Most popular website links are published on Twitter via automated accounts

New data from the Pew Research Center suggests that Bots chat robots are responsible for most of the links associated with popular Web sites published on the Twitter microblogging platform. According to new data published by the research center, about 66 percent of Twitter links On popular websites through automatic accounts instead of actual people.

To analyze this phenomenon, Pew researchers compiled a list of 2,315 Web sites from the most popular sites on the Internet and then analyzed a random sample of 1.2 million English users who included links to these sites over a six-week period from July 27 to September 11 in 2017.

The researchers wrote in their analysis “results show the pervasive role played by the mechanism of accounts in publishing links to a large group of prominent sites on Twitter, and among the famous news sites and current events sites are created 66 percent of links Twitter by tracking the suspect programs, a matching rate Total”.

Certain types of sites, including pornographic sites, sports sites, and news aggregators that gather stories from across the web, have the largest share of Twitter links published by chat blog robots. The study found that 89 percent of Twitter links to aggregation sites Popular News Posted by Automated Accounts.

The study also found that “a relatively small number of highly active script chat robots” were responsible for a large portion of the links to Twitter news and media sites during the period, with the most active 500 accounts posting 22 percent of those links, More than 500 of the most active Twitter users publish only 6 percent of links to news outlets.

“The study found no evidence that the automated accounts currently have a liberal or conservative political bias in their overall behavior. Suspicious robots have published nearly 41 percent of links to conservative political sites, and nearly 44 percent of links To political sites calculated by liberals, a difference that is not statistically significant. “