There are downsides with downloading their app just to input bad data, but it’s a fun thought.
edit: While we’re at it we might as well offer an alternative app to people.
I posted in !opensource@programming.dev to collect recommendations for better apps
The post: https://lemmy.ca/post/32877620
Leading Recommendation from the comments
The leading recommendation seems to be Drip (bloodyhealth.gitlab.io)
Summarizing what people shared:
- accessible: it is on F-droid, Google Play, & iOS App Store
- does not allow any third-party tracking
- the project got support from “PrototypeFund & Germany’s Federal Ministry of Education and Research, the Superrr Lab and Mozilla”
- Listed features:
- “Your data, your choice: Everything you enter stays on your device”
- “Not another cute, pink app: drip is designed with gender inclusivity in mind.”
- “Your body is not a black box: drip is transparent in its calculations and encourages you to think for yourself.”
- “Track what you like: Just your period, or detect your fertility using the symptothermal method.”
Their Mastodon: https://mastodon.social/@dripapp
“A bunch of new accounts posting obviously worthless data joined about the same time. Disregard them.”
So you’re saying if a woman made an account during this time, and threw garbage data in, they’d disregard it and then a month later she could use it for real?
(Also you guys are hilarious about how quickly you can just ‘do that’ because I’ve never worked at any software company where the devs who made the initial code are even still at the company a year or two later.)
This is data analysis, not development. Yes you can just exclude the problem month, average the previous and next months, and her real data starts to contribute again. And yes you can do that regardless of who is writing code. Or even that the code was written by your company and not some other company you bought or seized data from.
probably won’t be hard to spot all the accounts that sign up en masse, send 3 data points then stop forever because they got bored or forgot.
Alright, sure. The company will rigorously dig through the data to exactly remove exactly the specific accounts that aren’t real and deftly deal with it, and it won’t be some intern with a weeks training in paper docs from three years ago. No, it’ll be people who will know to do exactly those things. And the data you’re scraping to sell, well, no-one will mind you splicing out data you claim isn’t real and was fake, no they’ll be fine with that. Then when that intern is gone–and they didn’t log anything because they were never taught to–and the new intern arrives, they’ll know to continue exactly where they should, and at no point will anyone fuck up the dates, times, or additions from previous months. At each and every stage exactly what has to happen will happen, and no code changes, updates, or manager-directives will change any of these parts in any way. The addition of anywhere from dozens to hundreds to even tens of thousands of new accounts will be easy to deal with, because this has all been prepared ahead of time, and will immediately be dealt with. It won’t take weeks of meetings on how to tackle it, by whom, and what to push back - because they use waterfall/agile, and it’s a foolproof system where you don’t just punt things forward, you deliberately and delicately lay out each and every change that will now take place mixed with the 2 years that have already been planned out.
Absolutely everything will be covered and not a single thing will get through, and they’ll carefully and easily parse through the data with zero issues on the demand of a very competent government that doesn’t show any signs of issue whatsoever.
Nah they’ll just say “weird. Guys, exclude November, it’s an outlier”.
Okay cool, so the women who make accounts then can still use them, awesome.
Yes absolutely they can
You know the purpose of this is so they can use them without being tracked though, right? If it’s easy to exclude outliers and bad data, it makes this suggestion pretty useless.
As people have suggested, there’s almost no reason to ever have this data leave your own personal device or network. Women have tracked their periods for thousands, maybe hundreds of thousands of years.
I’m willing to bet it uses something resembling an SQL database on the back end, so ignoring or deleting data or entire user accounts that signed up in November 2024 should be a matter of a query or two.
I would also like to point out that, much like the Republicans, you’re painting your enemy as both dangerously competent and hilariously inept, whichever is most convenient at the moment. “They have a database of menstrual data, they can use data science and pattern analysis to detect changes in a woman’s reproductive cycle and use that information to make decisions to harm her!” minutes later App developers are rock chewing morons, there’s no way they could detect a pattern of strange data entering their database all at once, figure out what it is possibly by googling the name of their app and finding a Tumblr post about polluting the app, and then cancel those suspicious accounts."