eltsai/ShopTC-100K

ShopTC-100K Dataset

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The ShopTC-100K dataset is collected using TermMiner, an open-source data collection and topic modeling pipeline introduced in the paper:

Harmful Terms and Where to Find Them: Measuring and Modeling Unfavorable Financial Terms and Conditions in Shopping Websites at Scale

If you find this dataset or the related paper useful for your research, please cite our paper:

@inproceedings{tsai2025harmful,
  author = {Elisa Tsai and Neal Mangaokar and Boyuan Zheng and Haizhong Zheng and Atul Prakash},
  title = {Harmful Terms and Where to Find Them: Measuring and Modeling Unfavorable Financial Terms and Conditions in Shopping Websites at Scale},
  booktitle = {Proceedings of the ACM Web Conference 2025 (WWW ’25)},
  year = {2025},
  location = {Sydney, NSW, Australia},
  publisher = {ACM},
  address = {New York, NY, USA},
  pages = {14},
  month = {April 28-May 2},
  doi = {10.1145/3696410.3714573}
}

Dataset Description

The dataset consists of sanitized terms extracted from 8,251 e-commerce websites with English-language terms and conditions. The websites were sourced from the Tranco list (as of April 2024). The dataset contains:

• —1,825,231 sanitized sentences
• —7,777 unique websites
• —Four split files for ease of use:

ShopTC-100K
├── sanitized_split1.csv
├── sanitized_split2.csv
├── sanitized_split3.csv
├── sanitized_split4.csv

Data Sanitization Process

The extracted terms are cleaned and structured using a multi-step sanitization pipeline:

• —HTML Parsing: Raw HTML content is processed to extract text from <p> tags.
• —Sentence Tokenization: Text is split into sentences using a transformer-based tokenization model.
• —Filtering: Short sentences (<10 words) and duplicates are removed.
• —Preprocessing: Newline characters and extra whitespace are cleaned.

Example Data

The dataset is structured as follows: | URL | Paragraph | |-----------------------|----------------------------------------------------------------| | pythonanywhere.com | Copyright © 2011-2024 PythonAnywhere LLP — Terms of Service apply. | | pythonanywhere.com | We use cookies to provide social media features and to analyze our traffic. | | pythonanywhere.com | 2.8 You acknowledge that clicking on Links may lead to third-party sites. | | pythonanywhere.com | 3.4 No payment will be made unless and until Account verification is complete. | | pythonanywhere.com | 11.3 All licenses granted to you in this agreement are non-transferable. |