BRIGHTER Dataset Organization

🌍 BRIdging the Gap in Human-Annotated Textual Emotion Recognition (BRIGHTER)

Welcome to the official Hugging Face organization for BRIGHTER - a multilingual emotion recognition dataset collection spanning 28 languages from 7 distinct language families.

🌐 Project Website

Visit our official project page for more information: https://brighter-dataset.github.io/

TL;DR

We introduce BRIGHTER: a new emotion recognition dataset collection in 28 languages that originate from 7 distinct language families. Many of these languages are considered low-resource, and are mainly spoken in regions characterised by a limited availability of NLP resources (e.g., Africa, Asia, Latin America).

Our contribuitions:

• A linguistically diverse multilingual dataset: BRIGHTER consists of nearly 100k emotion-annotated instances in 28 languages, predominantly from Africa, Asia, Eastern Europe, and Latin America. The dataset spans 7 language families and covers a variety of domains, including social media, speeches, news, literature, and reviews. Each instance is multi-labeled with six emotion classes — joy, sadness, anger, fear, surprise, disgust, and neutral — and annotated within four emotion intensity levels, ranging from 0 to 3.
• Baseline Evaluation: We provide an initial set of monolingual and crosslingual experiments, benchmarking Large Language Models (LLMs) for multi-label emotion identification and intensity prediction. Our results highlight the performance disparities across languages, showing that LLMs struggle with perceived emotions in text, especially for low-resource languages, and often perform better when prompted in English.

📖 Citation

If you use our datasets, please cite our papers:

@article{muhammad2025brighterbridginggaphumanannotated,
  title = {BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages},
  author = {Muhammad, Shamsuddeen Hassan and Ousidhoum, Nedjma and Abdulmumin, Idris and Wahle, Jan Philip and Ruas, Terry and Beloucif, Meriem and de Kock, Christine and Surange, Nirmal and Teodorescu, Daniela and Ahmad, Ibrahim Said and Adelani, David Ifeoluwa and Aji, Alham Fikri and Ali, Felermino D. M. A. and Alimova, Ilseyar and Araujo, Vladimir and Babakov, Nikolay and Baes, Naomi and Bucur, Ana-Maria and Bukula, Andiswa and Cao, Guanqun and Cardenas, Rodrigo Tufino and Chevi, Rendi and Chukwuneke, Chiamaka Ijeoma and Ciobotaru, Alexandra and Dementieva, Daryna and Gadanya, Murja Sani and Geislinger, Robert and Gipp, Bela and Hourrane, Oumaima and Ignat, Oana and Lawan, Falalu Ibrahim and Mabuya, Rooweither and Mahendra, Rahmad and Marivate, Vukosi and Piper, Andrew and Panchenko, Alexander and Porto Ferreira, Charles Henrique and Protasov, Vitaly and Rutunda, Samuel and Shrivastava, Manish and Udrea, Aura Cristina and Wanzare, Lilian Diana Awuor and Wu, Sophie and Wunderlich, Florian Valentin and Zhafran, Hanif Muhammad and Zhang, Tianhui and Zhou, Yi and Mohammad, Saif M.},
  journal = {arXiv preprint arXiv:2502.11926},
  year = {2025}
}

@inproceedings{muhammad-etal-2025-semeval,
  title = "{S}em{E}val-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection",
  author = "Muhammad, Shamsuddeen Hassan and Ousidhoum, Nedjma and Abdulmumin, Idris and Yimam, Seid Muhie and Wahle, Jan Philip and Ruas, Terry and Beloucif, Meriem and De Kock, Christine and Belay, Tadesse Destaw and Ahmad, Ibrahim Said and Surange, Nirmal and Teodorescu, Daniela and Adelani, David Ifeoluwa and Aji, Alham Fikri and Ali, Felermino and Araujo, Vladimir and Ayele, Abinew Ali and Ignat, Oana and Panchenko, Alexander and Zhou, Yi and Mohammad, Saif M.",
  booktitle = "Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)",
  month = july,
  year = "2025",
  address = "Vienna, Austria",
  publisher = "Association for Computational Linguistics",
  url = "",
  doi = "",
  pages = ""
}

📧 Contact

• Shamsuddeen Hassan Muhammad: s.muhammad@imperial.ac.uk
• Nedjma Ousidhoum: OusidhoumN@cardiff.ac.uk

*Equal contribution by lead authors.