---
title: "NusaX — paper by Winata et al. (2023) — summary and ideas"
description: "Most of Indonesia's 700+ languages have almost no public NLP datasets or benchmarks, even when… 73 references, cited by 74 papers here."
authors: ["Genta Indra Winata", "Alham Fikri Aji", "Samuel Cahyawijaya", "Rahmad Mahendra", "Fajri Koto", "Ade Romadhony", "Kemal Kurniawan", "David Moeljadi", "Radityo Eko Prasojo", "Pascale Fung", "Timothy Baldwin", "Jey Han Lau", "Rico Sennrich", "Sebastian Ruder"]
year: 2023
venue: "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics"
source: "https://aclanthology.org/2023.eacl-main.57/"
doi: "10.18653/v1/2023.eacl-main.57"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/winata-2023-nusax-multilingual-parallel-sentiment-dataset/"
---
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# NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languages

**Authors:** [Genta Indra Winata](https://md.research.elamur.ai/free/en/authors/genta-indra-winata/), [Alham Fikri Aji](https://md.research.elamur.ai/free/en/authors/alham-fikri-aji/), [Samuel Cahyawijaya](https://md.research.elamur.ai/free/en/authors/samuel-cahyawijaya/), [Rahmad Mahendra](https://md.research.elamur.ai/free/en/authors/rahmad-mahendra/), [Fajri Koto](https://md.research.elamur.ai/free/en/authors/fajri-koto/), Ade Romadhony, Kemal Kurniawan, David Moeljadi, Radityo Eko Prasojo, [Pascale Fung](https://md.research.elamur.ai/free/en/authors/pascale-fung/), [Timothy Baldwin](https://md.research.elamur.ai/free/en/authors/timothy-baldwin/), [Jey Han Lau](https://md.research.elamur.ai/free/en/authors/jey-han-lau/), [Rico Sennrich](https://md.research.elamur.ai/free/en/authors/rico-sennrich/) and [Sebastian Ruder](https://md.research.elamur.ai/free/en/authors/sebastian-ruder/) · **Year:** 2023 · **Venue:** [Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/eacl/) ([EACL 2023](https://md.research.elamur.ai/free/en/venues/eacl/2023/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2023.eacl-main.57/) · [PDF](https://aclanthology.org/2023.eacl-main.57.pdf) · [DOI 10.18653/v1/2023.eacl-main.57](https://doi.org/10.18653/v1/2023.eacl-main.57) · [OpenAlex](https://openalex.org/W4386566878)

**Citations:** 56 citations (OpenAlex, 2026-10-14) · [74](https://md.research.elamur.ai/free/en/papers/winata-2023-nusax-multilingual-parallel-sentiment-dataset/cited-by/) in our library, of the 141,840 papers whose bibliographies we read

## Summary
Most of Indonesia's 700+ languages have almost no public NLP datasets or benchmarks, even when they have millions of speakers. NusaX partly closes this gap by providing a human-built parallel resource that covers ten local languages: Javanese, Sundanese, Balinese, Madurese, Minangkabau, Acehnese, Banjarese, Buginese, Ngaju and Toba Batak. Each is aligned with Indonesian and English. The authors took a label-balanced sample of the Indonesian sentiment corpus SmSA (part of IndoNLU) and removed abusive and personal content by hand. Native bilingual annotators then translated it, preserving sentiment polarity, entities and full meaning, and a separate human quality check followed. Using Indonesian rather than English as the source keeps topics and entities culturally relevant. The resource supports sentiment analysis, machine translation and bilingual lexicons. It is used to benchmark classical machine learning, Indonesian LMs and multilingual LMs in few-shot and full-data settings. A central finding is that multilingual training beats monolingual training. Leaving the target language out of training entirely performs roughly as well as including it, so related languages can stand in for scarce target data. The paper also documents practical data-collection difficulties.

## Key points
- **Data source:** 1,000 sentences were drawn by stratified sampling from SmSA, which has over 11,000 comments and reviews from sources such as Twitter, Zomato and TripAdvisor. Each sentence was translated into all ten languages plus English.
- **Annotators:** Each language had at least 2 native-speaker annotators, screened through trial translations and peer intelligibility review. English translators needed IELTS ≥ 6.5 or TOEFL PBT ≥ 600.
- **Languages and script:** All ten are Austronesian (Malayo-Polynesian) languages from Sumatra, Borneo, Java, Madura and Sulawesi. All are written in Latin script in the dataset.
- **Collection hurdles:** Platforms like MTurk do not support these languages. Coordination ran through WhatsApp and spreadsheets, and some annotators worked on phones or even on paper.
- **Release and limitations:** The data is available at github.com/IndoNLP/nusax. The authors note limited domain coverage, possible translationese, self-reported fluency, and dialect choice that depends on the annotator.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

## Institutions

- [Google](https://md.research.elamur.ai/free/en/companies/google/) — Company, Mountain View, United States · 353 works · 364,806 citations
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- [The University of Melbourne](https://md.research.elamur.ai/free/en/universities/the-university-of-melbourne/) — University, Melbourne, Australia · 60 works · 21,199 citations
- [University of Zurich](https://md.research.elamur.ai/free/en/universities/university-of-zurich/) — University, Zurich, Switzerland · 50 works · 11,138 citations
- [University of Indonesia](https://md.research.elamur.ai/free/en/universities/university-of-indonesia/) — University, Depok, Indonesia · 3 works · 477 citations

Also on the byline: [Kanda University of International Studies](https://ror.org/04hx9jj82) · [Telkom University](https://ror.org/0004wsx81).

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## Cite

Cite as: Genta Indra Winata, Alham Fikri Aji, Samuel Cahyawijaya, Rahmad Mahendra, Fajri Koto, Ade Romadhony, Kemal Kurniawan, David Moeljadi, Radityo Eko Prasojo, Pascale Fung, Timothy Baldwin, Jey Han Lau, Rico Sennrich and Sebastian Ruder. 2023. NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languages. Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics.

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{winata2023nusax,
  title = {{NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languages}},
  author = {Genta Indra Winata, Alham Fikri Aji, Samuel Cahyawijaya, Rahmad Mahendra, Fajri Koto, Ade Romadhony, Kemal Kurniawan, David Moeljadi, Radityo Eko Prasojo, Pascale Fung, Timothy Baldwin, Jey Han Lau, Rico Sennrich and Sebastian Ruder},
  booktitle = {Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics},
  year = {2023},
  doi = {10.18653/v1/2023.eacl-main.57},
  url = {https://doi.org/10.18653/v1/2023.eacl-main.57}
}
```

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