Leveraging online advertising platforms to measure and characterize digital inequalities
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As the Internet is becoming a fundamental aspect of the society serving as a de facto platform for social and business activities, traditional offline activities and services have remarkably migrated to the web. The presence and interaction of users on these platforms has created a large amount of digital trace which is being effectively exploited by businesses targeting users on these platforms. One of the main players in this regard is online advertising which is the underneath business that drives the majority of the most important online services such as social media, search engines, map services, etc. This has made online advertising a crucial Internet service in its own right. While the benefit of using these digital resources has been accepted widely pushing governments and organizations to improve their Internet coverage, there are major challenges that limit the society from enjoying their benefits. Together with transparency and privacy, digital inequality is the main challenge that the society faces today. In this thesis we propose a set of inexpensive and large scale methodologies that leverages datasets from online advertising systems to measure and characterize digital inequality on the web. Our methodologies consider various demographic, geographic and interest categories at global scale that advances the knowledge of the scientific community to better understand the challenges in the interplay between online services and users, specifically digital inequalities.