---
dataset_info:
features:
- name: date
dtype: string
- name: speaker
dtype: string
- name: chamber
dtype: string
- name: reference
dtype: string
- name: source
dtype: string
- name: party
dtype: string
- name: content
dtype: string
- name: dog_whistle
dtype: string
- name: ingroup
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 459187984
num_examples: 1096682
download_size: 139663768
dataset_size: 459187984
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Silent Signals | Formal Potential Dogwhistles (Potential Instance Dataset)
**A dataset of *potential* dogwhistle use cases in formal 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 1 million excepts from U.S. Congressional Records 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.
Please note, this dataset contains content that may be upsetting or offensive to some readers.
**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/)
📁 **Disambiguated Dogwhistles Dataset** - [Silent-Signals](https://huggingface.co/datasets/SALT-NLP/silent_signals)
💻 **Dataset webpage** - Coming soon 🚀
## Dataset Schema ##
| Field Name | Type | Example | Description |
|:------------|:------|:---------|:-------------|
| **dog_whistle** | str | "illegals" | Dog whistle word or term. |
| **dog_whistle_root** | str | "illegal immigrant" | The root form of the dog whistle,
as there could be multiple variations. |
| **ingroup** | str | "anti-Latino" | The community that uses the dog whistle. |
| **content** | str | "In my State of Virginia, the governor put a stop
to the independent audits that were finding
thousands of illegals on the roll." | Text containing the dog whistle. |
| **date** | str | "11/14/2016" | Date of comment, formatted as `mm/dd/yyyy`. |
| **speaker** | str | None | Speaker, included for U.S. Congressional speech
excerpts and Null for Reddit comments. |
| **chamber** | str | None | Chamber of Congress, 'S' for Senate,
'H' for House of Representatives, and
Null for Reddit comments. |
| **source** | str | "PRAW API" | The source or method of data collection. |
| **party** | str | None | The political party affiliation of the speaker,
available only for U.S. Congressional excerpts. |
> 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/).
# 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.",
}
```