Update on July 10, 2025: + We are uploading the whole AdsDP dataset to Kaggle (https://www.kaggle.com). This repository is an online demo that includes videos recorded by one researcher interacting with 81 English-language apps (which leads to 81 videos), and 9 Chinese-language apps (leads to 9 videos) along with the corresponding annotation files, in which you can directly view or download videos to get an overview of the dataset without having to download the compressed files. The complete dataset contains 718 videos, with a total duration of approximately 60 hours, and annotates 5,782 instances of ads-related dark patterns. Due to repository size limitations, we had to split the complete dataset into 2 parts (English apps and Chinese apps) for uploading. The links to the full AdsDP dataset are listed below: Online Demo: AdsDP: A Video Dataset for Recognizing and Examining Dark Patterns in iOS In-App Advertisements En-App: (En-App) AdsDP Cn-App: (Cn-App) AdsDP If you use this dataset, or the findings from the paper, please cite: @article{shang2025adsdp, title={AdsDP: A Video Dataset for Recognizing and Examining Dark Patterns in iOS In-App Advertisements}, author={Shang, Yuxuan and Wang, Guanxiao and Ren, Mengxia and Zhang, Haomin and Chen, Xingming and Xu, Haitao and Yue, Chuan and Hao, Shuai and Zhou, Bo and Ma, Wenrui and others}, journal={Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies}, volume={9}, number={3}, pages={1--31}, year={2025}, publisher={ACM New York, NY, USA} } ----------------- Update on May 1, 2025: + We added a manual for guiding researchers in operating the app and annotating ad dark patterns. + We added a record of a regular meeting, which helps to understand how we refined the codebook and manual, and clarified confusing instances to precisely define boundaries between ads dark patterns. ----------------- First Submission on Feb 1, 2025: This is a video dataset for studying deceptive or malicious UI designs related to advertisements, also known as "ads dark patterns". It captures the full interaction process of four researchers with 485 Chinese or English apps using iOS screen recording and annotates the occurrences and characteristics of identified ads dark patterns. More details about the dataset are provided in our paper, "AdsDP: A Video Dataset for Recognizing and Examining Dark Patterns in iOS In-App Advertisements." Each video corresponds to multiple rows in the annotation file. The first row contains the app’s basic information and dark patterns related to the ads' contextual design (namely, app's design), which are referred to as external dark patterns in the paper. From the second row onward, each row represents an ad and the dark patterns occurring within it, referred to as internal dark patterns. For more details, readers can refer to README. The complete dataset contains 718 videos, with a total duration of approximately 60 hours, and annotates 5,782 instances of ads-related dark patterns. Due to repository size limitations, we have currently uploaded videos recorded by one researcher interacting with 81 English-language apps (which leads to 81 videos), and 9 Chinese-language apps (leads to 9 videos) along with the corresponding annotation files. The complete dataset will be released soon.