| --- |
| license: mit |
| language: |
| - en |
| tags: |
| - text-classification |
| - social-science |
| - politics |
| - sentiment-analysis |
| - benchmark |
| task_categories: |
| - text-classification |
| task_ids: |
| - multi-class-classification |
| - sentiment-classification |
| annotations_creators: |
| - human-annotated |
| multilinguality: monolingual |
| --- |
| |
| [](https://github.com/iqss-research/readme-software) |
|
|
| # Automated Nonparametric Content Analysis Datasets |
|
|
| This repository provides the four benchmark datasets used in: |
|
|
| > Connor T. Jerzak, Gary King, and Anton Strezhnev. **An Improved Method of Automated Nonparametric Content Analysis for Social Science.** *Political Analysis*, 31(1): 42–58, 2023. |
|
|
| Each dataset is formatted for easy loading in Python and R (CSV). Labels are integer-coded from `1,...,K`; text is provided as raw strings. |
|
|
| ## Datasets |
|
|
| | Name | Documents | Categories | Source & Description | |
| | --------------- | --------: | ---------: | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- | |
| | **enron.csv** | 1,426 | 5 | Corporate emails from the Enron corpus, hand-coded into five thematic categories (e.g., business, personal, legal) | |
| | **immigration.csv** | 462 | 5 | Newspaper editorials on immigration policy, hand-coded into five sentiment/policy categories; originally used in Hopkins & King (2010) and Jerzak et al. (2023) | |
| | **clinton.csv** | 1,938 | 7 | Blog posts about Hillary Clinton from 2008, hand-coded into seven topical categories; feature space of \~3,623 word stems | |
| | **stanford.csv** | 11,855 | 5 | Sentences from the Stanford Sentiment Treebank, labeled on a five-point sentiment scale; commonly used in text quantification research | |
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|
|
| --- |
|
|
| ### Citation |
|
|
| Connor T. Jerzak, Gary King, Anton Strezhnev. *An Improved Method of Automated Nonparametric Content Analysis for Social Science*. Political Analysis, 31(1): 42–58, 2023. [\[PDF\]](https://neuristemic.ai/wp-content/uploads/2026/05/div-class-title-an-improved-method-of-automated-nonparametric-content-analysis-for-social-science-div.pdf) |
|
|
| ``` |
| @article{JSK-readme2, |
| title={An Improved Method of Automated Nonparametric Content Analysis for Social Science}, |
| author={Jerzak, Connor T. and Gary King and Anton Strezhnev}, |
| journal={Political Analysis}, |
| year={2023}, |
| volume={31}, |
| number={1}, |
| pages={42-58} |
| } |
| ``` |
|
|
