数据集:

swedish_reviews

语言:

sv

计算机处理:

monolingual

语言创建人:

found

批注创建人:

found

源数据集:

original

大小:

100K<n<1M
中文

Dataset Card for Swedish Reviews

Dataset Summary

The dataset is scraped from various Swedish websites where reviews are present. The dataset consists of 103 482 samples split between train , valid and test . It is a sample of the full dataset, where this sample is balanced to the minority class (negative). The original data dump was heavly skewved to positive samples with a 95/5 ratio.

Supported Tasks and Leaderboards

This dataset can be used to evaluate sentiment classification on Swedish.

Languages

The text in the dataset is in Swedish.

Dataset Structure

Data Instances

What a sample looks like:

{
 'text': 'Jag tycker huggingface är ett grymt project!',
 'label': 1,
}

Data Fields

  • text : A text where the sentiment expression is present.
  • label : a int representing the label 0 for negative and 1 for positive.

Data Splits

The data is split into a training, validation and test set. The final split sizes are as follow:

Train Valid Test
62089 20696 20697

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Various Swedish websites with product reviews.

Initial Data Collection and Normalization Who are the source language producers?

Swedish

Annotations

[More Information Needed]

Annotation process

Automatically annotated based on user reviews on a scale 1-5, where 1-2 is considered negative and 4-5 is positive , 3 is skipped as it tends to be more neutral.

Who are the annotators?

The users who have been using the products.

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

[More Information Needed]

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

[More Information Needed]

Dataset Curators

The corpus was scraped by @timpal0l

Licensing Information

Research only.

Citation Information

No paper exists currently.

Contributions

Thanks to @timpal0l for adding this dataset.