Large-Scale Analysis of User Exposure to Online Advertising on Facebook

Abstract

Online advertising is the major source of income for a large portion of the Internet Services. There exists a body of literature aiming at optimizing ads engagement, understanding the privacy and ethical implications of online advertising, and so on. However, to the best of our knowledge, no previous work analyzes, at large scale, the exposure of real users to online advertising. This paper performs a comprehensive analysis of the exposure of users to ads and advertisers using a dataset, including more than 7M ads from 140k unique advertisers delivered to more than 5k users, which was collected between October 2016 and May 2018. This paper focuses on Facebook, which is the second largest advertising platform next only to Google in terms of revenue and accounts for more than 2.2B monthly active users. Our analysis reveals that the Facebook users are exposed (in median) to 70 ads per week, which comes from 12 advertisers. Ads represent between 10% and 15% of all the information received in the users' newsfeed. A small increment of 1% in the portion of ads in the newsfeed could roughly represent a revenue increase of 8.17M USD per week for Facebook. Finally, we also reveal that the Facebook users are overprofiled since, in the best case, only 23% of the active interests, Facebook assigns to users for the advertising purpose, are actually related to the ads these users receive.

Keywords

• Facebook
• online advertising
• transparency
• user-centric analysis
• human-computer interaction