That only tells you the passwords are the same.
148 karma · joined August 11, 2021
That only tells you the passwords are the same.
Seems to be a meaty thread if anyone else is curious.
For everything else, just ask the community what they want. If they don't like Donald Trump in the conversation, then he's gone. Donald can then attempt to find a community (subreddit) that accepts him. That community can be quarantined or banned if people really don't like it.
Thank you for the feedback. I strongly suspect I'm wasting my time :(
It's definitely a huge draw back that you'd risk such important information.
I broadly agree but invites aren't complex. See lobste.rs
Yes, there is an issue of increasing the difficulty if signing up for real users but once accounts are tied to real identities doesn't that allow crowd moderation?
- person whose fallen into your apparent fallacy
Do you just test them separately? For example, mock out the db when testing the app and then sequentially test the db to make sure the sql statement works as expected. However, this explicitly doesn't test the integration.
I ask because I'm still trying to find a good solution for my project.
I feel like machine learning isn't at the level where it can tell if something is misleading, unless it's from a known sketchy source.
> (if they have a preference over which action will be taken) are incentivised to give more extreme answers.
With yes and no answers, how can answers become more extreme? If you are asked "Is this misleading? Yes/No" and it's only marked as misleading when "Yes" is the majority, then you are incentivized to answer with your true opinion. If you want the post to be marked misleading, then answering yes increases the chance that it is marked as such.
The bayesian truth sereum information score makes sense when you are trying to reward people for truthfully answering your questions; for example by paying them [0]. When asking "Is this misleading?", how do you use the information score to compute who won?
[0] - http://www.eecs.harvard.edu/cs286r/courses/fall10/papers/DW0...
The problem: how can I make decisions based on a sample with a binary question. I think the central limit theorem applies, and I need to account for various priors and missing votes. Is there an existing solution to this problem? The server is written in nodejs, if that matters.
https://arstechnica.com/science/2019/11/nasa-report-finds-bo...
https://support.google.com/voice/thread/1592118/wellsfargo-s...
My goal was to be more secure than an out of date wordpress site - which I think I have achieved.
I don't really understand the harm that can come from an email/password/ip leak, besides spam or stolen accounts if they reuse their password. Do you have a link that might impress the seriousness of the situation on me?
It's even open source!
The main issue is the more difficult sign up is, the less people sign up. It's a balancing act.
With any voting system you have to detect the validity of the votes, even upvotes.
I'm currently trying to build this but I'm not a programmer so it's slow going. I'm interested in your thoughts as I'm sure I'm missing something obvious.
The main recommendations that I didn't know was request size limits - though I'll probably set the limit in ngnix.