New research shows that understanding users' intentions—rather than simply increasing data volume—can improve the suggestions generated by YouTube's "black box" algorithms.

Algorithmic recommendation systems on social media sites like YouTube, Facebook and Twitter have shouldered much of the blame for the spread of misinformation, propaganda, hate speech, conspiracy ...

The Annals of the American Academy of Political and Social Science, Vol. 659, Toward Computational Social Science: Big Data in Digital Environments (May 2015), pp. 290-306 (17 pages) Theoretical and ...

When opening a short video information app and swiping across the screen, users expect to find content that is 'just what they want to see' — but the reality is often different: during commutes, users ...

Switch on your streaming service of choice or open the website for your preferred department store and a recommendation system is sure to kick in. “You liked this TV series, so we think you’ll like ...

Back in June, Netflix’s VP of Product Innovation Carlos A. Gomez-Uribe and Chief Product Officer Neil Hunt co-published a paper entitled, “The Netflix Recommender System: Algorithms, Business Value, ...

New Delhi, April 1 (IANS) Twitter has finally made most of its recommendation algorithm open source which is now available for independent third parties and users. According to Twitter CEO Elon Musk, ...