Personalization in online services measurement, analysis, and implications

• Online Access: http://hdl.handle.net/2047/D20235425

Since the turn of the century more and more of people's information consumption has moved online. The increasing amount of online content and the competition for attention has created a need for services that structure and filter the information served to consumers. Competing companies try to keep their customers by finding the most relevant and interesting information for them. Thus, companies have started using algorithms to tailor content to each user specifically, called personalization. These algorithms learn the users' preferences from a variety of data; content providers often collect demographic information, track user behavior on their website or even on third party websites, or turn to data brokers for personal data. This behavior has created a complex ecosystem in which users are unaware of what data is collected about them and how it is used to shape the content that they are served.