Clustering of Dark Patterns in the User Interfaces of Websites and Online Trading Portals (E-Commerce)
dark patterns in the interfaces of users using sites and portals of online trading affect their behavior by companies that own digital resources. The authors propose to implement the detection of dark patterns on sites in user interfaces using cluster analysis algorithms using two methods for cluste...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-09-01
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| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/10/18/3219 |
| _version_ | 1797485261775437824 |
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| author | Dmitry Nazarov Yerkebulan Baimukhambetov |
| author_facet | Dmitry Nazarov Yerkebulan Baimukhambetov |
| author_sort | Dmitry Nazarov |
| collection | DOAJ |
| description | dark patterns in the interfaces of users using sites and portals of online trading affect their behavior by companies that own digital resources. The authors propose to implement the detection of dark patterns on sites in user interfaces using cluster analysis algorithms using two methods for clustering many dark patterns in application interfaces: hierarchical and k-means. The complexity of the implementation lies in the lack of datasets that formalize dark patterns in user interfaces. The authors conducted a study and identified signs of dark patterns based on the use of Nelsen’s antisymmetric principles. The article proposes a technique for assessing dark patterns using linguistic variables and their further interval numerical assessment for implementing cluster data analysis. The last part of the article contains an analysis of two clustering algorithms and an analysis of the methods and procedures for applying them to clustering data according to previously selected features in the RStudio environment. We also gave a characteristic for each resulting cluster. |
| first_indexed | 2024-03-09T23:16:17Z |
| format | Article |
| id | doaj.art-161f626dbdfd4d5198f64ee8cba90ab6 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-09T23:16:17Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-161f626dbdfd4d5198f64ee8cba90ab62023-11-23T17:34:47ZengMDPI AGMathematics2227-73902022-09-011018321910.3390/math10183219Clustering of Dark Patterns in the User Interfaces of Websites and Online Trading Portals (E-Commerce)Dmitry Nazarov0Yerkebulan Baimukhambetov1Department of Business Informatics, Ural State University of Economics, 620144 Ekaterinburg, RussiaHead of the Institutional Effectiveness, Abai University, Almaty 050010, Kazakhstandark patterns in the interfaces of users using sites and portals of online trading affect their behavior by companies that own digital resources. The authors propose to implement the detection of dark patterns on sites in user interfaces using cluster analysis algorithms using two methods for clustering many dark patterns in application interfaces: hierarchical and k-means. The complexity of the implementation lies in the lack of datasets that formalize dark patterns in user interfaces. The authors conducted a study and identified signs of dark patterns based on the use of Nelsen’s antisymmetric principles. The article proposes a technique for assessing dark patterns using linguistic variables and their further interval numerical assessment for implementing cluster data analysis. The last part of the article contains an analysis of two clustering algorithms and an analysis of the methods and procedures for applying them to clustering data according to previously selected features in the RStudio environment. We also gave a characteristic for each resulting cluster.https://www.mdpi.com/2227-7390/10/18/3219dark patternclassificationclustering algorithmsuser interface |
| spellingShingle | Dmitry Nazarov Yerkebulan Baimukhambetov Clustering of Dark Patterns in the User Interfaces of Websites and Online Trading Portals (E-Commerce) Mathematics dark pattern classification clustering algorithms user interface |
| title | Clustering of Dark Patterns in the User Interfaces of Websites and Online Trading Portals (E-Commerce) |
| title_full | Clustering of Dark Patterns in the User Interfaces of Websites and Online Trading Portals (E-Commerce) |
| title_fullStr | Clustering of Dark Patterns in the User Interfaces of Websites and Online Trading Portals (E-Commerce) |
| title_full_unstemmed | Clustering of Dark Patterns in the User Interfaces of Websites and Online Trading Portals (E-Commerce) |
| title_short | Clustering of Dark Patterns in the User Interfaces of Websites and Online Trading Portals (E-Commerce) |
| title_sort | clustering of dark patterns in the user interfaces of websites and online trading portals e commerce |
| topic | dark pattern classification clustering algorithms user interface |
| url | https://www.mdpi.com/2227-7390/10/18/3219 |
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