
# Dataset Card for "imdb-javanese"

## Table of Contents

- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-instances)
  - [Data Splits Sample Size](#data-instances-sample-size)
- [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)

## Dataset Description

- **Homepage:** [Github](https://github.com/w11wo/nlp-datasets#javanese-imdb)
- **Repository:** [Github](https://github.com/w11wo/nlp-datasets#javanese-imdb)
- **Paper:** [Aclweb](http://www.aclweb.org/anthology/P11-1015)
- **Point of Contact:** [Wilson Wongso](https://github.com/w11wo)
- **Size of downloaded dataset files:** 17.0 MB
- **Size of the generated dataset:** 47.5 MB
- **Total amount of disk used:** 64.5 MB

### Dataset Summary

Large Movie Review Dataset translated to Javanese. This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training, and 25,000 for testing. There is additional unlabeled data for use as well. We translated the [original IMDB Dataset](https://huggingface.co/datasets/imdb) to Javanese using the multi-lingual MarianMT Transformer model from [`Helsinki-NLP/opus-mt-en-mul`](https://huggingface.co/Helsinki-NLP/opus-mt-en-mul).

### 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

We show detailed information for up to 5 configurations of the dataset.

### Data Instances

An example of `javanese_imdb_train.csv` looks as follows.

| label | text                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
| ----- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| 1     | "Drama romantik sing digawÃ© karo direktur Martin Ritt kuwi ora dingertÃ¨ni, nanging ana momen-momen sing marahi karisma lintang Jane Fonda lan Robert De Niro (kelompok sing luar biasa). DhÃ¨wÃ¨kÃ© dadi randha sing ora isa mlaku, iso anu anyar lan anyar-inventor-- kowÃ© isa nganggep isinÃ©. Adapsi novel Pat Barker ""Union Street"" (yak titel sing apik!) arep dinggo-back-back it on bland, lan pendidikan film kuwi gampang, nanging isih nyenengkÃ©; a rosy-hued-inventor-fantasi. Ora ana sing ngganggu gambar sing sejati ding kok iso dinggo nggawe gambar sing paling nyeneng."      |
| 0     | "Pengalaman wong lanang sing nduwÃ© perasaan sing ora lumrah kanggo babi. Mulai nganggo tuladha sing luar biasa yaiku komedia. Wong orkestra termel digawÃ© dadi wong gila, sing kasar merga nyanyian nyanyi. SayangÃ©, kuwi tetep absurd wektu WHOLE tanpa ceramah umum sing mung digawÃ©. Malah, sing ana ing jaman kuwi kudu ditinggalkÃ©. Diyalog kryptik sing nggawÃ© Shakespeare marah gampang kanggo kelas telu. Pak teknis kuwi luwih apik timbang kowe mikir nganggo cinematografi sing apik sing jenengÃ© Vilmos Zsmond. Masa depan bintang Saly Kirkland lan Frederic Forrest isa ndelok." |

### Data Fields

- `text`: The movie review translated into Javanese.
- `label`: The sentiment exhibited in the review, either `1` (positive) or `0` (negative).

### Data Splits Sample Size

| train | unsupervised |  test |
| ----: | -----------: | ----: |
| 25000 |        50000 | 25000 |

## 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
If you use this dataset in your research, please cite:

```
@inproceedings{wongso2021causal,
    title={Causal and Masked Language Modeling of Javanese Language using Transformer-based Architectures},
    author={Wongso, Wilson and Setiawan, David Samuel and Suhartono, Derwin},
    booktitle={2021 International Conference on Advanced Computer Science and Information Systems (ICACSIS)},
    pages={1--7},
    year={2021},
    organization={IEEE}
}
```

```
@InProceedings{maas-EtAl:2011:ACL-HLT2011,
  author    = {Maas, Andrew L.  and  Daly, Raymond E.  and  Pham, Peter T.  and  Huang, Dan  and  Ng, Andrew Y.  and  Potts, Christopher},
  title     = {Learning Word Vectors for Sentiment Analysis},
  booktitle = {Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies},
  month     = {June},
  year      = {2011},
  address   = {Portland, Oregon, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {142--150},
  url       = {http://www.aclweb.org/anthology/P11-1015}
}

```

task_categories:text-classification task_ids:sentiment-classification annotations_creators:found language_creators:machine-generated multilinguality:monolingual size_categories:10K<n<100K source_datasets:original language:jv license:odbl region:us
{"annotations_creators": ["found"], "language_creators": ["machine-generated"], "language": ["jv"], "license": ["odbl"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["sentiment-classification"], "extended": ["original"]}
TAGS
#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-found #language_creators-machine-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-Javanese #license-odbl #region-us 

Dataset Card for "imdb-javanese"
================================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks
	+ Languages
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splits Sample Size
* Dataset Creation
	+ Curation Rationale
	+ Source Data
	+ Annotations
	+ Personal and Sensitive Information
* Considerations for Using the Data
	+ Social Impact of Dataset
	+ Discussion of Biases
	+ Other Known Limitations
* Additional Information
	+ Dataset Curators
	+ Licensing Information
	+ Citation Information


Dataset Description
-------------------


* Homepage: Github
* Repository: Github
* Paper: Aclweb
* Point of Contact: Wilson Wongso
* Size of downloaded dataset files: 17.0 MB
* Size of the generated dataset: 47.5 MB
* Total amount of disk used: 64.5 MB


### Dataset Summary


Large Movie Review Dataset translated to Javanese. This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training, and 25,000 for testing. There is additional unlabeled data for use as well. We translated the original IMDB Dataset to Javanese using the multi-lingual MarianMT Transformer model from 'Helsinki-NLP/opus-mt-en-mul'.


### Supported Tasks and Leaderboards


### Languages


Dataset Structure
-----------------


We show detailed information for up to 5 configurations of the dataset.


### Data Instances


An example of 'javanese\_imdb\_train.csv' looks as follows.



### Data Fields


* 'text': The movie review translated into Javanese.
* 'label': The sentiment exhibited in the review, either '1' (positive) or '0' (negative).


### Data Splits Sample Size



Dataset Creation
----------------


### Curation Rationale


### Source Data


#### Initial Data Collection and Normalization


#### Who are the source language producers?


### Annotations


#### Annotation process


#### Who are the annotators?


### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


### Discussion of Biases


### Other Known Limitations


Additional Information
----------------------


### Dataset Curators


### Licensing Information


If you use this dataset in your research, please cite:



### Dataset Summary


Large Movie Review Dataset translated to Javanese. This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training, and 25,000 for testing. There is additional unlabeled data for use as well. We translated the original IMDB Dataset to Javanese using the multi-lingual MarianMT Transformer model from 'Helsinki-NLP/opus-mt-en-mul'. ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
-----------------


We show detailed information for up to 5 configurations of the dataset. ### Data Instances


An example of 'javanese\_imdb\_train.csv' looks as follows. ### Data Fields


* 'text': The movie review translated into Javanese.
* 'label': The sentiment exhibited in the review, either '1' (positive) or '0' (negative). ### Data Splits Sample Size



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information


If you use this dataset in your research, please cite:
TAGS
#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-found #language_creators-machine-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-Javanese #license-odbl #region-us 
 ### Dataset Summary


Large Movie Review Dataset translated to Javanese. This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training, and 25,000 for testing. There is additional unlabeled data for use as well. We translated the original IMDB Dataset to Javanese using the multi-lingual MarianMT Transformer model from 'Helsinki-NLP/opus-mt-en-mul'. ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
-----------------


We show detailed information for up to 5 configurations of the dataset. ### Data Instances


An example of 'javanese\_imdb\_train.csv' looks as follows. ### Data Fields


* 'text': The movie review translated into Javanese.
* 'label': The sentiment exhibited in the review, either '1' (positive) or '0' (negative). ### Data Splits Sample Size



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information


If you use this dataset in your research, please cite:
passage: TAGS
#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-found #language_creators-machine-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-Javanese #license-odbl #region-us 
### Dataset Summary


Large Movie Review Dataset translated to Javanese. This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training, and 25,000 for testing. There is additional unlabeled data for use as well. We translated the original IMDB Dataset to Javanese using the multi-lingual MarianMT Transformer model from 'Helsinki-NLP/opus-mt-en-mul'.### Supported Tasks and Leaderboards### Languages


Dataset Structure
-----------------


We show detailed information for up to 5 configurations of the dataset.### Data Instances


An example of 'javanese\_imdb\_train.csv' looks as follows.### Data Fields


* 'text': The movie review translated into Javanese.
* 'label': The sentiment exhibited in the review, either '1' (positive) or '0' (negative).### Data Splits Sample Size



Dataset Creation
----------------### Curation Rationale### Source Data#### Initial Data Collection and Normalization#### Who are the source language producers?### Annotations#### Annotation process#### Who are the annotators?### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------### Social Impact of Dataset### Discussion of Biases### Other Known Limitations


Additional Information
----------------------### Dataset Curators### Licensing Information


If you use this dataset in your research, please cite: