If you thought you were going to be among the first to tweet out this post, save the effort: A bot probably beat you to it.

This unflattering-to-humans assessment comes from a new study by the Pew Research Center that found 66% of tweeted links to popular news stories came from what appear to be automated accounts.

In some categories, bot banter constitutes even more of the Twitter (TWTR) chatter: Pew’s “Bots in the Twittersphere” study found that 76% of links to sports content and 90% of links to pornography came from accounts judged to be automated. Those figures far exceed other estimates of the bots on Twitter — estimates that have already subjected the San Francisco firm to criticism.

How to spot a bot

The Pew Research Center — funded mostly by the Pew Charitable Trusts, a Philadelphia foundation — opted to gauge the role of bots not just by counting accounts, but also by tracking links.

Researchers Stefan Wojcik, Solomon Messing, Aaron Smith, Lee Rainie, and Paul Hitlin began by assembling a list of 2,315 popular sites and the 1,156,837 English-language tweets from 140,545 accounts that linked to those sites between July 27 and Sept. 11 last year.

They then turned to a third-party tool, Botometer, to pick out the bots. This service, developed by two groups of Indiana University researchers, analyzes a Twitter account’s tweets and other activity to compute the probability of it being automated or human.

An appendix to the Pew study explains that the authors settled on a 0.43 threshold — that is, a 43% Botometer score — after checking the tool’s assessments against human inspection of a sample group of accounts.

That may be the study’s weakest link. Botometer gave my @robpegoraro Twitter account — which I promise you is 100% written by me — a 37% score. Botometer’s own FAQ warns that a score between 40 and 60% suggests “our classifier is uncertain about the classification.”

Good and bad bots

But that’s the basic problem with bots on Twitter: Depending on how they’re coded and controlled, they can provide a convincing impersonation of a human brain’s output, but almost none of them identify themselves accordingly. The Pew report notes that only 636 accounts of 140,545 studied had a bio disclosing the lack of a human behind a keyboard.

That doesn’t make bots evil. They can provide a valuable service by automating certain chores — for instance, @TrumpsAlert tracks the likes, follows and unfollows of President Donald Trump and his family members. They can call out human foibles at all hours; for a few happy years, @StealthMountain did nothing but correct tweets that spelled “sneak peek” as “sneak peak.”