Dark patterns in e-commerce: a dataset and its baseline evaluations

Yuki Yada*, Jiaying Feng, Tsuneo Matsumoto, Nao Fukushima, Fuyuko Kido, Hayato Yamana

*この研究の対応する著者

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

Dark patterns, which are user interface designs in online services, induce users to take unintended actions. Recently, dark patterns have been raised as an issue of privacy and fairness. Thus, a wide range of research on detecting dark patterns is eagerly awaited. In this work, we constructed a dataset for dark pattern detection and prepared its baseline detection performance with state-of-the-art machine learning methods. The original dataset was obtained from Mathur et al.'s study in 2019 [1], which consists of 1,818 dark pattern texts from shopping sites. Then, we added negative samples, i.e., non-dark pattern texts, by retrieving texts from the same websites as Mathur et al.'s dataset. We also applied state-of-the-art machine learning methods to show the automatic detection accuracy as baselines, including BERT, RoBERTa, ALBERT, and XLNet. As a result of 5-fold cross-validation, we achieved the highest accuracy of 0.975 with RoBERTa. The dataset and baseline source codes are available at https://github.com/yamanalab/ec-darkpattern.

本文言語English
ホスト出版物のタイトルProceedings - 2022 IEEE International Conference on Big Data, Big Data 2022
編集者Shusaku Tsumoto, Yukio Ohsawa, Lei Chen, Dirk Van den Poel, Xiaohua Hu, Yoichi Motomura, Takuya Takagi, Lingfei Wu, Ying Xie, Akihiro Abe, Vijay Raghavan
出版社Institute of Electrical and Electronics Engineers Inc.
ページ3015-3022
ページ数8
ISBN(電子版)9781665480451
DOI
出版ステータスPublished - 2022
イベント2022 IEEE International Conference on Big Data, Big Data 2022 - Osaka, Japan
継続期間: 2022 12月 172022 12月 20

出版物シリーズ

名前Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022

Conference

Conference2022 IEEE International Conference on Big Data, Big Data 2022
国/地域Japan
CityOsaka
Period22/12/1722/12/20

ASJC Scopus subject areas

  • モデリングとシミュレーション
  • コンピュータ ネットワークおよび通信
  • 情報システム
  • 情報システムおよび情報管理
  • 安全性、リスク、信頼性、品質管理
  • 制御と最適化

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