  Websites with hyper-partisan, left or right-leaning focus offer content that
is typically biased towards the expectations of their target audience. Such
content often polarizes users, who are repeatedly primed to specific (extreme)
content, usually reflecting hard party lines on political and socio-economic
topics. Though this polarization has been extensively studied with respect to
content, it is still unknown how it associates with the online tracking
experienced by browsing users, especially when they exhibit certain demographic
characteristics. For example, it is unclear how such websites enable the
ad-ecosystem to track users based on their gender or age. In this paper, we
take a first step to shed light and measure such potential differences in
tracking imposed on users when visiting specific party-line's websites. For
this, we design and deploy a methodology to systematically probe such websites
and measure differences in user tracking. This methodology allows us to create
user personas with specific attributes like gender and age and automate their
browsing behavior in a consistent and repeatable manner. Thus, we
systematically study how personas are being tracked by these websites and their
third parties, especially if they exhibit particular demographic properties.
Overall, we test 9 personas on 556 hyper-partisan websites and find that
right-leaning websites tend to track users more intensely than left-leaning,
depending on user demographics, using both cookies and cookie synchronization
methods and leading to more costly delivered ads.
