Advertisements have become commonplace on modern websites. While ads are typically designed for visual consumption, it is unclear how they affect blind users who interact with the ads using a screen reader. Existing research studies on non-visual web interaction predominantly focus on general web browsing; the specific impact of extraneous ad content on blind users’ experience remains largely unexplored. To fill this gap, we conducted an interview study with 18 blind participants; we found that blind users are often deceived by ads that contextually blend in with the surrounding web page content. While ad blockers can address this problem via a blanket filtering operation, many websites are increasingly denying access if an ad blocker is active. Moreover, ad blockers often do not filter out internal ads injected by the websites themselves. Therefore, we devised an algorithm to automatically identify contextually deceptive ads on a web page. Specifically, we built a detection model that leverages a multi-modal combination of handcrafted and automatically extracted features to determine if a particular ad is contextually deceptive. Evaluations of the model on a representative test dataset and ‘in-the-wild’ random websites yielded F1 scores of 0.86 and 0.88, respectively.
more »
« less
Who Am I?: A Design Probe Exploring Real-Time Transparency about Online and Offline User Profiling Underlying Targeted Ads
To enable targeted ads, companies profile Internet users, automatically inferring potential interests and demographics. While current profiling centers on users' web browsing data, smartphones and other devices with rich sensing capabilities portend profiling techniques that draw on methods from ubiquitous computing. Unfortunately, even existing profiling and ad-targeting practices remain opaque to users, engendering distrust, resignation, and privacy concerns. We hypothesized that making profiling visible at the time and place it occurs might help users better understand and engage with automatically constructed profiles. To this end, we built a technology probe that surfaces the incremental construction of user profiles from both web browsing and activities in the physical world. The probe explores transparency and control of profile construction in real time. We conducted a two-week field deployment of this probe with 25 participants. We found that increasing the visibility of profiling helped participants anticipate how certain actions can trigger specific ads. Participants' desired engagement with their profile differed in part based on their overall attitudes toward ads. Furthermore, participants expected algorithms would automatically determine when an inference was inaccurate, no longer relevant, or off-limits. Current techniques typically do not do this. Overall, our findings suggest that leveraging opportunistic moments within pervasive computing to engage users with their own inferred profiles can create more trustworthy and positive experiences with targeted ads.
more »
« less
- Award ID(s):
- 2047827
- NSF-PAR ID:
- 10319423
- Date Published:
- Journal Name:
- Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
- Volume:
- 5
- Issue:
- 3
- ISSN:
- 2474-9567
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Advertising companies and data brokers often provide consumers access to a dashboard summarizing attributes they have collected or inferred about that user. These attributes can be used for targeted advertising. Several studies have examined the accuracy of these collected attributes or users’ reactions to them. However, little is known about how these dashboards, and the associated attributes, change over time. Here, we report data from a week-long, longitudinal study (𝑛=158) in which participants used a browser extension automatically capturing data from one dashboard, Google Ads Settings, after every fifth website the participant visited. The results show that Ads Settings is frequently updated, includes many attributes unique to only a single participant in our sample, and is approximately 90% accurate when assigning age and gender. We also find evidence that Ads Settings attributes may dynamically impact browsing behavior and may be filtered to remove sensitive interests.more » « less
-
When consumers install Internet-connected "smart devices" in their homes, metadata arising from the communications between these devices and their cloud-based service providers enables adversaries privy to this traffic to profile users, even when adequate encryption is used. Internet service providers (ISPs) are one potential adversary privy to users’ incom- ing and outgoing Internet traffic and either currently use this insight to assemble and sell consumer advertising profiles or may in the future do so. With existing defenses against such profiling falling short of meeting user preferences and abilities, there is a need for a novel solution that empowers consumers to defend themselves against profiling by ISP-like actors and that is more in tune with their wishes. In this thesis, we present The Onion Router for Smart Homes (TorSH), a network of smart-home routers working collaboratively to defend smart-device traffic from analysis by ISP-like adversaries. We demonstrate that TorSH succeeds in deterring such profiling while preserving smart-device experiences and without encumbering latency-sensitive, non-smart-device experiences like web browsing.more » « less
-
Web data records are usually accompanied by auxiliary webpage segments, such as filters, sort options, search form, and multi-page links, to enhance interaction efficiency and convenience for end users. However, blind and visually impaired (BVI) persons are presently unable to fully exploit the auxiliary segments like their sighted peers, since these segments are scattered all across the screen, and as such assistive technologies used by BVI users, i.e., screen reader and screen magnifier, are not geared for efficient interaction with such scattered content. Specifically, for blind screen reader users, content navigation is predominantly one-dimensional despite the support for skipping content, and therefore navigating to-and-fro between different parts of the webpage is tedious and frustrating. Similarly, low vision screen magnifier users have to continuously pan back-and-forth between different portions of a webpage, given that only a portion of the screen is viewable at any instant due to content enlargement. The extant techniques to overcome inefficient web interaction for BVI users have mostly focused on general web-browsing activities, and as such they provide little to no support for data record-specific interaction activities such as filtering and sorting – activities that are equally important for facilitating quick and easy access to desired data records. To fill this void, we present InSupport, a browser extension that: (i) employs custom machine learning-based algorithms to automatically extract auxiliary segments on any webpage containing data records; and (ii) provides an instantly accessible proxy one-stop interface for easily navigating the extracted auxiliary segments using either basic keyboard shortcuts or mouse actions. Evaluation studies with 14 blind participants and 16 low vision participants showed significant improvement in web usability with InSupport, driven by increased reduction in interaction time and user effort, compared to the state-of-the-art solutions.more » « less
-
In an increasingly information-dense web, how do we ensure that we do not fall for unreliable information? To design better web literacy practices for assessing online information, we need to understand how people perceive the credibility of unfamiliar websites under time constraints. Would they be able to rate real news websites as more credible and fake news websites as less credible? We investigated this research question through an experimental study with 42 participants (mean age = 28.3) who were asked to rate the credibility of various “real news” (n = 14) and “fake news” (n = 14) websites under different time conditions (6s, 12s, 20s), and with a different advertising treatment (with or without ads). Participants did not visit the websites to make their credibility assessments; instead, they interacted with the images of website screen captures, which were modified to remove any mention of website names, to avoid the effect of name recognition. Participants rated the credibility of each website on a scale from 1 to 7 and in follow-up interviews provided justifications for their credibility scores. Through hypothesis testing, we find that participants, despite limited time exposure to each website (between 6 and 20 seconds), are quite good at the task of distinguishing between real and fake news websites, with real news websites being overall rated as more credible than fake news websites. Our results agree with the well-known theory of “first impressions” from psychology, that has established the human ability to infer character traits from faces. That is, participants can quickly infer meaningful visual and content cues from a website, that are helping them make the right credibility evaluation decision.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3478122
