Dataset:

Task Categories: text-classification
Languages: jv
Multilinguality: monolingual
Size Categories: 10K<n<100K
Licenses: odbl-1.0
Language Creators: machine-generated
Annotations Creators: found
Source Datasets: original

Dataset Card for "imdb-javanese"

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

More Information Needed

Languages

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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 digawé karo direktur Martin Ritt kuwi ora dingertèni, nanging ana momen-momen sing marahi karisma lintang Jane Fonda lan Robert De Niro (kelompok sing luar biasa). Dhèwèké dadi randha sing ora isa mlaku, iso anu anyar lan anyar-inventor-- kowé isa nganggep isiné. Adapsi novel Pat Barker ""Union Street"" (yak titel sing apik!) arep dinggo-back-back it on bland, lan pendidikan film kuwi gampang, nanging isih nyenengké; 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 nduwé perasaan sing ora lumrah kanggo babi. Mulai nganggo tuladha sing luar biasa yaiku komedia. Wong orkestra termel digawé dadi wong gila, sing kasar merga nyanyian nyanyi. Sayangé, kuwi tetep absurd wektu WHOLE tanpa ceramah umum sing mung digawé. Malah, sing ana ing jaman kuwi kudu ditinggalké. Diyalog kryptik sing nggawé Shakespeare marah gampang kanggo kelas telu. Pak teknis kuwi luwih apik timbang kowe mikir nganggo cinematografi sing apik sing jenengé 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

Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

@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}
}

Models trained or fine-tuned on w11wo/imdb-javanese