Ultranormal

Tag: moderation

  • Mid-caffeination Mastodon Thoughts

    Derek Powazek posted this on Mastodon yesterday:

    An actual use for machine learning that I’d want: a bot that records all the posts that cause me to block someone, saves them into a db, and then automatically hides posts that match above a certain threshold.

    Derek on Mastodon

    I love a good brain exercise, so I’ve been thinking about it, and I don’t actually think this is that hard, and is very possible using tools you already need to run Mastodon in production.

    I might play with actually implementing this during my week off around cooking and family time, but if someone else wanted to do it, this idea is 100% free.

    To enable search in Mastodon, you have to install and use ElasticSearch. It has machine learning goodies in it already like nearest neighbor and vector search.

    Basically, we should be able to build a very personal spam/block bot for Mastodon given some training data (posts that pushed you to block someone) and some fiddling about (which is the hard/fun part).

    Right now, there are no dates on blocks in Mastodon (I haven’t checked the schema yet to see if they’re there but not returned), and you can’t see which post “triggered” the block. I think that could be added fairly easily – or at least something like “Add this to Blockbot” to use it to train the bot.

    Mastodon doesn’t really have a plugin architecture yet, so I’m not sure if this should be a standalone app that sits alongside your running Mastodon instance or a feature – I’ll probably try it as a feature to get familiar with Mastodon.

    Basically, we take “blockworthy” posts, index them, and then use that to compare posts to the blocklist to get a semantic distance. Once we have the distance we can start manually testing for accuracy and tweak settings until we get something close to a “block score”. Users could then say, “yep, don’t show me anything with a block score greater than 1.5” and ta-da, a little robot janitor is just cleaning up your feed for you. That’s probably computationally intensive to do on every post, but I think you could apply it to people you don’t follow who reply to you to weed out the worst Reply Guys and riff raff.

    You could also have community-wide block bots that are trained on a communal collection of blockworthy posts. It could help get around rigid blocklists by allowing targetted removal of replies from timelines instead of blocking whole instances.

    It could also be used for finding good stuff too… Imagine something that found you people who post things like you do and brought them to you. It could be used as an “attract” bot as well.

    I think ideally, it could be used like left and right handed whuffie. When you come in contact with a profile, how alike and how different are your posts from theirs’? Do we agree on anything? Are our disagreements strong enough, and on topics that are sensitive enough, that I probably don’t want to engage with them? Then it’s more informative than just a robot going out and sweeping up my replies.

    Yeah, this is hand wavey, but a lot of this stuff is just built in to ElasticSearch already, so it’s not like we have to invent anything (yay, because that’s hard). We just have to assemble it and feed it enough data.

    It should be fun, and I think it could be helpful, especially for folks who get inundated with awful replies.

    And if you beat me to implementing it, that’s great! Then it’ll be out there in the world and we can all play with it!

  • Agile Moderation

    I read a lot of advice – on any social media platform it’s hard not to. Everyone spouts endlessly about hustle, self care, the grind, being the best you, on and on forever. There are memes and videos and heartfelt shout outs to gurus and coaches.

    All of that advice is fine, but it always leaves me cold. It all feels so extreme and if you fall down one rabbit hole of advice or another, it will probably lead to a lot of unhealthy behavior.

    I’m a developer. I’m incredibly hard on myself. I work with people who are also incredibly hard on themselves. They all seem to feel worse about themselves than I do, and I’ve been trying to figure out why – and what I do or what experience I have that tells me when to let up on the self-criticism.

    It’s taken a while but I think I’ve figured it out.

    I’ve been doing some form of agile development for a very long time. More than a decade but less than two. It’s fine and I’m not going to go into details about it because it doesn’t matter.

    My favorite part of that process, though, is the retrospective. It’s where the entire team gets together every two weeks and answers three questions:

    • What went well?
    • What didn’t go well?
    • What are we going to do differently next time?

    It’s a chance for the team to refine their process, learn how to work better with each other and improve personally. The best part is that my teams always write everything down so we have a record of our retrospectives over time so we can see our growth over time.

    It’s so effective that I now use it on myself. And this is where the moderation from the title comes in. Every time something goes wrong or I’m under stress, I go through those three questions. It’s calming, and a chance to reflect and commit to doing better.

    But, it’s not open ended. I can’t spent forever on how badly I messed up or on how great I did, and I always have to finish with how I’m going to improve.

    That process allows me to continue to be self critical, continue to hustle and not just love through the grind of startup life, but to love it, take care of myself and be aware of what I still need to work on.

    The goal of agile isn’t perfection; it’s constant, sustainable, incremental improvement. That’s a goal I can get behind for myself too.