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Two-thirds (66%) of all tweets linking to stories on popular websites are shared by automated accounts, or bots, according to new analysis by Pew Research Center.

The research was based on an analysis of a random sample of roughly 1.2 million English-language tweets gathered over a six-week period in 2017 that promoted links from any of the 2,315 most popular websites compiled by Pew.

Here are some other notable findings:

Bots were responsible for sharing links to some types of content more than others. Bots shared 90% of all tweeted links to adult content, 76% to sports content, 73% to commercial products or services, 66% to news and current event sites, and 62% to celebrity news and culture.

Bots shared 90% of all tweeted links to adult content, 76% to sports content, 73% to commercial products or services, 66% to news and current event sites, and 62% to celebrity news and culture. Relatively few highly active bots were responsible for a much larger portion of tweeted links to news and media sites than human users. The 500 most active bot accounts produced 22% of the tweeted links to popular news and media sites, whereas the 500 most active human users produced just 6% of tweeted links to the same outlets.

The 500 most active bot accounts produced 22% of the tweeted links to popular news and media sites, whereas the 500 most active human users produced just 6% of tweeted links to the same outlets. Among news and current events websites featuring political content for an audience with a certain political lean (conservative, liberal, or centrist), neither the left nor right had significantly more bots disseminating content. Bots shared 41% of links to political sites with a conservative audience, 44% of links to political sites with a liberal audience, and 57% to 66% of links to sites with a centrist audience.

It’s notoriously difficult, even for teams within Twitter, to determine whether an account is genuine or automated. Importantly, Pew noted that there was likely some risk of error involved in its bot-versus-human classification process, wherein some human users may have been classified as bots and vice versa. Further, the analysis doesn’t evaluate whether the links were being shared by “good” or “bad” bots. It’s worth noting that not all bots are so-called “bad” bots, that is, automated accounts set up by bad actors to deliver rampant streams of manipulative or deceptive content.

Bots, whether good or bad, are a particularly systemic and deeply embedded problem on Twitter, as a recent feature in The New York Times exposed. In an effort to limit negative, fake activity on the platform, Twitter has engaged in a platform-wide crackdown on bots, which has led to massive, unannounced purges of what it determines are automated accounts. Earlier this year, in a sudden overnight purge, Twitter removed thousands of bots, which led to an outcry in the morning when some users — particularly conservatives — found their follower counts had been drastically reduced.