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Comment by TheDong | Hacker News Reader

I think it's pretty easy to argue that their definition is intentionally misleading, which may not be technically inaccurate, but is arguably just as bad.

The big story in the news last week was "Elon Musk says deal on hold while verifying twitter's 5% Monthly Active Users stat", or something to that effect.

That's the context this article was published in. It is transparently obvious they are re-using the word "active twitter accounts" to cause confusion with the definition of "active" that has been being bandied around. The post is using such a title as a clickbait, to hop aboard a trend.

I think the title, and lack of significant clarification in the article, make it clearly misleading, and I don't think pedantic "well technically active can have multiple definitions" changes the reality of the situation meaningfully.

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But their definition makes things look worse for them. The high number of lurkers would make the percentage of fake accounts smaller.

I don't understand what you mean.

Let's take both their numbers at face-value and assume they're true.

Twitter has reported: 396.5 million logged-in-this-month users, of which 5% are fake/spam (19.8 million fake users)

This article reported: Looked at 44,058 tweeted-recently accounts, of which 20% are fake (8,800 fake)

Which of those stats looks worse for them?

> The high number of lurkers would make the percentage of fake accounts smaller

Why? Twitter included lurkers in its dataset, this article didn't, why should that impact stats in the direction of fake accounts being smaller?

> Why? Twitter included lurkers in its dataset, this article didn't, why should that impact stats in the direction of fake accounts being smaller?

Because you usually don't create fake accounts to lurk, but to do "something".

I'm speculating, but even when you create bots to boost follower counts you'd probably make them post now and then so as to seem "active".

It makes sense that the proportion of tweeting accounts being bots is much higher than the proportion of lurkers. And since there are also more lurkers in turn than posters, I would say that the real number is much lower than that.

I don't buy the speculation as obviously accurate.

Let's say I own a twitter bot farm. I make 20k accounts, have a system setup that logs into each of them from a unique IP each month at random times to make sure they're not banned yet, and advertise it out. On month 1, someone buys 1000 of them as followers. On month 2, someone buys 1000 of them to tweet spam. etc etc.

Each month, there's 20k active bot accounts (logged in to verify they weren't banned). Only a small number may actually tweet though since buyers may have not gotten them yet. Bot accounts lurk too, for months on end, before ever acting.

I'm not claiming this is accurate, but I am claiming this is a reasonable alternative which doesn't align with the view of bot accounts being more prevalent in tweeting accounts than lurking accounts.

> Twitter included lurkers in its dataset

A metric they've artificially inflated by gating tweets, which works to their advantage when calculating spam. With that in mind, I think I'm more inclined to look at spam as a percentage of active tweeters and ignore lurkers.

I thought the parent was criticizing Twitter's active monthly user definition, which only includes people who have tweeted in the past 90 days. The article used this definition of active use as well.

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