Twitter is trialling a way to surface relevant tweets around real-life events and conversations. The company confirmed that it’s experimenting with a “suggested reading” module within your timeline that showcases news articles it thinks you might be interested in. No public release date has been provided.
“We’re continuing to experiment with new ways to surface the best and most relevant content for people on Twitter,” a company spokesperson told VentureBeat.
Whoa is this “suggested reading” thing new or have I just never seen it pic.twitter.com/JJvZev5N2x
— Selena Larson (@selenalarson) April 20, 2017
For more than two years, Twitter has utilized a module within timelines to show you tweets that may have been missed. It also launched a feature that recommends users you should follow. While those may include links to news items, they were largely centered around individuals. With suggested reading, the service will focus more on the content and its newsworthiness. There’s a likelihood that there may be some overlap between all of these features. So perhaps as you browse through tweets about the latest actions taken by the U.S. government, Twitter will show you what it thinks are the most important articles that best summarize it.
Twitter declined to provide more information, but it’s feasible that Twitter could targeted tweets based on your previous conversations and things that are trending right now. Will it put a spotlight on Moments over articles from the BBC, CNN, NBC News, Washington Post, The New York Times, or even VentureBeat? It’s also worth looking into the criteria or algorithm Twitter is using to select the articles, because it might run the risk of people criticizing the company over censorship or bias, something that Facebook has faced previously.
Should suggested reading be launched to the masses, this might help make the service more easily understandable for both new and current users because now they won’t have to cycle through their timeline to try and find news worth reading amid a torrent of random tweets put forth by people they’re following.