参考：
byarticle
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:hyperpartisan_news_detection/byarticle')
- 说明：
Hyperpartisan News Detection was a dataset created for PAN @ SemEval 2019 Task 4.
Given a news article text, decide whether it follows a hyperpartisan argumentation, i.e., whether it exhibits blind, prejudiced, or unreasoning allegiance to one party, faction, cause, or person.
There are 2 parts:
- byarticle: Labeled through crowdsourcing on an article basis. The data contains only articles for which a consensus among the crowdsourcing workers existed.
- bypublisher: Labeled by the overall bias of the publisher as provided by BuzzFeed journalists or MediaBiasFactCheck.com.
- 许可：无已知许可
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'train' |
645 |
- 特征：
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hyperpartisan": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"url": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"published_at": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
bypublisher
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:hyperpartisan_news_detection/bypublisher')
- 说明：
Hyperpartisan News Detection was a dataset created for PAN @ SemEval 2019 Task 4.
Given a news article text, decide whether it follows a hyperpartisan argumentation, i.e., whether it exhibits blind, prejudiced, or unreasoning allegiance to one party, faction, cause, or person.
There are 2 parts:
- byarticle: Labeled through crowdsourcing on an article basis. The data contains only articles for which a consensus among the crowdsourcing workers existed.
- bypublisher: Labeled by the overall bias of the publisher as provided by BuzzFeed journalists or MediaBiasFactCheck.com.
- 许可：无已知许可
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'train' |
600000 |
'validation' |
600000 |
- 特征：
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hyperpartisan": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"url": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"published_at": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"bias": {
"num_classes": 5,
"names": [
"right",
"right-center",
"least",
"left-center",
"left"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}