On 08/11/17 17:01, Ivan Necas wrote: > And, if we meet in some time (let's say 6 months from the kick off) > and look at the numbers, I think it would be much easier discussion > if we should ditch the list or not. Additionally, we would have 6 > months of hands on experience with Discourse.
I'm going to assume we're talking about side-by-side for a single channel (i.e the users list). I'll focus on that, but I remain open to the option of running -dev on a list and -users on a forum, we can make that work. Still not my top choice, but doable. So, I'm all for following the data - in fact I'm actually studying Data Science at the moment in my spare time so I can be better at this for our community metrics in general (this course [1], good fun). What I think you're proposing is that we measure the amount of activity on both platforms after 6 months, and then use that as an indicator of how much people *like* each platform. The problem is that this experiment contains both systemic bais and a confounding variable. Firstly, the systemic bias: people will stay where the conversation is (i.e. the network effect). Unless everyone moves, no-one does. If we had zero users on both platforms at the start, this could probably be accounted for, but that's not the case. Secondly, the counfounding variable (nemesis of all data scientists). You're suggesting that "amount of activity" on a given platform (X) can be used to infer "willingness to use" that platform (Y). But this doesn't account for the procrastination problem (there are studies, I picked a couple [2,3]). People don't change if they don't *have* to, however much better the alternative is. So there's a variable affecting X but not Y that we can't account for, which means we can't use it for inference. > I'm not suggesting 100% agreement, on the other hand I'm serious > about listening carefully to the people that actually ARE active in > the community. 100% agree with that, that's exactly what this thread is for. I'll post that summary I mentioned shortly to try and loop some more voices in. Cheers, Greg [1] https://www.coursera.org/specializations/jhu-data-science [2] Opt-in vs opt-out organ donation - much higher donation rate with opt-out. People could *save lives* by filling out a form, and they don't. https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-014-0131-4 [3] Electricity costs. 14 million houses in the UK could be saving £200 per year (2016 data), but they don't switch. UK is actually considerating putting automatic tariff switching into law because people are so bad at this. https://www.gov.uk/government/publications/household-energy-savings-through-switching-supporting-evidence/many-households-could-save-around-200-per-year-through-switching-energy-supplier-basis-for-claim -- You received this message because you are subscribed to the Google Groups "foreman-dev" group. To unsubscribe from this group and stop receiving emails from it, send an email to foreman-dev+unsubscr...@googlegroups.com. For more options, visit https://groups.google.com/d/optout.
