Abstract
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 sites tend to track users more intensely than left-leaning, always depended on user demographics, and using both cookies and cookie synchronization methods, leading to more costly delivered ads.
Publication
Proceedings of the The Web Conference (WWW 2020)
PhD Student working with the UK Parliament on Digital Citizen Engagement
I am a PhD Scholar in Computer Science at King’s College London under the supervision of Dr. Nishanth Sastry. My doctoral work focuses on online digital citizen engagement with the UK Parliament. I completed my Bachelor of Engineering (Computer Science and Engineering) from The LNM Institute of Information Technology, India. My professional experiences include an internship at Telefonica I+D (Barcelona, Spain) and with the Neilsen Group. My honours include a “Best research impact” award at the PhD poster competition of King’s College London, NMS and Chairman’s Gold Medal for best all-round performance in graduating class of 2017 (BTech. CSE).
Former PhD student (now Research Scientist at Bell Labs Cambridge)
I am a Research Scientist at Nokia Bell labs, Cambridge UK, working with the social dynamics team. I am mainly interested in projects that deal with quantification of human processes from web scale data using methods from complex networks, machine learning and computer vision. I was a King’s India scholar at King’s College London, where I worked on my Ph.D. in computer science at the Department of Informatics, under the guidance of Dr. Nishanth Sastry. I have graduated with a Masters of Science (M.S.) degree from University of California at Santa Barbara - USA, majoring in signals processing and networks, and a Bachelors of Engineering (B.Eng) from University of Pune - India, majoring in Electronics engineering .