## Better Popularity Metrics For Twitter

Imagine two Twitter accounts. One has 100 followers, the other 200. Which account is more popular? And yes, this is a trick question.

At first it might seem like the answer is braindead-simple – users with lots followers are obviously more popular (on Twitter) than those who have just a small bunch of people looking at their updates. Indeed, this is the approach taken by the recently established Twitter directory WeFollow – users and tags are sorted by the number of followers, and so far it seems to work out okay. However, as you can probably guess, I’m about to say that this simplistic approach is wrong and suggest a more “advanced” way to measure Twitter popularity 🙂

When we determine popularity based on the follower count we treat each follower as a single vote, and in good democratic fashion we consider all votes equal. But the voting analogy doesn’t really hold. The real value that’s being passed around in the Twitter-verse isn’t votes – it’s attention. If you follow someone then you’re going to devote a portion of your time and attention to read their updates. And attention is a scarce resource. The more users you follow the less of your attention each of their updates will get.

We need to take this into account when counting the “votes”. Fortunately, somebody has already worked out the math for us :

Agalmos was first conceived for the Twitter platform, where people can “follow” other people’s updates, and the number of users one is following is assumed to be inversely proportional to the attention each feed is receiving. Then we use information entropy. Look up Wikipedia.

Source : “Agalmos – an information measure for agalmic economics” (Edit: Source page is down.)

I’ve written a little script that calculates the “attention value” of a Twitter account using this function. Due to API limitations it only analyzes the first 50 followers and then uses the average value to estimate the total, but I think it works well enough as a proof-of-concept. You can try it out yourself here.

To put the numbers it reports in perspective, here’s what the script says about my two accounts :

• 86 followers – mostly normal users
• 5.93 follower value

antiprivacy

• 193 followers – mostly spammers and people with auto-follow scripts
• 7.47 follower value

It’s not perfect, but judging from this singular, anecdotal example, I think it’s clear that an attention-based metric works better than directly comparing the number of followers 🙂

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### 4 Responses to “Better Popularity Metrics For Twitter”

1. Great article. Check out http://www.TweetTop.com for who to follow on twitter in many different categories. Similar to wefollow but a mix of UGC and editorial controlled (as opposed to wefollow which lets users self classify).

I’d like to incorporate some of your thoughts into tweettop.com for a better ranking algorithm. This could, theoretically remove our need for manual editorial control.

J