Dan Q
This is a repost promoting content originally published elsewhere. See more things Dan's reposted.
Known Leaders is an open-source program that combines WikiData with a random generator to come up with almost-invariably inaccurate but sometimes hilarious facts. Jim Kang came up with it during Recurse Center‘s Never Graduate Week. Go have a play, or read more about how and why he made it.
When geocachers find a geocache, they typically “log” their find both in the cache’s paper logbook and on one of the online listing sites on which the cache’s coordinates can be found.1
I’ve been finding and hiding geocaches for… a long while, so I’ve seen lots of log entries from people who’ve found my caches (and those of others). And it feels to me like the average length of a geocaching log entry is getting shorter.
“It feels to me like…” isn’t very scientific, though. Let’s see if we can do better.
To test my hypothesis, I needed a decade or so of logs. I didn’t want to compare old caches to new caches (in case people are biased by the logs before them) so I used Geocaching.com’s own search to open the pages for the 500 caches closest to me that are each at least 10 years old.
I hacked together a quick userscript to save all of the logs in a way that was easier than copy-pasting each of them but still didn’t involve hitting Geocaching.com’s API or automating bulk-scraping (which would violate their terms of service). Clicking each of several hundred tabs once every few minutes in the background while I got on with other things wasn’t as much of an ordeal as you might think… but it did take a while.
I mashed that together into a CSV file and for the first time looked at the size of my sample data: ~134,000 log entries, spanning 20 years. I filtered out everything over 10 years old (because some of the caches might have no logs that old) and stripped out everything that wasn’t a “found it” or “didn’t find it” log.
That gave me a far more-reasonable ~80,000 records with which I could make Excel cry.2
It looks like my hunch is right. The wordcount of “found” logs on traditional and multi-stage caches has generally decreased over time:
“Did not find” logs, which can be really helpful for cache owners to diagnose problems with their caches, have an even more-pronounced dip:
When I first saw that deep dip on the average length of “did not find” logs, my first thought was to wonder whether the sample might not be representative because the did-not-find rate itself might have fallen over time. But no: the opposite is true:
Strangely, the only place that the trend is reversed is in “found” logs of virtual caches, which have seen a slight increase in verbosity.
Within the limitations of my research (80,000 logs from 500 caches each 10+ years old, near me), there are a handful of clear trends over the last decade:
Are these trends a sign of shortening attention spans? Increased use of mobile phones for logging? Use of emoji and acronyms to pack more detail into shorter messages? I don’t know.
I’d love to see some wider research, perhaps by somebody at Geocaching.com HQ (who has database access and is thus able to easily extract enough data for a wider analysis!). I’m also very interested in whether the identity of the cache finder has an impact on log length: is it impacted by how long ago they started ‘caching? Whether or not they have hidden caches of their own? How many caches they’ve found?
But personally, I’m just pleased to have been able to have a question in the back of my mind and – through a little bit of code and a little bit of data-mashing – have a pretty good go at answering it.
1 I have a dream that someday cache logging could be powered by Webmentions or ActivityPub or some similar decentralised-Web technology, so that cachers can log their finds on any site on which a cache is listed or even on their own site and have all the dots joined-up… but that’s pretty far-fetched I’m afraid. It’s not stopping some of us from experimenting with possible future standards, though…
2 Just for fun, try asking Excel to extrapolate a second-order polynomial trendline across 80,000 pairs of datapoints. Just don’t do it if you’re hoping to use your computer for anything in the next quarter hour.
3 With stricter guidelines on how a “virtual rewards” virtual caches should work than existed for original pre-2005 virtuals, these new virtuals are more-likely than their predecessor to encourage or require longer logs.
Max credit to garry (@repeattofade) for the original toot. All I did was adapt it into a motivational poster.
The thing I’m wondering is whether that bus lane is one that a bi-cyclist like me can use? 😂
