“Be a Pattern for the World”: The Development of a Dark Patterns Detection Tool to Prevent Online User Loss

Jordan Donnelly; Alan Dowley; Yunpeng Liu; Yufei Su; Quanwei Sun; Lan Zeng; Andrea Curley; Damian Gordon; Paul Kelly; Dympna O'Sullivan; Anna Becevel

doi:10.21427/2y2q-6323

“Be a Pattern for the World”: The Development of a Dark Patterns Detection Tool to Prevent Online User Loss

Jordan Donnelly, Alan Dowley, Yunpeng Liu, Yufei Su, Quanwei Sun, Lan Zeng, Andrea Curley, Damian Gordon, Paul Kelly, Dympna O'Sullivan, Anna Becevel

Research output: Contribution to conference › Paper › peer-review

Abstract

Dark Patterns are designed to trick users into sharing more information or spending more money than they had intended to do, by configuring online interactions to confuse or add pressure to the users. They are highly varied in their form, and are therefore difficult to classify and detect. Therefore, this research is designed to develop a framework for the automated detection of potential instances of web-based dark patterns, and from there to develop a software tool that will provide a highly useful defensive tool that helps detect and highlight these patterns.

Original language	English
DOIs	https://doi.org/10.21427/2y2q-6323
Publication status	Published - 2022
Event	20th International Conference on the Ethical and Social issues in Information and Communication Technologies - Turku, Finland Duration: 26 Jul 2022 → 28 Jul 2022

Conference

Conference	20th International Conference on the Ethical and Social issues in Information and Communication Technologies
Country/Territory	Finland
City	Turku
Period	26/07/22 → 28/07/22

Keywords

Dark Patterns
automated detection
web-based
software tool

Access to Document

10.21427/2y2q-6323Licence: CC BY

Cite this

Donnelly, J., Dowley, A., Liu, Y., Su, Y., Sun, Q., Zeng, L., Curley, A., Gordon, D., Kelly, P., O'Sullivan, D., & Becevel, A. (2022). “Be a Pattern for the World”: The Development of a Dark Patterns Detection Tool to Prevent Online User Loss. Paper presented at 20th International Conference on the Ethical and Social issues in Information and Communication Technologies, Turku, Finland. https://doi.org/10.21427/2y2q-6323

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title = "“Be a Pattern for the World”: The Development of a Dark Patterns Detection Tool to Prevent Online User Loss",

abstract = "Dark Patterns are designed to trick users into sharing more information or spending more money than they had intended to do, by configuring online interactions to confuse or add pressure to the users. They are highly varied in their form, and are therefore difficult to classify and detect. Therefore, this research is designed to develop a framework for the automated detection of potential instances of web-based dark patterns, and from there to develop a software tool that will provide a highly useful defensive tool that helps detect and highlight these patterns.",

keywords = "Dark Patterns, automated detection, web-based, software tool",

author = "Jordan Donnelly and Alan Dowley and Yunpeng Liu and Yufei Su and Quanwei Sun and Lan Zeng and Andrea Curley and Damian Gordon and Paul Kelly and Dympna O'Sullivan and Anna Becevel",

year = "2022",

doi = "10.21427/2y2q-6323",

language = "English",

note = "20th International Conference on the Ethical and Social issues in Information and Communication Technologies ; Conference date: 26-07-2022 Through 28-07-2022",

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Donnelly, J, Dowley, A, Liu, Y, Su, Y, Sun, Q, Zeng, L, Curley, A, Gordon, D, Kelly, P, O'Sullivan, D & Becevel, A 2022, '“Be a Pattern for the World”: The Development of a Dark Patterns Detection Tool to Prevent Online User Loss', Paper presented at 20th International Conference on the Ethical and Social issues in Information and Communication Technologies, Turku, Finland, 26/07/22 - 28/07/22. https://doi.org/10.21427/2y2q-6323

“Be a Pattern for the World”: The Development of a Dark Patterns Detection Tool to Prevent Online User Loss. / Donnelly, Jordan; Dowley, Alan; Liu, Yunpeng et al.
2022. Paper presented at 20th International Conference on the Ethical and Social issues in Information and Communication Technologies, Turku, Finland.

Research output: Contribution to conference › Paper › peer-review

TY - CONF

T1 - “Be a Pattern for the World”: The Development of a Dark Patterns Detection Tool to Prevent Online User Loss

AU - Donnelly, Jordan

AU - Dowley, Alan

AU - Liu, Yunpeng

AU - Su, Yufei

AU - Sun, Quanwei

AU - Zeng, Lan

AU - Curley, Andrea

AU - Gordon, Damian

AU - Kelly, Paul

AU - O'Sullivan, Dympna

AU - Becevel, Anna

PY - 2022

Y1 - 2022

N2 - Dark Patterns are designed to trick users into sharing more information or spending more money than they had intended to do, by configuring online interactions to confuse or add pressure to the users. They are highly varied in their form, and are therefore difficult to classify and detect. Therefore, this research is designed to develop a framework for the automated detection of potential instances of web-based dark patterns, and from there to develop a software tool that will provide a highly useful defensive tool that helps detect and highlight these patterns.

AB - Dark Patterns are designed to trick users into sharing more information or spending more money than they had intended to do, by configuring online interactions to confuse or add pressure to the users. They are highly varied in their form, and are therefore difficult to classify and detect. Therefore, this research is designed to develop a framework for the automated detection of potential instances of web-based dark patterns, and from there to develop a software tool that will provide a highly useful defensive tool that helps detect and highlight these patterns.

KW - Dark Patterns

KW - automated detection

KW - web-based

KW - software tool

U2 - 10.21427/2y2q-6323

DO - 10.21427/2y2q-6323

M3 - Paper

T2 - 20th International Conference on the Ethical and Social issues in Information and Communication Technologies

Y2 - 26 July 2022 through 28 July 2022

ER -

“Be a Pattern for the World”: The Development of a Dark Patterns Detection Tool to Prevent Online User Loss

Abstract

Conference

Keywords

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