If somebody thought that they were going to be among the first to tweet out this post, they should save the effort: A bot probably beat them to it.
This unflattering-to-humans assessment comes from a new study by the Pew Research Center that found 66 percent 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 percent of links to sports content and 90 percent 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.
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.
This unflattering-to-humans assessment comes from a new study by the Pew Research Center that found 66 percent 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 percent of links to sports content and 90 percent 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.
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.
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