Leveraging online advertising platforms to measure and characterize digital inegualities

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dc.contributor.advisor Cuevas Rumín, Rubén
dc.contributor.author Kassa, Yonas Mitike
dc.date.accessioned 2020-10-02T09:55:51Z
dc.date.available 2020-10-02T09:55:51Z
dc.date.issued 2019-12
dc.date.submitted 2020-02-14
dc.identifier.uri http://hdl.handle.net/10016/31025
dc.description.abstract 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. In particular we present three main contributions in this context: (I) A methodology to measure the price variability assigned to users by the online advertising system. We created an advertising price comparison system that leverages the bidding data from four online advertising platforms that contributes to the transparency efforts to understand the economic value that online advertising system assigns to user profiles. Using this data we show that advertising price assigned to user profiles varies depending on the profile of the targeted user. (II) A methodology to leverage social media data for gender based digital inequality research. Efforts to understand global prevalence of gender based digital inequality and its interplay with socioeconomic inequalities are limited by lack of large scale representative dataset. Towards solving this problem we developed inexpensive methodologies using the Facebook online advertising platform to quantify the extent of digital inequality in access to social media and its relation with existing inequality indicators. (III) A methodology to measure and characterize user representation and growth variability on Facebook. Facebook is the most widely used social media platform connecting billions of people globally. However, little is known about composition and growth dynamic of this advertising driven social media giant. The main challenge in measuring these phenomena is due to lack of large scale representative dataset that describe the actual number of users and their activities on the social media. We address this problem by leveraging its online advertising platform to measure and characterize its global composition and growth based on age, gender, and country of location. In summary, the work presented in this thesis contributes to advance our knowledge of digital inequalities measured through social media and to develop methodologies for understanding important socioeconomic issues based on digital traces from social media and the Internet in general. It will motivate further research in the area to understand the extent and causes of digital inequalities in various aspects of the Internet considering different groups of societies. The reported findings and methodologies will also help lay foundation for informed policy development and research to close the gender gap and reduce digital inequalities worldwide.
dc.description.sponsorship This work has been supported by IMDEA Networks Institute
dc.language.iso eng
dc.relation.haspart https://doi.org/10.1109/ACCESS.2018.2885458
dc.relation.haspart https://doi.org/10.1073/pnas.1717781115
dc.relation.haspart https://doi.org/10.1109/ARES.2016.89
dc.relation.haspart https://doi.org/10.1109/ARES.2016.55
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Characterizing digital inequality
dc.subject.other Digital gender inequality
dc.subject.other Social network services
dc.subject.other Technology social factors
dc.subject.other Facebook
dc.title Leveraging online advertising platforms to measure and characterize digital inegualities
dc.type doctoralThesis
dc.subject.eciencia Telecomunicaciones
dc.rights.accessRights openAccess
dc.description.degree Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de Madrid
dc.description.responsability Presidente: Arturo Azcorra Saloña.- Secretario: Carlos Castillo Ocaranza.- Vocal: Gareth Tyson
dc.contributor.departamento Universidad Carlos III de Madrid. Departamento de Ingeniería Telemática
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