TY - GEN
T1 - Investigating Ad Transparency Mechanisms in Social Media
T2 - 25th Annual Network and Distributed System Security Symposium, NDSS 2018
AU - Andreou, Athanasios
AU - Venkatadri, Giridhari
AU - Goga, Oana
AU - Gummadi, Krishna P.
AU - Loiseau, Patrick
AU - Mislove, Alan
N1 - Publisher Copyright:
© 2018 25th Annual Network and Distributed System Security Symposium, NDSS 2018. All Rights Reserved.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Targeted advertising has been subject to many privacy complaints from both users and policy makers. Despite this attention, users still have little understanding of what data the advertising platforms have about them and why they are shown particular ads. To address such concerns, Facebook recently introduced two transparency mechanisms: a “Why am I seeing this?” button that provides users with an explanation of why they were shown a particular ad (ad explanations), and an Ad Preferences Page that provides users with a list of attributes Facebook has inferred about them and how (data explanations). In this paper, we investigate the level of transparency provided by these two mechanisms. We first define a number of key properties of explanations and then evaluate empirically whether Facebook’s explanations satisfy them. For our experiments, we develop a browser extension that collects the ads users receive every time they browse Facebook, their respective explanations, and the attributes listed on the Ad Preferences Page; we then use controlled experiments where we create our own ad campaigns and target the users that installed our extension. Our results show that ad explanations are often incomplete and sometimes misleading while data explanations are often incomplete and vague. Taken together, our findings have significant implications for users, policy makers, and regulators as social media advertising services mature.
AB - Targeted advertising has been subject to many privacy complaints from both users and policy makers. Despite this attention, users still have little understanding of what data the advertising platforms have about them and why they are shown particular ads. To address such concerns, Facebook recently introduced two transparency mechanisms: a “Why am I seeing this?” button that provides users with an explanation of why they were shown a particular ad (ad explanations), and an Ad Preferences Page that provides users with a list of attributes Facebook has inferred about them and how (data explanations). In this paper, we investigate the level of transparency provided by these two mechanisms. We first define a number of key properties of explanations and then evaluate empirically whether Facebook’s explanations satisfy them. For our experiments, we develop a browser extension that collects the ads users receive every time they browse Facebook, their respective explanations, and the attributes listed on the Ad Preferences Page; we then use controlled experiments where we create our own ad campaigns and target the users that installed our extension. Our results show that ad explanations are often incomplete and sometimes misleading while data explanations are often incomplete and vague. Taken together, our findings have significant implications for users, policy makers, and regulators as social media advertising services mature.
UR - https://www.scopus.com/pages/publications/85058403575
U2 - 10.14722/ndss.2018.23191
DO - 10.14722/ndss.2018.23191
M3 - Conference contribution
AN - SCOPUS:85058403575
T3 - 25th Annual Network and Distributed System Security Symposium, NDSS 2018
BT - 25th Annual Network and Distributed System Security Symposium, NDSS 2018
PB - The Internet Society
Y2 - 18 February 2018 through 21 February 2018
ER -