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first draft of model card

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@@ -24,8 +24,64 @@ tags:
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  - noncooperation
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  - pejorative
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  - sarcasm
 
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  task_categories:
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  - text-classification
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  task_ids:
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  - multi-label-classification
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - noncooperation
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  - pejorative
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  - sarcasm
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+ - vulgarity
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  task_categories:
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  - text-classification
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  task_ids:
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  - multi-label-classification
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  ---
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+
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+ # Dataset Card for incivility-arizona-daily-star-comments
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+ This is a collection of more than 6000 comments on Arizona Daily Star news articles from 2011 that have been manually annotated for various forms of incivility including aspersion, namecalling, sarcasm, and vulgarity.
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+
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+ ## Dataset Structure
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+
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+ Each instance in the dataset corresponds to a single comment from a single commenter.
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+ An instance's `text` field contains the text of the comment with any quotes of other commenters removed.
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+ The remaining fields in each instance provide binary labels for each type of incivility annotated:
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+ `aspersion`, `hyperbole`, `lying`, `namecalling`, `noncooperation`, `offtopic`, `pejorative`, `sarcasm`, `vulgarity`, and `other_incivility`.
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+
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+ The dataset provides three standard splits: `train`, `validation`, and `test`.
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+
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+ ## Dataset Creation
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+ The original annotation effort is described in:
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+ - Kevin Coe, Kate Kenski, Stephen A. Rains.
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+ [Online and Uncivil? Patterns and Determinants of Incivility in Newspaper Website Comments](https://doi.org/10.1111/jcom.12104).
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+ Journal of Communication, Volume 64, Issue 4, August 2014, Pages 658–679.
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+
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+ That dataset was converted to a computer-friendly form as described in section 4.2.1 of:
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+
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+ - Farig Sadeque.
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+ [User behavior in social media: engagement, incivility, and depression](https://repository.arizona.edu/handle/10150/633192).
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+ PhD thesis. The University of Arizona. 2019.
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+
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+ The current upload is a 2023 conversion of that form to a huggingface Dataset.
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+
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+ ## Considerations for Using the Data
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+ The data is intended for the study of incivility.
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+ It should not be used to train models to generate incivility.
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+ The human coders and their trainers were mostly [Western, educated, industrialized, rich and democratic (WEIRD)](https://www.nature.com/articles/466029a), which may have shaped how they evaluated incivility.
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @article{10.1111/jcom.12104,
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+ author = {Coe, Kevin and Kenski, Kate and Rains, Stephen A.},
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+ title = {Online and Uncivil? Patterns and Determinants of Incivility in Newspaper Website Comments},
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+ journal = {Journal of Communication},
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+ volume = {64},
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+ number = {4},
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+ pages = {658-679},
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+ year = {2014},
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+ month = {06},
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+ issn = {0021-9916},
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+ doi = {10.1111/jcom.12104},
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+ url = {https://doi.org/10.1111/jcom.12104},
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+ }
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+ ```