Muhammad Ahmad Bashir (Northeastern University), Umar Farooq (LUMS Pakistan), Maryam Shahid (LUMS Pakistan), Muhammad Fareed Zaffar (LUMS Pakistan), Christo Wilson (Northeastern University)

Widely reported privacy issues concerning major online advertising platforms (e.g., Facebook) have heightened concerns among users about the data that is collected about them. However, while we have a comprehensive understanding who collects data on users, as well as how tracking is implemented, there is still a significant gap in our understanding: what information do advertisers actually infer about users, and is this information accurate?

In this study, we leverage Ad Preference Managers (APMs) as a lens through which to address this gap. APMs are transparency tools offered by some advertising platforms that allow users to see the interest profiles that are constructed about them. We recruited 220 participants to install an IRB approved browser extension that collected their interest profiles from four APMs (Google, Facebook, Oracle BlueKai, and Neilsen eXelate), as well as behavioral and survey data. We use this data to analyze the size and correctness of interest profiles, compare their composition across the four platforms, and investigate the origins of the data underlying these profiles.

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Fei Zuo (University of South Carolina), Xiaopeng Li (University of South Carolina), Patrick Young (Temple University), Lannan Luo (University of South Carolina), Qiang Zeng (University of South Carolina), Zhexin Zhang (University of South Carolina)

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Ruian Duan (Georgia Institute of Technology), Ashish Bijlani (Georgia Institute of Technology), Yang Ji (Georgia Institute of Technology), Omar Alrawi (Georgia Institute of Technology), Yiyuan Xiong (Peking University), Moses Ike (Georgia Institute of Technology), Brendan Saltaformaggio (Georgia Institute of Technology), Wenke Lee (Georgia Institute of Technology)

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