Your audience and the algorithm
So, what’s a social media algorithm? Algorithms are made by people who are trying to be smarter than every other smart person in the world for the sake of earning money for the corporations that feed their families. Now some of these people are the best software engineers that money can buy, while the rest are ordinary people like you and me, so if you think the sum of their average intelligences is below your intelligence level, you’re more than welcome to try and outsmart the smartest people on the planet. For the rest of us, it’s about understanding how much we can give to social media sites without them taking more than we can handle. Otherwise we burn out. It's not a coincidence that social media sites happen to be black hole vortexes which suck all sense of self-worth out of our person if we approach them incorrectly.
Outsmarting the algorithm is a high risk play. Maybe you’re up to the challenge.
For this guide we present two high-level approaches:
Approach A: Playing smart (Top-down approach)
Figure out what it wants. Social media algorithms don’t exist out of nothingness; they are created with aims and goals. The company is trying to make its users spend more time on their website.
Research the company’s goals. Look at their feature rollouts, look at what they’re announcing to the media, try to figure out the strategy they’re aiming for. Make a few different types of social media posts at different parts of the day and different times of the week to see which ones do better, and try to think back to the company’s aims and objectives (since software engineers have to design the algorithm, and get approval before they do things to the core product, right?)
Timing your social media posts is a strategic decision which should be determined from input from macro trends (AKA what you get when you search “best times to post on social media”), intersected with info points from the micro level you’re working at: the unique audience of your zine. In other words, the researchers’ audience might not reach the niche of your fandom’s zine space. If you’re already running a Twitter account that produces content for a fandom, then you already have some information when that fandom’s followers are most active. Through experimentation, you can see when the subset of that fandom interested in zines is most engaged with you and your project.
Timing depends 100000% on your audience.
If you want to try applying more brains, you might be able to further divide this into targeting potential contributors, buyers, and/or supporters which share your content because they like it.
Approach B: Give them what they want (Bottom-up approach)
Why bother trying to figure out a long term strategy when your zine project is a short term, one-off project? Social media sites want people to stay on them. They want content for free. Then the answer is to just give it content.
Twitter likes emotional information that can be shared in small bites.
Tumblr users are looking for just a little more, something that users might look at and want on their own blogs.
Instagram is aggressive and the way it takes scheduling to an extreme reflects this.
(THIS ABOVE LIST IS FOR EXAMPLE PURPOSES ONLY. Chances are it might not apply to your project and your audience, make your own list!)
Ask yourself if you're aiming for more people showing interest (= Likes, Follows), more people boosting or sharing (= Reblogs/Retweets/Shares), or more engagement (= Replies)?
Algorithms might be designed by people who want them to do something, but the way they ultimately make a decision is based on the data they ingested. Data implies a large trove of existing information: posts made by you and by other people. Since they’re based on existing posts, they’ll look for consistency in new posts. If you have a post that’s done well, keep posting similar posts in a similar pattern (similar type of content, similar times of day, similar days of the week)—don’t change the way you post without “easing” into it—and help the algorithms assume your hot new content is just as interesting and relevant.
Since data acts on what is already there, you might need a lot of posts to pull this off depending on the platform and followers/engagement.
At the risk of sounding ominous... Remember that when you try to learn the algorithm, it’s also learning you.