Dissertation
Web Privacy Measurement in Real-Time Bidding Systems, A Graph- Based Approach to RTB system classification
On 29 January 2019, Robbert van Eijk defended his thesis 'Web Privacy Measurement in Real-Time Bidding Systems, A Graph- Based Approach to RTB system classification'. The doctoral research was supervised by Prof. dr. H.J. van den Herik.
- Author
- Robbert van Eijk
- Date
- 29 January 2019
- Links
- Leiden Repository
Web Privacy Measurement (WPM) has been established as an academic research field since 2012. WPM scholars observe websites and services to detect, characterize, and quantify privacy-impacting behaviors. The main goal of the research field is to increase transparency through measurement.
In the thesis, Robbert J. van Eijk investigates the advertisements online that seem to follow you. The technology enabling the advertisements is called Real-Time Bidding (RTB). An RTB system is defined as a network of partners enabling big data applications within the organizational field of marketing. The system aims to improve sales by real-time data-driven marketing and personalized (behavioral) advertising. The author applies network science algorithms to arrive at measuring the privacy component of RTB. In the thesis, it is shown that cluster-edge betweenness and node betweenness support us in understanding the partnerships of the ad-technology companies. From our research it transpires that the interconnection between partners in an RTB network is caused by the data flows of the companies themselves due
to their specializations in ad technology. Furthermore, the author provides that a Graph-Based Methodological Approach (GBMA) controls the situation of differences in consent implementations in European countries. The GBMA is tested on a dataset of national and regional European news websites.