of such crap for legal/troll management purposes or deletes them entirely – either way, they’re not available to our diligent statistician members.)

He dropped two big ones!

I am in awe, Earthling. You did a wonderful job, IMO

Wow. Very impressive from start to finish.

I don’t understand what the hell could possibly have motivated you to do all that… but you did an amazing job.

IMHO, there haven’t been enough 15 month periods in the Boards’ history for the pattern you noticed to be statistically significant. I’m putting my money on it being a random occurrence.

Me? Not at all. I don’t have any specific areas of expertise, and thus won’t qualify for SDSAB, and I certainly don’t want the hassles associated with being a mod.

Well, I like data, and I have time on my hands. What ended up as this thread started off as an attempt to get some factual information so that questions regarding pre- and post-subscription board behavior can be answered with something better than speculation and anecdotal evidence – but then took a life of its own (and took over my life). Maybe I can stick this on my resume when prospective employers ask, “so, what have you been doing with your time,” eh?

You may very well be correct, and I was certainly astonished to discover this periodicity. Without being able to fit it to some theoretical model, though (any help, guys?), the only way to find out if this is really true or not is to wait and see.

I would prefer not to discuss this overmuch, you’re correct.

Most plausible story, though is this: In the past we used to delete objectionable postings wholesale, so someone could have made a posting, had that post deleted, and then banned, which would give them a post count of 0.

your humble TubaDiva

I wouldn’t say that. Having an area of expertise certainly helps, but it’s not entirely necessary. Clearly, you can write very well. Equally clearly, you are very good at doing research, which is probably 90% of the job anyway. Personally, I think you’d do well at it. :slight_smile: