The use of social media platforms like Facebook, Twitter, YouTube, and TikTok is increasingly widespread, currently amounting to billions of users worldwide. Social media companies deploy proprietary recommendation algorithms to automate the selection, ranking, and presentation of content on the platform’s “feed” or recommended content section, every time a user opens or refreshes the site or app. However, social media recommendation algorithms have a range of privacy, security, information quality, and psychological concerns for users. 

A successful approach to the regulation of social media recommendation algorithms will require a combination of government regulation, self governance, and external oversight to facilitate value alignment across these diverse actors and tackle the various challenges associated with this technology. This publication explores the technical components of social media recommendation systems, as well as their public purpose considerations.