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Bots in the Twittersphere

An estimated two-thirds of tweeted links to popular websites are posted by automated accounts – not human beings

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The role of so-called social media “bots” – automated accounts capable of posting content or interacting with other users with no direct human involvement – has been the subject of much scrutiny and attention in recent years. These accounts can play a valuable part in the social media ecosystem by answering questions about a variety of topics in real time or providing automated updates about news stories or events. At the same time, they can also be used to attempt to alter perceptions of political discourse on social media, spread misinformation, or manipulate online rating and review systems. As social media has attained an increasingly prominent position in the overall news and information environment, bots have been swept up in the broader debate over Americans’ changing news habits, the tenor of online discourse and the prevalence of “fake news” online.

In the context of these ongoing arguments over the role and nature of bots, Pew Research Center set out to better understand how many of the links being shared on Twitter – most of which refer to a site outside the platform itself – are being promoted by bots rather than humans. To do this, the Center used a list of 2,315 of the most popular websites1 and examined the roughly 1.2 million tweets (sent by English language users) that included links to those sites during a roughly six-week period in summer 2017. The results illustrate the pervasive role that automated accounts play in disseminating links to a wide range of prominent websites on Twitter.

Among the key findings of this research:

  • Of all tweeted links2 3 to popular websites, 66% are shared by accounts with characteristics common among automated “bots,” rather than human users.
  • Among popular news and current event websites, 66% of tweeted links are made by suspected bots – identical to the overall average. The share of bot-created tweeted links is even higher among certain kinds of news sites. For example, an estimated 89% of tweeted links to popular aggregation sites that compile stories from around the web are posted by bots.
  • A relatively small number of highly active bots are responsible for a significant share of links to prominent news and media sites. This analysis finds that the 500 most-active suspected bot accounts are responsible for 22% of the tweeted links to popular news and current events sites over the period in which this study was conducted. By comparison, the 500 most-active human users are responsible for a much smaller share (an estimated 6%) of tweeted links to these outlets.
  • The study does not find evidence that automated accounts currently have a liberal or conservative “political bias” in their overall link-sharing behavior. This emerges from an analysis of the subset of news sites that contain politically oriented material. Suspected bots share roughly 41% of links to political sites shared primarily by conservatives and 44% of links to political sites shared primarily by liberals – a difference that is not statistically significant. By contrast, suspected bots share 57% to 66% of links from news and current events sites shared primarily by an ideologically mixed or centrist human audience.

These findings are based on an analysis of a random sample of about 1.2 million tweets from English language users containing links to popular websites over the time period of July 27 to Sept. 11, 2017.4 To construct the list of popular sites used in this analysis, the Center identified nearly 3,000 of the most-shared websites during the first 18 days of the study period and coded them based on a variety of characteristics.5 After removing links that were dead, duplicated or directed to sites without sufficient information to classify their content, researchers arrived at a list of 2,315 websites.

The Center’s analysis finds that suspected autonomous accounts post a higher proportion of links to sites that are primarily shared by human users who score near the center of the ideological spectrum, rather than those shared more often by either a more liberal or a more conservative audience. Automated accounts share roughly 57% to 66% of the links to political sites that are shared by an ideologically mixed or centrist human audience, according to the analysis. By contrast, automated accounts are estimated to share roughly 41% of links to political sites with audiences comprised primarily of conservatives, and 44% of those comprised primarily of conservatives. Sharing rates among sites with liberal audiences are not significantly different from those with conservative audiences. However, differences in sharing rates for sites with centrist audiences compared with those at either end of the spectrum are substantially beyond the margins of error.
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