I recently ran a game theory analysis of following on Twitter, specifically focused on following with the intent of getting someone to follow in return; originally, I intended it for myself, but I think the findings are worth talking about (especially for those who try to use follows and ‘follow backs’ to build your audience on Twitter). The extended form analysis is down below:I get that this chart might be a little hard to read at first. Basically, Player 1’s choices are highlighted in light blue, and Player 2’s choices are highlighted in green. Off to the right side, you’ll see the results of their combined choices, phrased as simple equations. The V1 and V2 indicate the value of a follow from Player 1 and Player 2, respectively, and there are two equations for each result (one from Player 1’s perspective and one from Player 2’s).
To explain this a little better, let’s run through the game once. It starts when Player 2 follows player 1 (the ‘Original follow’ on the chart), and then Player 1 must decide whether to follow back or ignore this action. Let’s say they choose to follow back; Player 2 then has the option to continue following them, or to unfollow. If they choose to continue following Player 1, then they both obtain the top result (V2-V1 for Player 1, and V1-V2 for Player 2).
What this means is that Player 1 gets the value of Player 2’s follow, minus the value of their own follow (and vice versa for Player 2). These values are relative based on each player’s perspective; Player 1 might value their own follow highly and Player 2’s highly as well, whereas Player 2 might not value either.
This explains a lot of behavior when it comes to following and following back. For example, it’s well known that those who follow many others have a high rate of returning follows. Based on this analysis, that likely occurs because the more people someone is following, the less they value their own follow (perhaps because they rarely check their feed or it’s already cluttered anyway). Hence, why they follow back with more predictably.
It also explains why unfollowing someone whom you received a follow back from almost always results in a loss of that follower. The equation for that scenario is the second down on the chart (0-V1, V1), which shows that you’ve forced Player 1 into a losing situation; the only way they don’t lose the game is if V1 is zero, which is almost never true. That’s why you see some people who create throwaway accounts just to follow, and why they generally aren’t successful (since hardly anyone values what’s essentially an empty follow).
Scenario three (the ‘celebrity’ result), in which Player 1 doesn’t follow back and retains the original follow anyway, typically occurs if Player 2 followed Player 1 for some reason outside of the game (for example, they saw them on TV or heard them on the radio).
Finally, the bottom result—scenario four—is a failed game, in which neither player gains anything. This should logically be the most common result. Game theory explains it thusly: Player 1’s decision is the most operative, as Player 2’s second choice is the same regardless (continue following or unfollow). Therefore, Player 1 can look at the end result and determine their best play.
If they follow back, they’ll receive either V2-V1 or 0-V1. If they ignore, they’ll receive either V2 or 0. Therefore, the worst result of ignoring is a zero sum game (no one wins, but Player 1 can’t lose). This has to be compared to the best and worst result of following back. In order for Player 1 to choose the follow back option, V2-V1 must be greater than 0, and 0-V1 must be extremely low (preferably approaching 0).
In other words, someone you follow must value their own follow little and value yours highly, or else they won’t follow back. And yet, the more people you’re following the less value your follow seems to carry. Twitter users aren’t stupid; they can tell that someone following a hundred thousand other users isn’t likely to see their tweet.
It’s a paradox of sorts: the fastest, most reliable way to gain followers is to follow others, and yet the more you do this the less likely you are to receive follow backs. That’s why many authors seem to approach a ‘critical mass,’ where they no longer receive enough follow backs to grow at a reasonable rate (or they seek out other valueless followers, which is why they start to look like spam accounts).
I hope you found this interesting; if so, please like, share, and leave a comment.