Taking Data Out of Context to Hyper-Personalize Ads

Abstract: Data brokers and advertisers increasingly collect data in one context and use it in another. When users encounter a misuse of their data, do they subsequently disclose less information? We report on human-subjects experiments with 25 in-person and 280 online participants. First, participants provided personal information amidst distractor questions. A week later, while participants completed another survey, they received either a robotext or online banner ad seemingly unrelated to the study. Half of the participants received an ad containing their name, partner’s name, preferred cuisine, and location; others received a generic ad. We measured how many of 43 potentially invasive questions participants subsequently chose to answer. Participants reacted negatively to the personalized ad, yet answered nearly all invasive questions accurately. We unpack our results relative to the privacy paradox, contextual integrity, and power dynamics in crowdworker platforms.

25/04/2020

What Twitter Knows: Characterizing Ad Targeting Practices, User Perceptions, and Ad Explanations Through Users' Own Twitter Data

Miranda Wei, Madison Stamos, Sophie Veys and
Nathan Reitinger, Justin Goodman, Margot Herman, Dorota Filipczuk, Ben Weinshel, Michelle L. Mazurek, Blase Ur

Keywords Paper

12:16

25/04/2020

Informing the Design of a Personalized Privacy Assistant for the Internet of Things

Jessica Colnago, Yuanyuan Feng, Tharangini Palanivel and
Sarah Pearman, Megan Ung, Alessandro Acquisti, Lorrie Cranor, Norman Sadeh

"I am uncomfortable sharing what I can't see": Privacy Concerns of the Visually Impaired with Camera Based Assistive Applications

Psychological, personality-based and ethnographic studies of social media, Qualitative and quantitative studies of social media, Subjectivity in textual data, sentiment analysis, polarity/opinion identification and extraction, linguistic analyses of social

8:00

07/08/2020

Algorithms, Meta-Learning, Algorithms, Multitask and Transfer Learning, Social Aspects of Machine Learning, Privacy, Anonymity, and Security

5:03

16/11/2020

conversational recommendation, asking clarifying questions, question-based systems, empirical study, conversational search

7:16

06/12/2021

Exercise? I thought you said 'Extra Fries’: Leveraging Sentence Demarcations and Multi-hop Attention for Meme Affect Analysis

Shraman Pramanick, Md Shad Akhtar, Tanmoy Chakraborty

Keywords Paper

Subjectivity in textual data, sentiment analysis, polarity/opinion identification and extraction, linguistic analyses of social media behavior

7:57

04/07/2020

Towards Understanding Gender Bias in Relation Extraction

Andrew Gaut, Tony Sun, Shirlyn Tang and
Yuxin Huang, Jing Qian, Mai ElSherief, Jieyu Zhao, Diba Mirza, Elizabeth Belding, Kai-Wei Chang, William Yang Wang