How users break Twitter’s following rules and get away with it

I’m going to show you how to identify users who may be breaking Twitter’s Terms of Service (TOS), but also show you why it’s hard to know for sure—and how newer, more sophisticated follow-unfollow software makes it impossible to tell.

What I’m going to be covering are uses of Twitter that will get your account suspended. For legitimate ways to gain followers quickly (such as contests and advertising), read this. One of the things that can help a lot is just knowing the best times to tweet, or learning what makes a tweet get the best response.

Why am I doing this?

Many people misinterpret available information. Some users are clearly using sophisticated software to (likely) hide how they are violating the TOS, others are clearly not. Inexperienced users often make the wrong assumptions about how experienced users are using Twitter. After reading this, you should have a much better idea of who is hiding something, who is barely getting away with something, and who has failed to get away with violating the TOS .

But, as I will point out repeatedly, there can be many, many different reasons for how someone follows and unfollows others on Twitter. Jumping to conclusions without doing some research first is always a bad idea!

How Twitter stops follow “churn”

Twitter says that if you follow a lot of users hoping to be followed back, wait a few days and then unfollow the ones that don’t follow you back, you can be suspended. It’s a practice that is against Twitter’s Terms of Service (TOS) called “follow churn” and they spell out that aggressive follow churn” is cause for suspension. Also, any kind of automated unfollowing is not allowed (which features of some popular apps violate).

Twitter helps make this hard to do by preventing users from following more than 10% that follow them, once a user follows 2,000 or more. So if 2,000 follow you, you can follow up to 2,200; if 10,000 follow you, you can follow up to 11,000, and so forth. This prevents anyone from simply following huge numbers of people just because they know a few will automatically follow them back. Twitter also limits all accounts to following no more than 1,000 per day, and commonly limits this further in individual cases. Of course, there is no one right number of people to follow. If you want to engage with people heavily, you may naturally follow fewer, and if you are primarily seeking links to information, you will likely follow more.

For more information, see

  1. The Twitter Rules
  2. Automation Rules and Best Practices
  3. Following Rules and Best Practice

How do people get caught?

What you may NOT know, is that thanks to more advanced software, it can be virtually impossible to catch users that are doing this. However, most still use less advanced software, and so you can often see a pattern in their following that still shows some “churning.”

The most popular software apps that automate following and unfollowing have for a long time done it by alternating following people and then unfollowing people. It creates a pattern you can see at of several days of following more and more, followed by a shorter period of unfollowing. If you do this too frequently, such as repeatedly week after week, Twitter will suspend your account. All of the charts here are what TwitterCounter calls the “following” charts, meaning they show the total for each day that a user is following.

Finding churners by their charts—the old way

For a long time, users would get in touch with me and ask why their accounts had been suspended. I would put them in touch with Twitter and give them the “contest account suspension” information, but I would also check their following pattern. 95% of the time it was a classic TwitterCounter “churn” following pattern such as this:

Each time the churner is finished unfollowing the users that didn’t follow them back (points A and B) the total number of people they have followed is greater (B is higher than A). That’s because they are trying to only follow users that follow them back, and get ever higher numbers. So if they are successful, the chart will keep rising in this zig-zag pattern.

The particular pattern shown is slightly more modern, since there are several weeks between unfollowing periods. Earlier users who churned would repeat this pattern every week or so (point A and B would be only a few days apart), allowing them to gain followers faster, and leading more quickly to having their accounts suspended. It was necessary for users that hadn’t built up a larger following to churn more regularly, since if they followed other users for too long, they would break their 10% ratio and wouldn’t be allowed to follow any more.

Another classic chart is following for 1-2 days at once, waiting a few days to identify who doesn’t follow you back, then unfollowing then for 1-2 days. This is less sophisticated, and may look like this:

Some users do this to test different lists, to see which ones have the greatest percentage of users that will follow back quickly. If the user in the chart above was doing this, they didn’t find lists where many would follow them back, as there were only small gains from the jump up to the jump back down in most cases.

There are a lot of possible variations, but all have some kind of regular up-and-down with an overall rise:

Interpreting follow charts

TwitterCounter is the most popular place to see users follow patterns. Here for example is the 6-month follow chart of @JustinBieber. One thing to realize is that TwitterCounter doesn’t always record each day properly, sometimes due to technical issues, and sometimes due to users updating their charts at odd times. So if there is generally a smooth trend, with a day here and there that goes strangely flat followed by a day that jumps sharply upwards, you should ignore the “flat followed by jump” and just assume the trend was smooth throughout. Also, some users charts are not updated regularly. You can click “Update stats now” at the top of a TwitterCounter user page to see the latest stats.

Also, there are a variety of explanations for why a chart goes up or down. For example, you can’t tell if someone is unfollowing

  1. inactive accounts,
  2. spammers,
  3. active users that didn’t follow them back,
  4. People with the letter “e” in their name,
  5. etc.

This point is, by looking at follow charts, you don’t know for certain who was being unfollowed or why. But certain patterns happen so often, they are a pretty reliable indicator. Another reliable indicator if a person with username @user unfollows hundreds or more, you can search for “@user unfollowed me” at If there are a few of these, you can be pretty sure that @user is unfollowing active users, a few of which are using a service that announces their unfollows. If @user does a lot of unfollowing and there are zero tweets of complaint, they are likely only unfollowing inactive users.

Chart showing a user was suspended

You can often see this from either their following or followers chart. A period of growth, followed by a long period of steady decline. After being caught, the user was afraid to do any following for awhile, and either eventually bought more advanced software, quit playing the churn game, or began again more conservatively. This is hard to tell from a chart though, because the same thing can happen if people just become inactive on Twitter for awhile. You have to compare their frequently of tweeting. If they keep tweeting steadily, but their following charts looks like this, it’s quite possible they were suspended:

This is most likely to be a user who was suspended if their number of followers showed a steady gain in followers during the up-down periods, and a steady decline afterwards, and they tweeted steadily the whole time.

Some users have even bragged that they have been suspended and unsuspended multiple times, saying that “they have learned to push the envelope” on what Twitter allows. Of course, what they really mean is they’ve learned how to get worthless followers and ruin a Twitter account faster than anyone else!

Hiding churn partially…and completely

As users were suspended, unsuspended and experimented, some being suspended more than once (Twitter is less forgiving now), people began to try different methods for hiding their churn. Here’s one example of a following chart that is likely just trying to smooth and spread out churn:

There is the same up-and-down, but this time it is neither a zig-zag or up-and-down jumps, but a smooth line rising and then falling over several weeks’ time. The longer users take before unfollowing, the less Twitter considers it “churn.” This forces users using automated follow-unfollow software to grow their accounts slower. One reason popular users will do this is simply to avoid questions of “Why did you unfollow a bunch of people in one day?”

What is really happening here isn’t clear, of course. But it’s likely that this user is using some kind of app to identify who didn’t follow them back and then unfollow them, purely for the purpose of gaining more followers—churn—probably mixed in with some more natural following (people they chat with) and unfollowing (people that annoy them). Twitter allows any kind of pattern as long as it is not “aggressive” So, what is considered “aggressive?” Only Twitter knows, and they can change the definition at any time. But from looking at changes in user behavior, it seems that zig-zagging up and down more frequently than once every three weeks or so is now considered “aggressive.”

So over the years, users learned ways to work around Twitter’s rules, by following for longer periods before unfollowing. This made for less “churn.” Some also tested a reverse pattern, following a bunch all at once, then unfollowing slowly. But some time back advanced software began being sold, previously only used by people who paid programmers to create custom software for them.

How sophisticated users completely hide from Twitter rules

Here is the following chart of a well-known user who has stated publicly that they use auto-follow-back to follow anyone that follows them. The chart not shown here, showing gains in people following them, has had a very steady increase over the past year. Many months ago, this chart (of how many they follow) was steadily rising, followed by periodic drops (churn). Then one day, and for months since, it has looked like this:

How about that—a steady decline, all the while their number of followers continues to grow steadily unchanged. The most likely scenario here is that they are doing the same things they were before, but using software to avoid showing any ups or downs publicly.

Because of this user’s previous history and statement that they use auto-follow-back software, they are probably still following around 80 per day, but they are also unfollowing around 86 per day. The net results is -6, and a steady decline. This way they don’t get any complaints about how “they are unfollowing lots of people” or that they are “churning” due to having a chart that shows ups and downs. Newer software can keep detailed lists of users and gradually unfollow them here and there while still following new people, and adjust for autofollowing by unfollowing more or less depending on many people were followed that day.

So this user simply picked his strategies for how he wanted to follow and unfollow, and had the advanced software implement it so that it looks steady each day. Of course, there could be several alternate explanations for this. It could be that they stopped using auto-follow-back, stopped following anyone for any other reason, and just unfollowed a few people every day. But considering their history, and the fact that their follower growth line did NOT change, it’s likely they are doing exactly what they did before, but using software that allows them to mask it by mixing in a variety of kinds of follows and unfollows (likely in a pattern timed to appear “human-like”).

Also, much of the older software relied on the old Twitter interface to work. To try and look “human-like” it would open a hidden browser and use the web interface to do it’s following and unfollowing. Had it used an API connection, it would have been easier for Twitter to identify it violating Twitter automation rules. But the new Twitter interface is much less machine friendly, and so some of the old Twitter automation software will stop working once the old Twitter interface is permanently replaced by the new Twitter interface. So more sophisticated software is being bought by users who rely heavily on Twitter automation.

Unfollowing inactive users

Many Twitter accounts unfollow inactive users—users who haven’t tweeted for several months from time to time. Over the years, this can add up to a lot of accounts! I didn’t check for a very long time, and then used ManageFlitter to check one day, and I found there were around 80,000 accounts following @TweetSmarter that were inactive (hadn’t tweeted in over 30 days).

Here’s an example of a user for which there were no tweeted complaints that “@user is unfollowing me” but who apparently unfollowed over 30,000 users (each horizontal gray bar is 10,000 users). Unfollowing that many users with zero complaints showing up in search means they are virtually certain to only be unfollowing inactive users:

This user appears to have manually or semi-manually used some method for unfollowing inactive users, such as (approved by Twitter). If the unfollowing were fully automated, there would be no reason for having so many different drops. It could simply be a steady decline, or with more sophisticated software, they could have spread it out and showed a slight curve down and then back up. In this case, it’s simply likely they unfollowed inactive accounts whenever they had free time over a few weeks.

Clearly this is also a user that does either or both auto-follow-back or find and follow several dozen users each day, as evidenced by the long steady upward line. (For more information on how @TweetSmarter follows other users, click here.)

Conditions that skew interpretations

Because people unfollow you, even if you ONLY follow people after they follow you, it can look like “churn” in your chart. Here’s why:

Imagine that someone has turned auto-follow-back on using a service like SocialOomph, but they have also gotten a reputation for following back. This mean that, over time, more users will seek them out in order to get them to follow back, and then unfollow them. So, as users unfollow them more and more, as long as they leave auto-follow-back on, each day they will follow more people than seem to follow them back, because other people are using them to gain their follow back.

So, as more and more users realize this account can be gamed in this way, there will be an ever greater disparity between how much their “follow” number rises each day, compared to how many follow them.

The funny thing is, each day they only follow people that follow them first! If no one unfollowed them, the number of people they follow and the number that follow them would go up exactly equally.

But because many of those users unfollow later, it looks like they are following many people, and only a few are following them back. In other words, using nothing but auto-follow-back can make it look like you are churning! This is because eventually you will have to unfollow the people that unfollowed you, or Twitter will block you from following anyone else when your ratio goes beyond 10%.

So by auto-following users that follow you first, you can appear to be doing churning, when the reality is that you are the one being churned by users that later unfollow you. Any account that follows more people each day than follow back could be intentionally following people that don’t follow them, and not having them all follow back, OR they could have simply left auto-follow-back turned on and are simply getting a lot of unfollows of people abusing them in order to gain a follow.

Problems with some large accounts

However, as popular user @ChrisBrogan has pointed out, for large accounts it can seem easier to leave auto-follow-back on so you automatically follow all the people you engage with each day, and then over time unfollow the spam users that creep in. Nonetheless, using auto-follow-back is fraught with problems no matter how you use Twitter, because it gives you a reputation that causes more and more low quality accounts to follow you over time.

Bigger accounts also get many people each day writing “Hey, please follow me back” and this clutters up their mentions inbox, making it more work to find the tweets from people you want to see. I got so annoyed with all the “Hey, follow me back” tweets that I once turned on auto-follow-back using SocialOomph just so I could get rid of them!

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