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--- |
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license: mit |
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tags: |
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- tabular |
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- text |
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dataset_info: |
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languages: |
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- en |
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size_categories: |
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- 100M-1B |
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pretty_name: ShopTC-100K |
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task_categories: |
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- text-classification |
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- summarization |
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language: |
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- en |
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pretty_name: ShopTC-100K |
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size_categories: |
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- 100M<n<1B |
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--- |
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# ShopTC-100K Dataset |
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The ShopTC-100K dataset is collected using [TermMiner](https://github.com/eltsai/term_miner/), an open-source data collection and topic modeling pipeline introduced in the paper: |
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[Harmful Terms and Where to Find Them: Measuring and Modeling Unfavorable Financial Terms and Conditions in Shopping Websites at Scale](https://www.arxiv.org/abs/2502.01798) |
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If you find this dataset or the related paper useful for your research, please cite our paper: |
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``` |
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@inproceedings{tsai2025harmful, |
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author = {Elisa Tsai and Neal Mangaokar and Boyuan Zheng and Haizhong Zheng and Atul Prakash}, |
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title = {Harmful Terms and Where to Find Them: Measuring and Modeling Unfavorable Financial Terms and Conditions in Shopping Websites at Scale}, |
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booktitle = {Proceedings of the ACM Web Conference 2025 (WWW ’25)}, |
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year = {2025}, |
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location = {Sydney, NSW, Australia}, |
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publisher = {ACM}, |
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address = {New York, NY, USA}, |
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pages = {14}, |
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month = {April 28-May 2}, |
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doi = {10.1145/3696410.3714573} |
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} |
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``` |
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## Dataset Description |
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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](https://tranco-list.eu/) (as of April 2024). The dataset contains: |
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- 1,825,231 sanitized sentences |
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- 7,777 unique websites |
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- Four split files for ease of use: |
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``` |
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ShopTC-100K |
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├── sanitized_split1.csv |
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├── sanitized_split2.csv |
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├── sanitized_split3.csv |
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├── sanitized_split4.csv |
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``` |
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### Data Sanitization Process |
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The extracted terms are cleaned and structured using a multi-step sanitization pipeline: |
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- HTML Parsing: Raw HTML content is processed to extract text from `<p>` tags. |
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- Sentence Tokenization: Text is split into sentences using a transformer-based tokenization model. |
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- Filtering: Short sentences (<10 words) and duplicates are removed. |
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- Preprocessing: Newline characters and extra whitespace are cleaned. |
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| Split File | Rows | Columns | Unique Websites | |
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|--------------------------------------|---------|---------|----------------| |
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| sanitized_split1.csv | 523,760 | 2 | 1,979 | |
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| sanitized_split2.csv | 454,966 | 2 | 1,973 | |
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| sanitized_split3.csv | 425,028 | 2 | 1,988 | |
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| sanitized_split4.csv | 421,477 | 2 | 1,837 | |
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### Example Data |
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The dataset is structured as follows: |
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| URL | Paragraph | |
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|-----------------------|----------------------------------------------------------------| |
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