---
dataset_info:
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  - name: content
    dtype: string
  - name: subreddit
    dtype: string
  - name: dog_whistle
    dtype: string
  - name: date
    dtype: string
  - name: ingroup
    dtype: string
  - name: source
    dtype: string
  splits:
  - name: train
    num_bytes: 1926104999
    num_examples: 6026919
  download_size: 978098068
  dataset_size: 1926104999
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---


# Silent Signals | Informal Potential Dogwhistles (Potential Instance Dataset)

**A dataset of *potential* dogwhistle use cases in informal discourse.** A dog whistle is a form of coded communication that carries a secondary meaning to specific audiences and is often weaponized for racial and socioeconomic discrimination. Dog whistling historically originated from United States politics, but in recent years has taken root in social media as a means of evading hate speech detection systems and maintaining plausible deniability.

**This dataset contains over 6 million excepts from Reddit comments that contain a dogwhistle term, created via keyword search on terms in the [Allen AI Dogwhistle Glossary](https://dogwhistles.allen.ai/)**. Therefore, many of the excerpts are likely using these terms in a non-coded sense. This dataset was used as input to our approach for word-sense disambiguation of dog whistles from standard speech using Large Language Models (LLMs). Please see the paper linked below for more details.

*Although we collect over 7 million potential dog whistle instances, due to resource constraints, we only sample 100,000 instances for the creation of the Silent Signals dataset. **Therefore, we release the Potential Dog Whistle Dataset to enable the open sourced expansion of the Silent Signals dataset.***

<p style="color:red;">Please note, this dataset contains content that may be upsetting or offensive to some readers.</p>

**Published at ACL 2024!**

📄 **Paper Link** - [Silent Signals, Loud Impact: LLMs for Word-Sense Disambiguation of Coded Dog Whistles](https://aclanthology.org/2024.acl-long.675/)<br>
🗂️ **Disambiguated Dogwhistles Dataset** - [Silent-Signals on HuggingFace](https://huggingface.co/datasets/SALT-NLP/silent_signals)<br>
💻 **Dataset webpage** - Coming soon 🚀

<!-- ![head_figure_large.png](https://cdn-uploads.huggingface.co/production/uploads/632d02054a4991e711591c34/m70hfQTN2Aw7t3Ilkga4u.png) -->
<centering><img src="https://cdn-uploads.huggingface.co/production/uploads/632d02054a4991e711591c34/m70hfQTN2Aw7t3Ilkga4u.png" alt="head_figure" width="400"/></centering>


## Dataset Schema ##

| <nobr>Field Name </nobr>| <nobr>Type</nobr> | <nobr>Example</nobr> | <nobr>Description</nobr> |
|:------------|:------|:---------|:-------------|
| <nobr>**dog_whistle**</nobr> | <nobr>str</nobr> | <nobr>"illegals"</nobr> | <nobr>Dog whistle word or term.</nobr> |
| <nobr>**ingroup**</nobr> | <nobr>str</nobr> | <nobr>"anti-Latino"</nobr> | <nobr>The community that uses the dog whistle.</nobr> |
| <nobr>**content**</nobr> | <nobr>str</nobr> | <nobr>"In my State of Virginia, the governor put a stop <br>to the independent audits that were finding <br>thousands of illegals on the roll."</nobr> | <nobr>Text containing the dog whistle.</nobr> |
| <nobr>**date**</nobr> | <nobr>str</nobr> | <nobr>"11/14/2016"</nobr> | <nobr>Date of comment, formatted as `mm/dd/yyyy`.</nobr> |
| <nobr>**subreddit**</nobr> | <nobr>str</nobr> | <nobr>"The_Donald"</nobr> | <nobr>Subreddit where the comment was posted,<br> Null for Congressional data.</nobr> |
| <nobr>**source**</nobr> | <nobr>str</nobr> | <nobr>"PRAW API"</nobr> | <nobr>The source or method of data collection.</nobr> |
> NOTE: The dog whistles terms and definitions that enabled this research and data collection were sourced from the [Allen AI Dogwhistle Glossary](https://dogwhistles.allen.ai/).
> <br>


# Citations #

### MLA ###

Julia Kruk, Michela Marchini, Rijul Magu, Caleb Ziems, David Muchlinski, and Diyi Yang. 2024. Silent Signals, Loud Impact: LLMs for Word-Sense Disambiguation of Coded Dog Whistles. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 12493–12509, Bangkok, Thailand. Association for Computational Linguistics.

### Bibtex ###

```
@inproceedings{kruk-etal-2024-silent,
    title = "Silent Signals, Loud Impact: {LLM}s for Word-Sense Disambiguation of Coded Dog Whistles",
    author = "Kruk, Julia  and
      Marchini, Michela  and
      Magu, Rijul  and
      Ziems, Caleb  and
      Muchlinski, David  and
      Yang, Diyi",
    editor = "Ku, Lun-Wei  and
      Martins, Andre  and
      Srikumar, Vivek",
    booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = aug,
    year = "2024",
    address = "Bangkok, Thailand",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.acl-long.675",
    pages = "12493--12509",
    abstract = "A dog whistle is a form of coded communication that carries a secondary meaning to specific audiences and is often weaponized for racial and socioeconomic discrimination. Dog whistling historically originated from United States politics, but in recent years has taken root in social media as a means of evading hate speech detection systems and maintaining plausible deniability. In this paper, we present an approach for word-sense disambiguation of dog whistles from standard speech using Large Language Models (LLMs), and leverage this technique to create a dataset of 16,550 high-confidence coded examples of dog whistles used in formal and informal communication. Silent Signals is the largest dataset of disambiguated dog whistle usage, created for applications in hate speech detection, neology, and political science.",
}
```