google-research-datasets/coarse_discourse

---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-class-classification
paperswithcode_id: coarse-discourse
pretty_name: Coarse Discourse
dataset_info:
features:
- name: title
dtype: string
- name: is_self_post
dtype: bool
- name: subreddit
dtype: string
- name: url
dtype: string
- name: majority_link
dtype: string
- name: is_first_post
dtype: bool
- name: majority_type
dtype: string
- name: id_post
dtype: string
- name: post_depth
dtype: int32
- name: in_reply_to
dtype: string
- name: annotations
sequence:
- name: annotator
dtype: string
- name: link_to_post
dtype: string
- name: main_type
dtype: string
splits:
- name: train
num_bytes: 45097556
num_examples: 116357
download_size: 4256575
dataset_size: 45097556
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---

# Dataset Card for "coarse_discourse"

## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)

## Dataset Description

- **Homepage:**
- **Repository:** https://github.com/google-research-datasets/coarse-discourse
- **Paper:** [Characterizing Online Discussion Using Coarse Discourse Sequences](https://research.google/pubs/pub46055/)
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Size of downloaded dataset files:** 4.63 MB
- **Size of the generated dataset:** 45.45 MB
- **Total amount of disk used:** 50.08 MB

### Dataset Summary

A large corpus of discourse annotations and relations on ~10K forum threads.

We collect and release a corpus of over 9,000 threads comprising over 100,000 comments manually annotated via paid crowdsourcing with discourse acts and randomly sampled from the site Reddit.

### Supported Tasks and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Dataset Structure

### Data Instances

#### default

- **Size of downloaded dataset files:** 4.63 MB
- **Size of the generated dataset:** 45.45 MB
- **Total amount of disk used:** 50.08 MB

An example of 'train' looks as follows.
```
{
"annotations": {
"annotator": ["fc96a15ab87f02dd1998ff55a64f6478", "e9e4b3ab355135fa954badcc06bfccc6", "31ac59c1734c1547d4d0723ff254c247"],
"link_to_post": ["", "", ""],
"main_type": ["elaboration", "elaboration", "elaboration"]
},
"id_post": "t1_c9b30i1",
"in_reply_to": "t1_c9b2nyd",
"is_first_post": false,
"is_self_post": true,
"majority_link": "t1_c9b2nyd",
"majority_type": "elaboration",
"post_depth": 2,
"subreddit": "100movies365days",
"title": "DTX120: #87 - Nashville",
"url": "https://www.reddit.com/r/100movies365days/comments/1bx6qw/dtx120_87_nashville/"
}
```

### Data Fields

The data fields are the same among all splits.

#### default
- `title`: a `string` feature.
- `is_self_post`: a `bool` feature.
- `subreddit`: a `string` feature.
- `url`: a `string` feature.
- `majority_link`: a `string` feature.
- `is_first_post`: a `bool` feature.
- `majority_type`: a `string` feature.
- `id_post`: a `string` feature.
- `post_depth`: a `int32` feature.
- `in_reply_to`: a `string` feature.
- `annotations`: a dictionary feature containing:
- `annotator`: a `string` feature.
- `link_to_post`: a `string` feature.
- `main_type`: a `string` feature.

### Data Splits

| name |train |
|-------|-----:|
|default|116357|

## Dataset Creation

### Curation Rationale

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the source language producers?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the annotators?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Personal and Sensitive Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Citation Information

```
@inproceedings{coarsediscourse, title={Characterizing Online Discussion Using Coarse Discourse Sequences}, author={Zhang, Amy X. and Culbertson, Bryan and Paritosh, Praveen}, booktitle={Proceedings of the 11th International AAAI Conference on Weblogs and Social Media}, series={ICWSM '17}, year={2017}, location = {Montreal, Canada} }

```

### Contributions

Thanks to [@thomwolf](https://github.com/thomwolf), [@lewtun](https://github.com/lewtun), [@jplu](https://github.com/jplu) for adding this dataset.

原始信息汇总

数据集概述

数据集摘要

Coarse Discourse 数据集是一个包含约10,000个论坛帖子的大规模语料库，涵盖超过100,000条评论，这些评论通过付费众包手动标注了话语行为，并从Reddit网站随机抽样得到。

支持的任务和排行榜

该数据集支持的任务类别是文本分类，具体任务是多类别分类。

语言

数据集的语言是英语。

数据集结构

数据实例

一个训练集的示例如下：

json { "annotations": { "annotator": ["fc96a15ab87f02dd1998ff55a64f6478", "e9e4b3ab355135fa954badcc06bfccc6", "31ac59c1734c1547d4d0723ff254c247"], "link_to_post": ["", "", ""], "main_type": ["elaboration", "elaboration", "elaboration"] }, "id_post": "t1_c9b30i1", "in_reply_to": "t1_c9b2nyd", "is_first_post": false, "is_self_post": true, "majority_link": "t1_c9b2nyd", "majority_type": "elaboration", "post_depth": 2, "subreddit": "100movies365days", "title": "DTX120: #87 - Nashville", "url": "https://www.reddit.com/r/100movies365days/comments/1bx6qw/dtx120_87_nashville/" }

数据字段

数据集包含以下字段：

• title: 字符串类型，帖子标题。
• is_self_post: 布尔类型，是否为自发布。
• subreddit: 字符串类型，子版块名称。
• url: 字符串类型，帖子URL。
• majority_link: 字符串类型，主要链接。
• is_first_post: 布尔类型，是否为首帖。
• majority_type: 字符串类型，主要类型。
• id_post: 字符串类型，帖子ID。
• post_depth: 整数类型，帖子深度。
• in_reply_to: 字符串类型，回复对象。
• annotations: 字典类型，包含以下子字段：
  • annotator: 字符串类型，标注者。
  • link_to_post: 字符串类型，帖子链接。
  • main_type: 字符串类型，主要类型。

数据分割

数据集只有一个训练集，包含116,357个样本。

数据集创建

数据集来源

数据集的来源是原始数据。

标注过程

数据集的标注是由众包完成的。

许可证信息

数据集的许可证是CC-BY-4.0。

引用信息

bibtex @inproceedings{coarsediscourse, title={Characterizing Online Discussion Using Coarse Discourse Sequences}, author={Zhang, Amy X. and Culbertson, Bryan and Paritosh, Praveen}, booktitle={Proceedings of the 11th International AAAI Conference on Weblogs and Social Media}, series={ICWSM 17}, year={2017}, location = {Montreal, Canada} }

搜集汇总

背景与挑战

背景概述

Coarse Discourse数据集是一个包含约10,000个Reddit论坛线程和超过100,000条评论的大型语料库，这些评论通过付费众包进行了话语行为标注。数据集适用于多类文本分类任务，主要用于研究在线讨论的话语结构。