Annoyed Users

Pujol, Enric; Hohlfeld, Oliver; Feldmann, Anja

doi:10.1145/2815675.2815705

Cited by 89 publications

(8 citation statements)

References 31 publications

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“…Gugelmann et al in [29] investigated how to detect privacyintrusive trackers and services from passive measurements and propose an automated approach that relies on a set of web traffic features to identify such services and thus help developers maintaining filter lists. Pujol et al in [38] used Adblock Plus filter lists for passive network classification. By analyzing data from a major European ISP authors show that 22% of the active users have Adblock Plus deployed.…”

Section: Filter Listsmentioning

confidence: 99%

“…30% of all internet users [25]) use filter lists to maintain a secure, private, performant, and appealing web. Prior work has shown that filter lists, and the types of content blocking they enable, significantly reduce data use [37], protect users from malware [36], improve browser performance [28,38] and significantly reduce how often and persistently users are tracked on the web.…”

Section: Introductionmentioning

confidence: 99%

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Filter List Generation for Underserved Regions

Sjösten

Snyder

Pastor

et al. 2020

Proceedings of the Web Conference 2020

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Filter lists play a large and growing role in protecting and assisting web users. The vast majority of popular filter lists are crowd-sourced, where a large number of people manually label resources related to undesirable web resources (e.g. ads, trackers, paywall libraries), so that they can be blocked by browsers and extensions.Because only a small percentage of web users participate in the generation of filter lists, a crowd-sourcing strategy works well for blocking either uncommon resources that appear on "popular" websites, or resources that appear on a large number of "unpopular" websites. A crowd-sourcing strategy will perform poorly for parts of the web with small "crowds", such as regions of the web serving languages with (relatively) few speakers.This work addresses this problem through the combination of two novel techniques: (i) deep browser instrumentation that allows for the accurate generation of request chains, in a way that is robust in situations that confuse existing measurement techniques, and (ii) an ad classifier that uniquely combines perceptual and page-context features to remain accurate across multiple languages.We apply our unique two-step filter list generation pipeline to three regions of the web that currently have poorly maintained filter lists: Sri Lanka, Hungary, and Albania. We generate new filter lists that complement existing filter lists. Our complementary lists block an additional 3,349 of ad and ad-related resources (1,771 unique) when applied to 6,475 pages targeting these three regions.We hope that this work can be part of an increased effort at ensuring that the security, privacy, and performance benefits of web resource blocking can be shared with all users, and not only those in dominant linguistic or economic regions. CCS CONCEPTS• Security and privacy → Human and societal aspects of security and privacy; • Information systems → Web applications.

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Section: Filter Listsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Filter List Generation for Underserved Regions

Sjösten

Snyder

Pastor

et al. 2020

Proceedings of the Web Conference 2020

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“…Nowadays, programming techniques allow detecting mechanisms for blocking advertisements very effectively, and then prevent access to the website when ad blocking software is active and set to block advertisements [25], [26]. With blocking ads, it is possible to effectively fight at the technology level [27]. Mastering the phenomenon at the social level is not so easy.…”

Section: Website Owners Preventing Ad Blockingmentioning

confidence: 99%

Evaluation of Adblock Software Usage

Sołtysik-Piorunkiewicz

Strzelecki

Abramek

2019

CSIMQ

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The article shows the main factors of adblocking software usage. The study was based on data obtained by a web questionnaire. The research was focused on evaluation of ad blocking (adblock) software usage factors in five categories: (1) gender, age, and education; (2) use of advertising and sources of knowledge about advertising; (3) technical and social reasons for blocking online advertisements; (4) usage of an adblock-wall; and (5) type of online advertisement. An evaluation of adblock usage factors revealed four main technical reasons for adblock usage connected with website technology and web development problemsinterruption, amount of ads, speed, and security; and one social reason for adblock usage, namely, the problem of privacy.

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“…Nonetheless, online ads, especially intrusive ads, have usability consequences [6]. As Pujol et al [35] observed, 22% of the most active users of a major European ISP use Adblock Plus. As a result, providing the main content in a simple and less cluttered page, such as Reader Mode, not only decreases the complexity of a page, but also can preserve privacy by limiting the number of requests for third-party services and trackers [12,24] as well as improve user experience.…”

Section: Performance and User Experiencementioning

confidence: 99%

SpeedReader: Reader Mode Made Fast and Private

Ghasemisharif

Snyder²,

Auçinas

et al. 2019

The World Wide Web Conference

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Most popular web browsers include "reader modes" that improve the user experience by removing un-useful page elements. Reader modes reformat the page to hide elements that are not related to the page's main content. Such page elements include site navigation, advertising related videos and images, and most JavaScript. The intended end result is that users can enjoy the content they are interested in, without distraction.In this work, we consider whether the "reader mode" can be widened to also provide performance and privacy improvements. Instead of its use as a post-render feature to clean up the clutter on a page we propose SpeedReader as an alternative multistep pipeline that is part of the rendering pipeline. Once the tool decides during the initial phase of a page load that a page is suitable for reader mode use, it directly applies document tree translation before the page is rendered.Based on our measurements, we believe that SpeedReader can be continuously enabled in order to drastically improve end-user experience, especially on slower mobile connections. Combined with our approach to predicting which pages should be rendered in reader mode with 91% accuracy, it achieves drastic speedups and bandwidth reductions of up to 27× and 84× respectively on average. We further find that our novel "reader mode" approach brings with it significant privacy improvements to users. Our approach effectively removes all commonly recognized trackers, issuing 115 fewer requests to third parties, and interacts with 64 fewer trackers on average, on transformed pages.

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Annoyed Users

Cited by 89 publications

References 31 publications

Filter List Generation for Underserved Regions

Filter List Generation for Underserved Regions

Evaluation of Adblock Software Usage

SpeedReader: Reader Mode Made Fast and Private

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