Today, many major websites personalize the content that they show to users. Examples include: Google Search, which personalizes search results to try and surface more relevant content; Amazon and Netflix, which personalize product and movie recommendations; and Facebook, which personalizes each user’s news-feed to highlight engaging content. The proliferation of personalization on the Web is driven by the explosion of Big Data that is available about people’s online and offline behavior.
Although there are cases where personalization is beneficial to users, scientists and regulators have become increasingly concerned that personalization may also harm Web users. For example, sociologists and political scientists are concerned that online Filter Bubbles may create “echo chambers” that increase political polarization. Similarly, personalization on e-commerce sites can be used to implement price discrimination.
Given the enormous number of people who rely on the Web, it is imperative that we understand how personalization algorithms are being deployed, and the effect that they have on Web users. Below, you will find links to specific research projects that our group has undertaken to address these issues.
The explosion of digital video has created an unprecedented level of choice for viewers. Netflix VP of Product Innovation Todd Yellin and his team devised a system to cut through the clutter and match viewers with the stories they’ll love.