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I always feel like somebody's watching me: measuring online behavioural advertising

Authors:

Juan Miguel Carrascosa,

Vijay Erramilli,

Nikolaos LaoutarisAuthors Info & Claims

CoNEXT '15: Proceedings of the 11th ACM Conference on Emerging Networking Experiments and Technologies

Article No.: 13, Pages 1 - 13

https://doi.org/10.1145/2716281.2836098

Published: 01 December 2015 Publication History

Abstract

Online Behavioural targeted Advertising (OBA) has risen in prominence as a method to increase the effectiveness of online advertising. OBA operates by associating tags or labels to users based on their online activity and then using these labels to target them. This rise has been accompanied by privacy concerns from researchers, regulators and the press. In this paper, we present a novel methodology for measuring and understanding OBA in the online advertising market. We rely on training artificial online personas representing behavioural traits like 'cooking', 'movies', 'motor sports', etc. and build a measurement system that is automated, scalable and supports testing of multiple configurations. We observe that OBA is a frequent practice and notice that categories valued more by advertisers are more intensely targeted. In addition, we provide evidences showing that the advertising market targets sensitive topics (e.g, religion or health) despite the existence of regulation that bans such practices. We also compare the volume of OBA advertising for our personas in two different geographical locations (US and Spain) and see little geographic bias in terms of intensity of OBA targeting. Finally, we check for targeting with do-not-track (DNT) enabled and discover that DNT is not yet enforced in the web.

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Cited By

Kaushik SSharma TYu YAli AWang YZou Y(2024)Cross-Country Examination of People’s Experience with Targeted Advertising on Social MediaExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650780(1-10)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3650780
Ormeno MDao HHerskovic VFukuda K(2024)Do Cookie Banners Respect My Browsing Privacy? Measuring the Effectiveness of Cookie Rejection for Limiting Behavioral AdvertisingIEEE Access10.1109/ACCESS.2024.349453912(174539-174550)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3494539
Ormeno MDao HFukuda KTyson GVarvello M(2023)Investigating Search Engines Terms LeakageProceedings of the on CoNEXT Student Workshop 202310.1145/3630202.3630236(15-16)Online publication date: 8-Dec-2023
https://dl.acm.org/doi/10.1145/3630202.3630236
Show More Cited By

Index Terms

I always feel like somebody's watching me: measuring online behavioural advertising
1. Information systems
  1. Information systems applications
    1. Computational advertising
  2. World Wide Web
    1. Online advertising
      1. Display advertising

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Published In

cover image ACM Conferences

CoNEXT '15: Proceedings of the 11th ACM Conference on Emerging Networking Experiments and Technologies

December 2015

483 pages

ISBN:9781450334129

DOI:10.1145/2716281

General Chairs:
Felipe Huici
NEC Europe Ltd
,
Giuseppe Bianchi
University of Rome Tor Vergata

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCOMM: ACM Special Interest Group on Data Communication

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 December 2015

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Funding Sources

Ministerio de Economía y Competitividad
European Union's Horizon 2020
Regional Government of Madrid

Conference

CoNEXT '15

Sponsor:

SIGCOMM

CoNEXT '15: Conference on emerging Networking Experiments and Technologies

December 1 - 4, 2015

Heidelberg, Germany

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Overall Acceptance Rate 198 of 789 submissions, 25%

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Cited By

Kaushik SSharma TYu YAli AWang YZou Y(2024)Cross-Country Examination of People’s Experience with Targeted Advertising on Social MediaExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650780(1-10)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3650780
Ormeno MDao HHerskovic VFukuda K(2024)Do Cookie Banners Respect My Browsing Privacy? Measuring the Effectiveness of Cookie Rejection for Limiting Behavioral AdvertisingIEEE Access10.1109/ACCESS.2024.349453912(174539-174550)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3494539
Ormeno MDao HFukuda KTyson GVarvello M(2023)Investigating Search Engines Terms LeakageProceedings of the on CoNEXT Student Workshop 202310.1145/3630202.3630236(15-16)Online publication date: 8-Dec-2023
https://dl.acm.org/doi/10.1145/3630202.3630236
Noah NMayer PDas S(2023)A Proposal to Study Shoulder-Surfing Resistant Authentication for Augmented and Virtual Reality: Replication Study in the USCompanion Publication of the 2023 Conference on Computer Supported Cooperative Work and Social Computing10.1145/3584931.3607007(317-322)Online publication date: 14-Oct-2023
https://dl.acm.org/doi/10.1145/3584931.3607007
Papadogiannakis EPapadopoulos PP. Markatos EKourtellis N(2023)Who Funds Misinformation? A Systematic Analysis of the Ad-related Profit Routines of Fake News SitesProceedings of the ACM Web Conference 202310.1145/3543507.3583443(2765-2776)Online publication date: 30-Apr-2023
https://dl.acm.org/doi/10.1145/3543507.3583443
Callejo PGramaglia MCuevas RCuevas Á(2023)A Deep Dive into the Accuracy of IP Geolocation Databases and its Impact on Online AdvertisingIEEE Transactions on Mobile Computing10.1109/TMC.2022.316678522:8(4359-4373)Online publication date: 1-Aug-2023
https://doi.org/10.1109/TMC.2022.3166785
Gkiouzepi EAndreou AGoga OLoiseau P(2023)Collaborative Ad Transparency: Promises and Limitations2023 IEEE Symposium on Security and Privacy (SP)10.1109/SP46215.2023.10179448(2639-2657)Online publication date: May-2023
https://doi.org/10.1109/SP46215.2023.10179448
Kikuchi HAoyama A(2023)Targeted Ads Analysis: What are The most Targeted Personas?2023 IEEE International Conference on Big Data (BigData)10.1109/BigData59044.2023.10386760(5512-5518)Online publication date: 15-Dec-2023
https://doi.org/10.1109/BigData59044.2023.10386760
Bilby JMarti DPritchard E(2023)Signaling Authenticity: Practitioner Views of the Signaling Power of Creative Advertising in a Digital WorldAdvances in Advertising Research (Vol. XII)10.1007/978-3-658-40429-1_9(121-135)Online publication date: 11-Apr-2023
https://doi.org/10.1007/978-3-658-40429-1_9
Vassiliades ABassiliades NPatkos TVrakas D(2022)An Open-Ended Web Knowledge Retrieval Framework for the Household Domain With Explanation and Learning Through ArgumentationInternational Journal on Semantic Web & Information Systems10.4018/IJSWIS.30942118:1(1-34)Online publication date: 26-Aug-2022
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