YouTube sharpens how it recommends videos despite fears of isolating users
By Paresh Dave
SAN FRANCISCO (Reuters) - Google's YouTube has updated its recommendation feature to spotlight videos users are likely to find the most gratifying, brushing aside concerns that such an approach can trap people in bubbles of misinformation and like-minded opinions.
The new feature, which arrived in January but has not previously been reported, uses a measure of satisfaction derived from a massive and ongoing user survey to predict and promote videos that people would rank as among the best they have watched recently.
The goal is to prevent the negative sentiments that can arise when people watch hours and hours of uninspired programs, said Jim McFadden and Cristos Goodrow, who work on recommendation technology at YouTube, which is part of Alphabet Inc.
But the change comes at a time when YouTube and other social media firms are facing heavy criticism from advertisers, regulators and advocacy groups for failing to police content and account for the way their services shape public opinion.
Russian agents exploited the recommendation systems of Facebook Inc, Twitter Inc and YouTube to popularize propaganda and fake news during the 2016 U.S. presidential election.[nL1N1NG03B] The companies responded with increased user verification and fact-checking tools, but their recommendations remain focused on winning the attention and boosting the enjoyment of users.
"The risk is not that we are just siloing ourselves, but we're able to also reinforce pre-existing, flawed viewpoints," said Jacob Groshek, a Boston University associate professor who researches the influence of social media and "filter bubbles."
YouTube automatically recommends videos through a machine learning algorithm that analyzes the characteristics of videos and the behavior of its 1.5 billion users to generate personalized viewing recommendations.
These recommendations, which appear on YouTube's homepage and alongside clips, have become a centerpiece of the service, encouraging people to watch videos that are similar to ones they have spent significant time viewing in the past. Recommendations now drive 70 percent of overall "watch time" on YouTube, compared with 40 percent in early 2014, the company said.
The more time people spend watching, the more ad slots YouTube can sell. Sales of YouTube commercials are among Google's top growth areas.
But by last year, YouTube's prediction tool had matured, said McFadden, a software engineer at YouTube since 2011. He said the idea of pinpointing "satisfaction" came after he had watched "particularly good" videos, including a commencement speech by the late author David Foster Wallace.