Two-Thirds of Tweeted Links are Posted by Bots, and Other Not Terribly Useful info
If you ever wondered just how many links you see on Twitter were shared by a person, the answer is: not too damn many.
We still don’t know what impact they have, though.
From Pew Research Center:
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 links 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.
As interesting as this may be, it is not terribly useful.
All this really told us is that the share count shown on popular websites is grossly inflated by bots. This report did not tell us anything about the impact of all that extra sharing.
Pew was wrong to say that this report shows "the pervasive role that automated accounts play"; while Pew did collect data about the bots, they did not collect anything that could explain the bots' _role_.
Did those bots have lots of followers, or hardly any? If they have no followers this doesn’t matter a bit, and if they have a lot of followers then it might mean the bots have value.
Rather than count the volume of shared links, a better question would be to ask how many people actually saw the typical bot-generated tweets. That would tell us if this was meaningless share count inflation, or if the bots were actually driving the conversation.
That would be interesting, but even then it might not tell us what you would expect.
I live on Twitter, and I have connections with software engineers that make Twitter and other bots. Those bots are far more common than you might realize, and the vast majority are both benign and useful (or at least amusing).
I know at least 6 different bots tweeting links to my site. Some of those bots have a lot of followers and get a lot of RTs because they are useful to the bot’s followers. If the bot is benign and valued by its followers, I really don’t have a problem with it.
As for those that are not, until you filter out the benign bots, there’s no way to grasp the scale of the impact of malignant bots.
And that is the question worth investigating.