M-ABSA

This repo contains the data for our paper M-ABSA: A Multilingual Dataset for Aspect-Based Sentiment Analysis.

Data Description:

This is a dataset suitable for the multilingual ABSA task with triplet extraction.

All datasets are stored in the data/ folder:

• All dataset contains 7 domains.

domains = ["coursera", "hotel", "laptop", "restaurant", "phone", "sight", "food"]

• Each dataset contains 21 languages.

langs = ["ar", "da", "de", "en", "es", "fr", "hi", "hr", "id", "ja", "ko", "nl", "pt", "ru", "sk", "sv", "sw", "th", "tr", "vi", "zh"]

• The labels contain triplets with [aspect term, aspect category, sentiment polarity]. Each sentence is separated by "####", with the first part being the sentence and the second part being the corresponding triplet. Here is an example, where the triplet includes [aspect term, aspect category, sentiment polarity].

This coffee brews up a nice medium roast with exotic floral and berry notes .####[['coffee', 'food quality', 'positive']]

• Each dataset is divided into training, validation, and test sets.

Citation

If the code or dataset is used in your research, please star our repo and cite our paper as follows:

@inproceedings{wu-etal-2025-absa,
    title = "{M}-{ABSA}: A Multilingual Dataset for Aspect-Based Sentiment Analysis",
    author = "Wu, ChengYan  and
      Ma, Bolei  and
      Liu, Yihong  and
      Zhang, Zheyu  and
      Deng, Ningyuan  and
      Li, Yanshu  and
      Chen, Baolan  and
      Zhang, Yi  and
      Xue, Yun  and
      Plank, Barbara",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.emnlp-main.128/",
    doi = "10.18653/v1/2025.emnlp-main.128",
    pages = "2530--2557",
    ISBN = "979-8-89176-332-6",
}